E. Xing

Wei Wu, Michael I. Jordan, Richard M. Karp, 2003, Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003.

Bayesian multi-population haplotype inference via a hierarchical dirichlet process mixture

Yee Whye Teh, Michael I. Jordan, Eric P. Xing, 2006, ICML.

Discrete Temporal Models of Social Networks

E. Xing, Wenjie Fu, Steve Hanneke, 2006, SNA@ICML.

An E-cient Proximal Gradient Method for General Structured Sparse Learning

E. Xing, X. Chen, J. Carbonell, 2010 .

MedLDA: maximum margin supervised topic models for regression and classification

Eric P. Xing, Jun Zhu, Amr Ahmed, 2009, ICML '09.

Harnessing Deep Neural Networks with Logic Rules pdf

Eric P. Xing, Zhiting Hu, Eduard H. Hovy, 2016, ACL.

Automatic mining of fruit fly embryo images

Christos Faloutsos, Eric P. Xing, Agma J. M. Traina, 2006, KDD '06.

An Efficient Proximal-Gradient Method for Single and Multi-task Regression with Structured Sparsity pdf

Xi Chen, Jaime G. Carbonell, Eric P. Xing, 2010, ArXiv.

Mining Associated Text and Images with Dual-Wing Harmoniums pdf

Rong Yan, Eric P. Xing, Alexander G. Hauptmann, 2005, UAI.

Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-slide Images

Michael Kampffmeyer, Eric P. Xing, Xiaodan Liang, 2018, DLMIA/ML-CDS@MICCAI.

Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces

Andrew Gordon Wilson, Eric P. Xing, Daniel B. Neill, 2015, AISTATS.

An Adaptive Learning Rate for Stochastic Variational Inference

Chong Wang, Eric P. Xing, David M. Blei, 2013, ICML.

Online detection of unusual events in videos via dynamic sparse coding

Fei-Fei Li, Eric P. Xing, Bin Zhao, 2011, CVPR 2011.

SCAN: Structure Correcting Adversarial Network for Chest X-rays Organ Segmentation pdf

Yuan Li, Eric P. Xing, Hao Zhang, 2017, ArXiv.

Large Margin Learning of Upstream Scene Understanding Models

Fei-Fei Li, Eric P. Xing, Jun Zhu, 2010, NIPS.

A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks

Eric P. Xing, Qirong Ho, Junming Yin, 2013, NIPS.

Large-Scale Category Structure Aware Image Categorization

Eric P. Xing, Bin Zhao, Fei Li, 2011, NIPS.

Scalable Time-Decaying Adaptive Prediction Algorithm

Eric P. Xing, Guilin Li, Qirong Ho, 2016, KDD.

Screening Rules for Overlapping Group Lasso pdf

Seunghak Lee, Eric P. Xing, E. Xing, 2014, ArXiv.

The Human Kernel

Andrew Gordon Wilson, Eric P. Xing, Christopher G. Lucas, 2015, NIPS.

Integrating Document Clustering and Topic Modeling pdf

Pengtao Xie, Eric P. Xing, E. Xing, 2013, UAI.

Missing Value Imputation Based on Deep Generative Models pdf

Pengtao Xie, Eric P. Xing, Hongbao Zhang, 2018, ArXiv.

A Neural Architecture for Automated ICD Coding

Pengtao Xie, Eric P. Xing, Haoran Shi, 2018, ACL.

Exact Algorithms for Isotonic Regression and Related

E. Xing, Yaoliang Yu, 2016 .

Learning Less-Overlapping Representations pdf

Pengtao Xie, Eric P. Xing, Hongbao Zhang, 2017, ArXiv.

Controllable Text Generation pdf

Eric P. Xing, Zhiting Hu, Ruslan Salakhutdinov, 2017, ArXiv.

Hybrid Retrieval-Generation Reinforced Agent for Medical Image Report Generation

Eric P. Xing, Zhiting Hu, Xiaodan Liang, 2018, NeurIPS.

Improved Estimation of High-dimensional Ising Models

E. Xing, M. Kolar, 2008, 0811.1239.

Neural Architecture Search for Adversarial Medical Image Segmentation

Eric P. Xing, Wei Dai, Min Xu, 2019, MICCAI.

BiTAM: Bilingual Topic AdMixture Models for Word Alignment

Eric P. Xing, Bing Zhao, E. Xing, 2006, ACL.

On the Origin of Deep Learning pdf

Bhiksha Raj, Eric P. Xing, Haohan Wang, 2017, ArXiv.

Diffusion of Lexical Change in Social Media

Eric P. Xing, Jacob Eisenstein, Noah A. Smith, 2012, PloS one.

High-Frequency Component Helps Explain the Generalization of Convolutional Neural Networks

Eric P. Xing, Haohan Wang, Pengcheng Yin, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

An Efficient Nonlinear Regression Approach for Genome-Wide Detection of Marginal and Interacting Genetic Variations

Seunghak Lee, Eric P. Xing, Prabhanjan Kambadur, 2015, RECOMB.

Distributed, partially collapsed MCMC for Bayesian Nonparametrics pdf

Eric P. Xing, Avinava Dubey, Michael Minyi Zhang, 2020, AISTATS.

Sparse Topical Coding pdf

Eric P. Xing, Jun Zhu, E. Xing, 2011, UAI.

Network Analysis of Breast Cancer Progression and Reversal Using a Tree-Evolving Network Algorithm

Eric P. Xing, Ankur P. Parikh, Ross E. Curtis, 2014, PLoS Comput. Biol..

A penalized regression model for the joint estimation of eQTL associations and gene network structure

Yaoliang Yu, Eric P. Xing, Wei Wu, 2019, The Annals of Applied Statistics.

Sample Complexity of Nonparametric Semi-Supervised Learning pdf

Pradeep Ravikumar, Eric P. Xing, Chen Dan, 2018, NIPS 2018.

Learning Robust Representations by Projecting Superficial Statistics Out pdf

Eric P. Xing, Zachary C. Lipton, Zexue He, 2018, ICLR.

Ensembles of Lasso Screening Rules

Eric P. Xing, Christoph Lippert, Nico Görnitz, 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

DAGs with NO TEARS: Smooth Optimization for Structure Learning pdf

Pradeep Ravikumar, Eric P. Xing, Xun Zheng, 2018, ArXiv.

Spatial compactness meets topical consistency: jointly modeling links and content for community detection

Eric P. Xing, Mrinmaya Sachan, Eduard H. Hovy, 2014, WSDM.

An Efficient Nonlinear Regression Approach for Genome-Wide Detection of Marginal and Interacting Genetic Variations

Seunghak Lee, Eric P. Xing, Prabhanjan Kambadur, 2015, RECOMB.

Evaluation of normalization methods for cDNA microarray data by k-NN classification

Wei Wu, Eric P. Xing, Mina J. Bissell, 2005, BMC Bioinformatics.

Science Question Answering using Instructional Materials pdf

Eric P. Xing, Mrinmaya Sachan, Kumar Avinava Dubey, 2016, ACL.

Consistent Covariance Selection From Data With Missing Values

Eric P. Xing, Mladen Kolar, E. Xing, 2012, ICML.

Learning Answer-Entailing Structures for Machine Comprehension

Eric P. Xing, Matthew Richardson, Mrinmaya Sachan, 2015, ACL.

Smoothing proximal gradient method for general structured sparse regression

Xi Chen, Jaime G. Carbonell, Eric P. Xing, 2010, The Annals of Applied Statistics.

Quasi Real-Time Summarization for Consumer Videos

Bin Zhao, Eric P. Xing, E. Xing, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Semantic Concept Discovery for Large-Scale Zero-Shot Event Detection

Yi Yang, Yaoliang Yu, Eric P. Xing, 2015, IJCAI.

A Multiscale Community Blockmodel for Network Exploration

Le Song, Eric P. Xing, Ankur P. Parikh, 2011, AISTATS.

Minimizing Nonconvex Non-Separable Functions

Yaoliang Yu, Eric P. Xing, Xun Zheng, 2015, AISTATS.

Linear Time Samplers for Supervised Topic Models using Compositional Proposals

Yaoliang Yu, Eric P. Xing, Xun Zheng, 2015, KDD.

On Topic Evolution

E. Xing, 2005 .

Stability Selection for Structured Variable Selection pdf

Seunghak Lee, Eric P. Xing, George Philipp, 2017, ArXiv.

Leveraging input and output structures for joint mapping of epistatic and marginal eQTLs

Seunghak Lee, Eric P. Xing, E. Xing, 2012, Bioinform..

Regularizing Black-box Models for Improved Interpretability pdf

Ameet Talwalkar, Eric P. Xing, Maruan Al-Shedivat, 2019, NeurIPS.

Structured Input-Output Lasso, with Application to eQTL Mapping, and a Thresholding Algorithm for Fast Estimation

Seunghak Lee, Eric P. Xing, E. Xing, 2012, 1205.1989.

A multivariate regression approach to association analysis of a quantitative trait network

Eric P. Xing, Kyung-Ah Sohn, Seyoung Kim, 2008, Bioinform..

Smoothing Proximal Gradient Method for General Structured Sparse Learning

Xi Chen, Jaime G. Carbonell, Eric P. Xing, 2011, UAI.

Recovering temporally rewiring networks: a model-based approach

Wenjie Fu, Fan Guo, Eric P. Xing, 2007, ICML '07.

Litz: Elastic Framework for High-Performance Distributed Machine Learning

Abutalib Aghayev, Eric P. Xing, Garth A. Gibson, 2018, USENIX Annual Technical Conference.

Toward Controlled Generation of Text

Eric P. Xing, Zhiting Hu, Ruslan Salakhutdinov, 2017, ICML.

Learning GMRF Structures for Spatial Priors

Takeo Kanade, Eric P. Xing, Lie Gu, 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-Rays

Eric P. Xing, Hao Zhang, Xiaodan Liang, 2017, DLMIA/ML-CDS@MICCAI.

Automating Dependence-Aware Parallelization of Machine Learning Training on Distributed Shared Memory

Eric P. Xing, Phillip B. Gibbons, Garth A. Gibson, 2019, EuroSys.

On the Generalization Error Bounds of Neural Networks under Diversity-Inducing Mutual Angular Regularization pdf

Pengtao Xie, Eric P. Xing, Yuntian Deng, 2015, ArXiv.

Dependent nonparametric trees for dynamic hierarchical clustering

Eric P. Xing, Qirong Ho, Kumar Avinava Dubey, 2014, NIPS.

Deep Variation-Structured Reinforcement Learning for Visual Relationship and Attribute Detection

Eric P. Xing, Xiaodan Liang, Lisa Lee, 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Dynamic Non-Parametric Mixture Models and the Recurrent Chinese Restaurant Process: with Applications to Evolutionary Clustering

Eric P. Xing, Amr Ahmed, E. Xing, 2008, SDM.

Dynamic Nonparametric Bayesian Models And the Birth-Death Process

E. Xing, 2006 .

mStruct: a new admixture model for inference of population structure in light of both genetic admixing and allele mutations

Eric P. Xing, Suyash Shringarpure, E. Xing, 2008, ICML '08.

Hidden Markov Dirichlet process: modeling genetic inference in open ancestral space

Eric P. Xing, Kyung-Ah Sohn, E. Xing, 2007 .

Strategies and Principles of Distributed Machine Learning on Big Data pdf

Pengtao Xie, Eric P. Xing, Wei Dai, 2015, ArXiv.

Document hierarchies from text and links

Eric P. Xing, Jacob Eisenstein, Qirong Ho, 2012, WWW.

Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity

Eric P. Xing, Seyoung Kim, E. Xing, 2009, ICML.

TREEGL: reverse engineering tree-evolving gene networks underlying developing biological lineages

Wei Wu, Eric P. Xing, Ankur P. Parikh, 2011, Bioinform..

Parsing to Programs: A Framework for Situated QA

Eric P. Xing, Mrinmaya Sachan, E. Xing, 2018, KDD.

Sparse Additive Generative Models of Text

Eric P. Xing, Jacob Eisenstein, Amr Ahmed, 2011, ICML.

Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering

Pengtao Xie, Eric P. Xing, Kun Zhang, 2019, NeurIPS.

Stacking Dependency Parsers

Eric P. Xing, Noah A. Smith, André F. T. Martins, 2008, EMNLP.

Theoretically Principled Trade-off between Robustness and Accuracy

Michael I. Jordan, Eric P. Xing, Laurent El Ghaoui, 2019, ICML.

LOGOS: a modular Bayesian model for de novo motif detection

Wei Wu, Michael I. Jordan, Richard M. Karp, 2003, Computational Systems Bioinformatics. CSB2003. Proceedings of the 2003 IEEE Bioinformatics Conference. CSB2003.

Recovering time-varying networks of dependencies in social and biological studies

Amr Ahmed, Eric P Xing, E. Xing, 2009, Proceedings of the National Academy of Sciences.

MoGUL: Detecting Common Insertions and Deletions in a Population

Seunghak Lee, Eric P. Xing, Michael Brudno, 2010, RECOMB.

Adaptive Multi-Task Lasso: with Application to eQTL Detection

Seunghak Lee, Eric P. Xing, Jun Zhu, 2010, NIPS.

Fast Distribution To Real Regression

Barnabás Póczos, Eric P. Xing, Jeff G. Schneider, 2013, AISTATS.

A network-driven approach for genome-wide association mapping

Seunghak Lee, Eric P. Xing, Soonho Kong, 2016, Bioinform..

Bayesian haplo-type inference via the dirichlet process

Roded Sharan, Michael I. Jordan, Eric P. Xing, 2004, ICML.

Asymptotically Exact, Embarrassingly Parallel MCMC pdf

Chong Wang, Eric P. Xing, Willie Neiswanger, 2013, UAI.

Contextual Explanation Networks pdf

Eric P. Xing, Maruan Al-Shedivat, Avinava Dubey, 2017, J. Mach. Learn. Res..

CIRL: Controllable Imitative Reinforcement Learning for Vision-based Self-driving pdf

Eric P. Xing, Xiaodan Liang, Luona Yang, 2018, ECCV.

Estimating sparse precision matrices from data with missing values

E. Xing, M. Kolar, 2012, ICML 2012.

Structured Databases of Named Entities from Bayesian Nonparametrics

Eric P. Xing, Noah A. Smith, William W. Cohen, 2011, ULNLP@EMNLP.

Personalized Regression Enables Sample-Specific Pan-Cancer Analysis

Eric P. Xing, Bryon Aragam, Benjamin J. Lengerich, 2018, bioRxiv.

Dynamic Language Models for Streaming Text

Chong Wang, Eric P. Xing, Noah A. Smith, 2014, TACL.

Interpreting anonymous DNA samples from mass disasters - probabilistic forensic inference using genetic markers

Eric P. Xing, Eugene W. Myers, Tien-ho Lin, 2006, ISMB.

Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio pdf

Michael Kampffmeyer, Eric P. Xing, Xiaodan Liang, 2018, MICCAI.

Deep Learning Based Supervised Semantic Segmentation of Electron Cryo-Subtomograms

Eric P. Xing, Chang Liu, Min Xu, 2018, 2018 25th IEEE International Conference on Image Processing (ICIP).

Latent Variable Modeling with Diversity-Inducing Mutual Angular Regularization pdf

Pengtao Xie, Eric P. Xing, Yuntian Deng, 2015, ArXiv.

Learning Scalable Deep Kernels with Recurrent Structure

Andrew Gordon Wilson, Eric P. Xing, Zhiting Hu, 2016, J. Mach. Learn. Res..

Monte Carlo Methods for Maximum Margin Supervised Topic Models

Maosong Sun, Eric P. Xing, Jun Zhu, 2012, NIPS.

Learning Data Manipulation for Augmentation and Weighting

Tom M. Mitchell, Eric P. Xing, Zhiting Hu, 2019, NeurIPS.

Evolving Cluster Mixed-Membership Blockmodel for Time-Evolving Networks

Le Song, Eric P. Xing, Qirong Ho, 2011, AISTATS.

Nonparametric Latent Tree Graphical Models: Inference, Estimation, and Structure Learning

Ankur P. Parikh, E. Xing, Han Liu, 2014, 1401.3940.

A Spectral Algorithm for Latent Tree Graphical Models

Le Song, Eric P. Xing, Ankur P. Parikh, 2011, ICML.

Staying Informed: Supervised and Semi-Supervised Multi-View Topical Analysis of Ideological Perspective

Eric P. Xing, Amr Ahmed, E. Xing, 2010, EMNLP.

WGAN domain adaptation for the joint optic disc-and-cup segmentation in fundus images

Eric Xing, Zeya Wang, Shreya Kadambi, 2020, International Journal of Computer Assisted Radiology and Surgery.

Image-derived generative modeling of pseudo-macromolecular structures - towards the statistical assessment of Electron CryoTomography template matching

Eric P. Xing, Min Xu, Xiaodan Liang, 2018, BMVC.

TopicViz: interactive topic exploration in document collections

Aniket Kittur, Eric P. Xing, Jacob Eisenstein, 2012, CHI Extended Abstracts.

Conditional graphical models for protein structure prediction

E. Xing, J. Lafferty, J. Carbonell, 2006 .

Poseidon : An Efficient Communication Interface for Distributed Deep Learning on GPU Clusters

E. Xing, Qirong Ho, Zeyu Zheng, 2017 .

Structured Sparse Regression Methods for Learning from High-Dimensional Genomic Data

E. Xing, Su-In Lee, Seyoung Kim, 2021 .

Inference of multiple-wave population admixture by modeling decay of linkage disequilibrium with polynomial functions

E P Xing, E. Xing, P. Xie, 2016, Heredity.

Structured Generative Adversarial Networks 1

E. Xing, Shizhen Xu, Xiaodan Liang, 2017 .

Deep Belief Nets for Topic Modeling Workshop on Knowledge-Powered Deep Learning for Text Mining (KPDLTM-2014)

E. P. Xing, T. Jebara, E. Xing, 2015 .

Scalable GP-LSTMs with Semi-Stochastic Gradients

A. G. Wilson, E. Xing, Zhiting Hu, 2016 .

Robust Estimation of Local Genetic Ancestry in Admixed Populations Using a Nonparametric Bayesian Approach

E. Xing, Zoubin Ghahramani, Kyung-ah Sohn, 2012, Genetics.

13 15 4 v 1 [ cs . C L ] 2 8 Se p 20 19 Generalized Zero-shot ICD Coding

E. Xing, P. Xie, Congzheng Song, 2019 .

Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks

Tom Michael Mitchell, E. Xing, D. Roth, 2019, Computational Linguistics.

PLOS ONE: Diffusion of Lexical Change in Social Media

Brendan T. O'Connor, Noah A. Smith, E. Xing, 2015 .

M L ] 3 0 Ja n 20 18 Bayesian Nonparametric Kernel-Learning

Junier B. Oliva, A. G. Wilson, E. Xing, 2018 .

SMPFRAME : A Distributed Framework for Scheduled Model Parallel Machine Learning

Garth A. Gibson, E. Xing, Qirong Ho, 2015 .

Learning ancestral genetic processes using nonparametric bayesian models

E. Xing, Kyung-ah Sohn, 2011 .

March 1 , 2010 DRAFT Learning Structured Classifiers with Dual Coordinate Descent

André F. T. Martins, Mário A. T. Figueiredo, Noah A. Smith, 2010 .

Bayesian Exponential Family Harmoniums

E. Xing, Fan Guo, 2004 .

Proceedings for 20th Annual Conference on Neural Information Processing Systems (NIPS)

Andrew Gordon Wilson, Eric P. Xing, Christopher G. Lucas, 2015 .

Learning Time-Varying Graphs using Temporally Smoothed L 1-Regularized Logistic Regression

E. Xing, Amr Ahmed, 2008 .

Inferring regulatory networks using a hierarchical Bayesian graphical Gaussian model

Yiming Yang, Eric Xing, E. Xing, 2005 .

Multiplex Confounding Factor Correction for Genomic Association Mapping with Squared Sparse Linear Mixed Model

Eric P. Xing, Yunpeng Xiao, Haohan Wang, 2017, bioRxiv.

Capturing characteristic structural features for motif detection using a hierarchical Bayesian Markovian model

E. Xing, 2007 .

20 : Hierarchical Dirichlet Processes

E. Xing, Lavanya Viswanathan, 2014 .

Timelines : Recovering Birth and Evolution of Topics In Scientific Literature Using Dynamic Non-Parametric Bayesian Models

Eric Xing, Amr Ahmed, E. Xing, 2009 .

Proceedings of the 2006 conference on Statistical network analysis

Edoardo M. Airoldi, Eric P. Xing, Stephen E. Fienberg, 2006 .

Latent Aspects Analysis : From Independence to Contagion

E. Xing, S. Fienberg, E. Airoldi, 2006 .

STRADS-AP: Simplifying Distributed Machine Learning Programming

E. Xing, Jin Kyu Kim, G. Gibson, 2018 .

Proceedings of the 31st International Conference on International Conference on Machine Learning - Volume 32

Eric P. Xing, Tony Jebara, E. Xing, 2014 .

A Hidden Markov Dirichlet Process Model for Genetic Recombination in Open Ancestral Space

E. Xing, Kyung-ah Sohn, 2007 .

Effects of Sample Selection Bias on the Accuracy of Population Structure and Ancestry Inference

Eric P. Xing, E. Xing, S. Shringarpure, 2014, G3: Genes, Genomes, Genetics.

Analyzing Time-Evolving Networks using an Evolving Cluster Mixed Membership Blockmodel

E. Xing, Qirong Ho, 2014 .

Towards Visual Question Answering on Pathology Images

Pengtao Xie, Eric P. Xing, Luntian Mou, 2021, ACL.

Backward genotype-transcript-phenotype association mapping.

E. Xing, Seunghak Lee, Haohan Wang, 2017, Methods.

STRADS-AP: Simplifying Distributed Machine Learning Programming without Introducing a New Programming Model

Abutalib Aghayev, Eric P. Xing, Garth A. Gibson, 2019, USENIX Annual Technical Conference.

Prototypical Graph Contrastive Learning pdf

Eric Xing, Liang Lin, Ruihui Zhao, 2021, ArXiv.

Graph-structured Sparse Mixed Models for Genetic Association with Confounding Factors Correction

Eric P. Xing, Wei Wu, Haohan Wang, 2019, 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

GINI: From ISH Images to Gene Interaction Networks

Eric P. Xing, Kriti Puniyani, E. Xing, 2013, PLoS Comput. Biol..

Seeking The Truly Correlated Topic Posterior - on tight approximate inference of logistic-normal admixture model

Eric P. Xing, Amr Ahmed, E. Xing, 2007, AISTATS.

Bayesian Inference with Posterior Regularization and Infinite Latent Support Vector Machines pdf

Ning Chen, Eric P. Xing, Jun Zhu, 2012, ArXiv.

Bayesian Inference with Posterior Regularization and Infinite Latent SVMs

Eric P. Xing, Jun Zhu, Ning Chen, 2012 .

RLPrompt: Optimizing Discrete Text Prompts With Reinforcement Learning

E. Xing, Zhiting Hu, Jianyu Wang, 2022, ArXiv.

BertNet: Harvesting Knowledge Graphs from Pretrained Language Models

E. Xing, Zhiting Hu, Bowen Tan, 2022, ArXiv.

Discovering weaker genetic associations guided by known associations

E. Xing, Haohan Wang, Wei Wu, 2020, BMC Medical Genomics.

M L ] 2 0 A pr 2 01 3 Graph Estimation From Multi-attribute Data

E. Xing, Han Liu, M. Kolar, 2013 .

Artificial selection experiments for association in model organisms

E. Xing, S. Shringarpure, 2012 .

Structured association analysis leads to insight into Saccharomyces cerevisiae gene regulation by finding multiple contributing eQTL hotspots associated with functional gene modules

Ross E. Curtis, E. Xing, Seyoung Kim, 2013, BMC Genomics.

Consistency Models for Distributed ML with Theoretical Guarantees

Eric P. Xing, Xun Zheng, Wei Dai, 2013 .

More Effective Distributed ML via a Structure-Aware Dynamic Scheduler

Seunghak Lee, Eric P. Xing, Garth A. Gibson, 2013 .

Discovery of the gene signature for acute lung injury in patients with sepsis.

E. Xing, D. Christiani, A. Choi, 2009, Physiological genomics.

Semantic-Aligned Matching for Enhanced DETR Convergence and Multi-Scale Feature Fusion

E. Xing, Shijian Lu, Zhipeng Luo, 2022, ArXiv.

MRCLens: an MRC Dataset Bias Detection Toolkit

E. Xing, Haohan Wang, Yifan Zhong, 2022, ArXiv.

Tree-guided group lasso for multi-response regression with structured sparsity, with an application to eQTL mapping

E. Xing, Seyoung Kim, 2009, 0909.1373.

Learning Sparse Nonparametric DAGs

E. Xing, Pradeep Ravikumar, Xun Zheng, 2019, AISTATS.

Toward Controllable Text Content Manipulation

Shuai Lin, Eric P. Xing, Zhiting Hu, 2019 .

GenAMap: Visualization strategies for structured association mapping

Eric P. Xing, Ross E. Curtis, Peter Kinnaird, 2011, 2011 IEEE Symposium on Biological Data Visualization (BioVis)..

Learning from Imperfect Annotations

Eric P. Xing, Maruan Al-Shedivat, Emmanouil Antonios Platanios, 2019, ArXiv.

Diffusion of Lexical Change in Social Media

Brendan T. O'Connor, Noah A. Smith, E. Xing, 2012, PloS one.

Prototypical Graph Contrastive Learning

E. Xing, Xiaodan Liang, Pan Zhou, 2021, IEEE Transactions on Neural Networks and Learning Systems.

Coupled mixed model for joint genetic analysis of complex disorders with two independently collected data sets

Eric P. Xing, Fen Pei, Wei Wu, 2018, bioRxiv.

RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning

Yihan Wang, E. Xing, Zhiting Hu, 2022, EMNLP.

Probabilistic Graphical Models-Theory, Algorithm, and Application

Eric P. Xing, E. Xing, 2007, Sixth International Conference on Machine Learning and Applications (ICMLA 2007).

This paper is included in the Proceedings of the 16th USENIX Symposium on Operating Systems Design and Implementation.

E. Xing, H. Zhang, Lianmin Zheng, 2022 .

Smooth Kernels Improve Adversarial Robustness and Perceptually-Aligned Gradients

Eric P. Xing, Zachary C. Lipton, Haohan Wang, 2019 .

Toward a 'Standard Model' of Machine Learning

E. Xing, Zhiting Hu, 2022, Harvard Data Science Review.

DNB: A Joint Learning Framework for Deep Bayesian Nonparametric Clustering

E. Xing, Zeya Wang, Baoyu Jing, 2021, IEEE Transactions on Neural Networks and Learning Systems.

Kernel Mixed Model for Transcriptome Association Study

E. Xing, Haohan Wang, Wei Wu, 2022, J. Comput. Biol..

Sparse Output Coding for Scalable Visual Recognition

E. Xing, Bin Zhao, 2016, International Journal of Computer Vision.

Toward a 'Standard Model' of Machine Learning

E. Xing, Zhiting Hu, 2021, Harvard Data Science Review.

Orpheus: Efficient Distributed Machine Learning via System and Algorithm Co-design

Yaoliang Yu, Pengtao Xie, Eric P. Xing, 2018, SoCC.

Nonoverlap-Promoting Variable Selection

Pengtao Xie, Eric P. Xing, Yichen Zhu, 2018, ICML.

Learning Latent Space Models with Angular Constraints

Yaoliang Yu, Yi Zhou, Pengtao Xie, 2017, ICML.

Near-Orthogonality Regularization in Kernel Methods

Pengtao Xie, Barnabás Póczos, Eric P. Xing, 2017, UAI.

Lighter-Communication Distributed Machine Learning via Sufficient Factor Broadcasting

Yaoliang Yu, Yi Zhou, Pengtao Xie, 2016, UAI.

Distributed Machine Learning via Sufficient Factor Broadcasting pdf

Yaoliang Yu, Yi Zhou, Pengtao Xie, 2015, ArXiv.

Reconstructing Storyline Graphs for Image Recommendation from Web Community Photos

Eric P. Xing, Gunhee Kim, E. Xing, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Towards Principled Disentanglement for Domain Generalization

E. Xing, B. Scholkopf, Adrian Weller, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Post-Inference Prior Swapping

Eric P. Xing, Willie Neiswanger, E. Xing, 2016, ICML.

Prior Swapping for Data-Independent Inference pdf

Eric P. Xing, Willie Neiswanger, E. Xing, 2016, ArXiv.

Easy Questions First? A Case Study on Curriculum Learning for Question Answering

Eric P. Xing, Mrinmaya Sachan, E. Xing, 2016, ACL.

Exploiting Genome Structure in Association Analysis

Eric P. Xing, Seyoung Kim, E. Xing, 2014, J. Comput. Biol..

Learning to Solve Geometry Problems from Natural Language Demonstrations in Textbooks

Eric P. Xing, Mrinmaya Sachan, E. Xing, 2017, *SEMEVAL.

AD3: alternating directions dual decomposition for MAP inference in graphical models

Eric P. Xing, Noah A. Smith, André F. T. Martins, 2015, J. Mach. Learn. Res..

Alternating Directions Dual Decomposition pdf

Eric P. Xing, Noah A. Smith, André F. T. Martins, 2012, ArXiv.

Predictive Subspace Learning for Multi-view Data: a Large Margin Approach

Ning Chen, Eric P. Xing, Jun Zhu, 2010, NIPS.

BayCis: A Bayesian Hierarchical HMM for Cis-Regulatory Module Decoding in Metazoan Genomes

Eric P. Xing, Geir Kjetil Sandve, Pradipta Ray, 2008, RECOMB.

Few-Shot Semantic Segmentation with Prototype Learning

Eric P. Xing, Nanqing Dong, E. Xing, 2018, BMVC.

State Space LSTM Models with Particle MCMC Inference pdf

Alexander J. Smola, Eric P. Xing, Xun Zheng, 2017, ArXiv.

Approximating Correlated Equilibria using Relaxations on the Marginal Polytope

Eric P. Xing, Christopher James Langmead, Hetunandan Kamisetty, 2011, ICML.

Structured probabilistic models of proteins across spatial and fitness landscapes

E. Xing, C. Langmead, Hetunandan Kamichetty, 2011 .

Learning Robust Global Representations by Penalizing Local Predictive Power

Eric P. Xing, Haohan Wang, Zachary C. Lipton, 2019, NeurIPS.

Bilingual Word Spectral Clustering for Statistical Machine Translation

Eric P. Xing, Alexander H. Waibel, Bing Zhao, 2005, ParallelText@ACL.

Structured Literature Image Finder: Extracting Information from Text and Images in Biomedical Literature

Eric P. Xing, William W. Cohen, Robert F. Murphy, 2009, BioLINK@ISMB/ECCB.

On Convergence of Model Parallel Proximal Gradient Algorithm for Stale Synchronous Parallel System

Yaoliang Yu, Yi Zhou, Yingbin Liang, 2016, AISTATS.

High-Performance Distributed ML at Scale through Parameter Server Consistency Models pdf

Eric P. Xing, Garth A. Gibson, Wei Dai, 2014, AAAI.

Model-Parallel Inference for Big Topic Models pdf

Eric P. Xing, Xun Zheng, Jin Kyu Kim, 2014, ArXiv.

Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data

Eric P. Xing, Qirong Ho, Alex Beutel, 2014, AISTATS.

Bayesian inference with posterior regularization and applications to infinite latent SVMs

Ning Chen, Eric P. Xing, Jun Zhu, 2012, J. Mach. Learn. Res..

Unified analysis of streaming news

Alexander J. Smola, Eric P. Xing, Choon Hui Teo, 2011, WWW.

Maximum Entropy Discrimination Markov Networks

Jun Zhu, Eric P. Xing, E. Xing, 2009, J. Mach. Learn. Res..

Mixed Membership Stochastic Blockmodels

Edoardo M. Airoldi, Eric P. Xing, Stephen E. Fienberg, 2007, NIPS.

Conditional topical coding: an efficient topic model conditioned on rich features

Ning Chen, Eric P. Xing, Ni Lao, 2011, KDD.

GeePS: scalable deep learning on distributed GPUs with a GPU-specialized parameter server

Eric P. Xing, Hao Zhang, Henggang Cui, 2016, EuroSys.

An Active Learning Approach to Coreference Resolution

Eric P. Xing, Mrinmaya Sachan, Eduard H. Hovy, 2015, IJCAI.

Fair Deep Learning Prediction for Healthcare Applications with Confounder Filtering pdf

Eric P. Xing, Haohan Wang, Yin Chen, 2018, ArXiv.

Dynamic mixed membership blockmodel for evolving networks

Le Song, Wenjie Fu, Eric P. Xing, 2009, ICML '09.

AutoSync: Learning to Synchronize for Data-Parallel Distributed Deep Learning

Hao Zhang, Eric P. Xing, Lawrence Carin, 2020, NeurIPS.

DISCOVER: a feature-based discriminative method for motif search in complex genomes

Wenjie Fu, Eric P. Xing, Pradipta Ray, 2009, Bioinform..

CSMET: Comparative Genomic Motif Detection via Multi-Resolution Phylogenetic Shadowing

Eric P. Xing, Mladen Kolar, Pradipta Ray, 2008, PLoS Comput. Biol..

Feature selection for high-dimensional genomic microarray data

Michael I. Jordan, Richard M. Karp, Eric P. Xing, 2001, ICML.

Multi-population GWA mapping via multi-task regularized regression

Eric P. Xing, Seyoung Kim, Kriti Puniyani, 2010, Bioinform..

Coupled mixed model for joint genetic analysis of complex disorders with two independently collected data sets

E. Xing, I. Bahar, Haohan Wang, 2018, BMC Bioinformatics.

Coupled Mixed Model for joint genetic analysis of complex disorders from independently collected data sets: application to Alzheimer's disease and substance use disorder

Eric P. Xing, Haohan Wang, Michael Vanyukov, 2018 .

ProBO: Versatile Bayesian Optimization Using Any Probabilistic Programming Language

Eric Xing, Kirthevasan Kandasamy, Willie Neiswanger, 2019 .

ProBO: a Framework for Using Probabilistic Programming in Bayesian Optimization pdf

Kirthevasan Kandasamy, Barnabás Póczos, Eric P. Xing, 2019, ArXiv.

Tradeoffs of Linear Mixed Models in Genome-wide Association Studies pdf

Eric Xing, Bryon Aragam, Haohan Wang, 2021, J. Comput. Biol..

Supervised Adversarial Alignment of Single-Cell RNA-seq Data

Eric P. Xing, Ziv Bar-Joseph, Amir Alavi, 2020, bioRxiv.

A time-varying group sparse additive model for genome-wide association studies of dynamic complex traits

Eric P. Xing, Micol Marchetti-Bowick, Junming Yin, 2016, Bioinform..

Gene expression profiling of asthma phenotypes demonstrates molecular signatures of atopy and asthma control.

E. Xing, Wei Wu, B. Raby, 2016, The Journal of allergy and clinical immunology.

Kernel methods for large-scale genomic data analysis

Eric P. Xing, Xuefeng Wang, Daniel J. Schaid, 2015, Briefings Bioinform..

Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly

Kirthevasan Kandasamy, Barnabás Póczos, Eric P. Xing, 2019, J. Mach. Learn. Res..

NOTMAD: Estimating Bayesian Networks with Sample-Specific Structures and Parameters pdf

Eric P. Xing, Manolis Kellis, Bryon Aragam, 2021, ArXiv.

Hybrid Subspace Learning for High-Dimensional Data pdf

Eric P. Xing, Ankur P. Parikh, Benjamin J. Lengerich, 2018, ArXiv.

Learning Sample-Specific Models with Low-Rank Personalized Regression

Eric P. Xing, Bryon Aragam, Benjamin J. Lengerich, 2019, NeurIPS.

GIMscan: A New Statistical Method for Analyzing Whole-Genome Array CGH Data

Wei Wu, Fan Guo, Eric P. Xing, 2007, RECOMB.

Structured correspondence topic models for mining captioned figures in biological literature

Eric P. Xing, William W. Cohen, Robert F. Murphy, 2009, KDD.

Precision Lasso: accounting for correlations and linear dependencies in high-dimensional genomic data

Eric P. Xing, Bryon Aragam, Haohan Wang, 2018, Bioinform..

Self-Training for Jointly Learning to Ask and Answer Questions

Eric P. Xing, Mrinmaya Sachan, E. Xing, 2018, NAACL.

Semi-Supervised Learning Based on Semiparametric Regularization

Christos Faloutsos, Zhen Guo, Eric P. Xing, 2008, SDM.

Sample-Efficient Deep Learning for COVID-19 Diagnosis Based on CT Scans

X. He, X. Yang, S. Zhang, 2020, medRxiv.

Predicting Discharge Medications at Admission Time Based on Deep Learning pdf

Pengtao Xie, Eric P. Xing, Xin Gao, 2017, ArXiv.

Connecting the Dots Between MLE and RL for Sequence Generation pdf

Eric P. Xing, Zhiting Hu, Ruslan Salakhutdinov, 2018, DeepRLStructPred@ICLR.

Connecting the Dots Between MLE and RL for Sequence Prediction

Eric Xing, Zhiting Hu, Ruslan Salakhutdinov, 2019 .

Deep learning-based subdivision approach for large scale macromolecules structure recovery from electron cryo tomograms

Eric P. Xing, Min Xu, Xiaodan Liang, 2017, Bioinform..

Population Stratification with Mixed Membership Models

Eric P. Xing, Suyash Shringarpure, E. Xing, 2014, Handbook of Mixed Membership Models and Their Applications.

Genetic Population Structure in Pacific Islanders

E. Xing, S. Shringarpure, 2010 .

Comparison of normalization methods for CodeLink Bioarray data

Wei Wu, Eric P. Xing, Naftali Kaminski, 2005, BMC Bioinformatics.

Neural Architecture Search with Bayesian Optimisation and Optimal Transport pdf

Kirthevasan Kandasamy, Barnabás Póczos, Eric P. Xing, 2018, NeurIPS.

Discriminative Subtyping of Lung Cancers from Histopathology Images via Contextual Deep Learning

Benjamin J. Lengerich, E. P. Xing, B. J. Lengerich, 2020, medRxiv.

Deep mixed model for marginal epistasis detection and population stratification correction in genome-wide association studies

Eric P. Xing, Wei Wu, Haohan Wang, 2019, BMC Bioinformatics.

Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models

Eric P. Xing, Avinava Dubey, Sinead Williamson, 2013, ICML.

Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices

Kirthevasan Kandasamy, Eric P. Xing, Maruan Al-Shedivat, 2016, NIPS.

Enabling dynamic network analysis through visualization in TVNViewer

Eric P. Xing, Ankur P. Parikh, Ross E. Curtis, 2012, BMC Bioinformatics.

Poly(A)-DG: A deep-learning-based domain generalization method to identify cross-species Poly(A) signal without prior knowledge from target species

Xin Gao, Haohan Wang, Eric P Xing, 2020, PLoS Comput. Biol..

Learning Pipelines with Limited Data and Domain Knowledge: A Study in Parsing Physics Problems

Tom M. Mitchell, Eric P. Xing, Dan Roth, 2018, NeurIPS.

Automatic discovery of sub-molecular sequence domains in multi-aligned sequences: a dynamic programming algorithm for multiple alignment segmentation.

C Kulikowski, E P Xing, D M Wolf, 2000, Journal of theoretical biology.

Active Learning to Classify Macromolecular Structures in situ for Less Supervision in Cryo-Electron Tomography

Eric P. Xing, Xiangrui Zeng, Haohan Wang, 2021, Bioinform..

Efficient Exploration via State Marginal Matching pdf

Sergey Levine, Eric Xing, Ruslan Salakhutdinov, 2019, ArXiv.

Inference of multiple-wave population admixture by modeling decay of linkage disequilibrium with multiple exponential functions

E. Xing, Yaoliang Yu, P. Xie, 2015, bioRxiv.

Fast Function to Function Regression pdf

Barnabás Póczos, Eric P. Xing, Jeff G. Schneider, 2014, AISTATS.

Collective Support Recovery for Multi-Design Multi-Response Linear Regression

Yingbin Liang, Eric P. Xing, Weiguang Wang, 2015, IEEE Transactions on Information Theory.

High-Dimensional Feature Selection by Feature-Wise Kernelized Lasso

Masashi Sugiyama, Eric P. Xing, Makoto Yamada, 2012, Neural Computation.

Restricting exchangeable nonparametric distributions

Eric P. Xing, Sinead Williamson, Steve N. MacEachern, 2012, NIPS.

Semantic Pooling for Complex Event Analysis in Untrimmed Videos

Yi Yang, Yaoliang Yu, Eric P. Xing, 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Self-Challenging Improves Cross-Domain Generalization pdf

Eric P. Xing, Zeyi Huang, Dong Huang, 2020, ECCV.

Technology readiness levels for machine learning systems

E. Xing, Y. Gal, A. G. Baydin, 2020, Nature Communications.

Sparse Word Graphs: A Scalable Algorithm for Capturing Word Correlations in Topic Models

William W. Cohen, E. Xing, Amr Ahmed, 2007, Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007).

Effective Use of Bidirectional Language Modeling for Transfer Learning in Biomedical Named Entity Recognition

Pengtao Xie, Eric P. Xing, Mrinmaya Sachan, 2017, MLHC.

Target-Guided Open-Domain Conversation

Eric P. Xing, Zhiting Hu, Xiaodan Liang, 2019, ACL.

A Neural Architecture for Automated ICD Coding pdf

Pengtao Xie, Eric P. Xing, Zhiting Hu, 2017, ACL.

Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation

Eric P. Xing, Zhiting Hu, Di Wang, 2019, ACL.

Large-Margin Predictive Latent Subspace Learning for Multiview Data Analysis

Fuchun Sun, Ning Chen, Eric P. Xing, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Improving GAN Training with Probability Ratio Clipping and Sample Reweighting

E. Xing, Zhiting Hu, Pan Zhou, 2020, NeurIPS.

On Unifying Deep Generative Models pdf

Eric P. Xing, Zhiting Hu, Ruslan Salakhutdinov, 2017, ICLR.

Text Generation with Efficient (Soft) Q-Learning

E. Xing, Zhiting Hu, Han Guo, 2021, ArXiv.

DAGs with NO TEARS: Continuous Optimization for Structure Learning

Pradeep Ravikumar, Eric P. Xing, Xun Zheng, 2018, NeurIPS.

A Joint Topic and Perspective Model for Ideological Discourse

Wei-Hao Lin, Eric P. Xing, Alexander G. Hauptmann, 2008, ECML/PKDD.

Automatic Human-like Mining and Constructing Reliable Genetic Association Database with Deep Reinforcement Learning

Eric P. Xing, William W. Cohen, Qiao Jin, 2018, bioRxiv.

Semantic-aware Grad-GAN for Virtual-to-Real Urban Scene Adaption pdf

Eric P. Xing, Xiaodan Liang, Peilun Li, 2018, BMVC.

Symbolic Graph Reasoning Meets Convolutions

Eric P. Xing, Zhiting Hu, Liang Lin, 2018, NeurIPS.

Time-Varying Dynamic Bayesian Networks

Le Song, Eric P. Xing, Mladen Kolar, 2009, NIPS.

Identifiability of Nonparametric Mixture Models and Bayes Optimal Clustering pdf

Pradeep Ravikumar, Eric P. Xing, Chen Dan, 2018, The Annals of Statistics.

Augmenting Dual Decomposition for MAP Inference

Eric P. Xing, Noah A. Smith, André F. T. Martins, 2010 .

Diversity-Promoting Bayesian Learning of Latent Variable Models pdf

Pengtao Xie, Eric P. Xing, Jun Zhu, 2016, ICML.

Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation pdf

Eric P. Xing, Zhiting Hu, Bowen Tan, 2021, EMNLP.

Progressive Generation of Long Text with Pretrained Language Models

Eric Xing, Zhiting Hu, Maruan Al-Shedivat, 2021, NAACL.

DTR-GAN: dilated temporal relational adversarial network for video summarization

Michael Kampffmeyer, Eric P. Xing, Xiaodan Liang, 2018, ACM TUR-C.

Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling pdf

Eric Xing, Willie Neiswanger, Artur Dubrawski, 2020, ICLR.

Modeling Citation Networks Using Latent Random Offsets

Chong Wang, Eric P. Xing, Willie Neiswanger, 2014, UAI.

On the Generation of Medical Dialogues for COVID-19

E. Xing, P. Xie, Zhou Yu, 2020, medRxiv.

Dynamic Topic Modeling for Monitoring Market Competition from Online Text and Image Data

Eric P. Xing, Hao Zhang, Gunhee Kim, 2015, KDD.

Multimodal Machine Learning for Automated ICD Coding pdf

Pengtao Xie, Eric P. Xing, Xin Gao, 2018, MLHC.

On Data Efficiency of Meta-learning

Ameet Talwalkar, Eric Xing, Maruan Al-Shedivat, 2021, AISTATS.

Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms

E. Xing, Afshin Rostamizadeh, Jennifer Gillenwater, 2020, ICLR.

Infinite Latent SVM for Classification and Multi-task Learning

Ning Chen, Eric P. Xing, Jun Zhu, 2011, NIPS.

Heterogeneous multitask learning with joint sparsity constraints

Eric P. Xing, Xiaolin Yang, Seyoung Kim, 2009, NIPS.

On the Automatic Generation of Medical Imaging Reports

Pengtao Xie, Eric P. Xing, Baoyu Jing, 2017, ACL.

Toward Understanding the Impact of Staleness in Distributed Machine Learning pdf

Yi Zhou, Eric P. Xing, Hao Zhang, 2018, ICLR.

Discovering Sociolinguistic Associations with Structured Sparsity

Eric P. Xing, Noah A. Smith, Jacob Eisenstein, 2011, ACL.

Unsupervised Object-Level Video Summarization with Online Motion Auto-Encoder

Eric P. Xing, Min Tan, Xiaodan Liang, 2018, Pattern Recognit. Lett..

ConnNet: A Long-Range Relation-Aware Pixel-Connectivity Network for Salient Segmentation

Michael Kampffmeyer, Eric P. Xing, Xiaodan Liang, 2018, IEEE Transactions on Image Processing.

Gated Path Planning Networks

Eric P. Xing, Ruslan Salakhutdinov, Emilio Parisotto, 2018, ICML.

Real-to-Virtual Domain Unification for End-to-End Autonomous Driving

Eric P. Xing, Xiaodan Liang, Luona Yang, 2018, ECCV.

Knowledge-driven Encode, Retrieve, Paraphrase for Medical Image Report Generation pdf

Eric P. Xing, Zhiting Hu, Xiaodan Liang, 2019, AAAI.

Dual Motion GAN for Future-Flow Embedded Video Prediction

Eric P. Xing, Xiaodan Liang, Wei Dai, 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

Recurrent Topic-Transition GAN for Visual Paragraph Generation

Chuang Gan, Eric P. Xing, Zhiting Hu, 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

On Dropout, Overfitting, and Interaction Effects in Deep Neural Networks pdf

Eric P. Xing, Rich Caruana, Benjamin J. Lengerich, 2020, ArXiv.

Explaining a black-box using Deep Variational Information Bottleneck Approach pdf

Wei Wu, Pengtao Xie, Eric P. Xing, 2019, ArXiv.

Dropout as a Regularizer of Interaction Effects

Benjamin J. Lengerich, E. Xing, R. Caruana, 2020, AISTATS.

Dynamic-Structured Semantic Propagation Network

Eric P. Xing, Xiaodan Liang, Hongfei Zhou, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

StyleRF: Zero-Shot 3D Style Transfer of Neural Radiance Fields

E. Xing, Abdulmotaleb El Saddik, Shijian Lu, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Semantic-Aligned Matching for Enhanced DETR Convergence and Multi-Scale Feature Fusion

E. Xing, Shijian Lu, Zhipeng Luo, 2022, International Journal of Computer Vision.

Rethinking Knowledge Graph Propagation for Zero-Shot Learning

Hao Wang, Michael Kampffmeyer, Eric P. Xing, 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Show, Describe and Conclude: On Exploiting the Structure Information of Chest X-ray Reports

Eric P. Xing, Baoyu Jing, Zeya Wang, 2019, ACL.

Query-Conditioned Three-Player Adversarial Network for Video Summarization pdf

Michael Kampffmeyer, Eric P. Xing, Min Tan, 2018, BMVC.

From Textbooks to Knowledge: A Case Study in Harvesting Axiomatic Knowledge from Textbooks to Solve Geometry Problems

Eric P. Xing, Mrinmaya Sachan, Avinava Dubey, 2017, EMNLP.

GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning pdf

Eric P. Xing, Liang Lin, Jinghui Qin, 2021, FINDINGS.

On the Generation of Medical Dialogs for COVID-19

Pengtao Xie, Eric P. Xing, Zhou Yu, 2021, ACL.

Unsupervised Text Style Transfer using Language Models as Discriminators

Eric P. Xing, Zhiting Hu, Chris Dyer, 2018, NeurIPS.

Pathological Visual Question Answering pdf

Eric Xing, Pengtao Xie, Luntian Mou, 2020, ArXiv.

PathVQA: 30000+ Questions for Medical Visual Question Answering pdf

Eric Xing, Pengtao Xie, Luntian Mou, 2020, ArXiv.

Domain Adaption in One-Shot Learning

Eric P. Xing, Nanqing Dong, E. Xing, 2018, ECML/PKDD.

Towards Robust Medical Image Segmentation on Small-Scale Data with Incomplete Labels pdf

Irina Voiculescu, Michael Kampffmeyer, Eric P. Xing, 2020, ArXiv.

Jointly Aligning and Segmenting Multiple Web Photo Streams for the Inference of Collective Photo Storylines

Eric P. Xing, Gunhee Kim, E. Xing, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

Discovering Demographic Language Variation

Brendan T. O'Connor, Eric P. Xing, Noah A. Smith, 2010 .

The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models

Pradeep Ravikumar, Eric P. Xing, Chen Dan, 2018, NeurIPS.

Select-additive learning: Improving generalization in multimodal sentiment analysis

Eric P. Xing, Louis-Philippe Morency, Haohan Wang, 2016, 2017 IEEE International Conference on Multimedia and Expo (ICME).

Graph estimation from multi-attribute data

Eric P. Xing, Mladen Kolar, Han Liu, 2012, J. Mach. Learn. Res..

Towards Principled Disentanglement for Domain Generalization

E. Xing, B. Schölkopf, Adrian Weller, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Differential Principal Components Reveal Patterns of Differentiation in Case/Control Studies

Eric P. Xing, Benjamin J. Lengerich, E. Xing, 2019, bioRxiv.

Select-Additive Learning: Improving Cross-individual Generalization in Multimodal Sentiment Analysis pdf

Eric P. Xing, Louis-Philippe Morency, Haohan Wang, 2016, ArXiv.

Geometric Generalization Based Zero-Shot Learning Dataset Infinite World: Simple Yet Powerful pdf

Michael Kampffmeyer, Eric P. Xing, Xiaodan Liang, 2018, ArXiv.

Fault Tolerance in Iterative-Convergent Machine Learning pdf

Eric P. Xing, Bryon Aragam, Bingjing Zhang, 2018, ICML.

Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning pdf

Eric P. Xing, Gregory R. Ganger, Willie Neiswanger, 2020, OSDI.

Graph-Structured Multi-task Regression and an Efficient Optimization Method for General Fused Lasso pdf

Xi Chen, Jaime G. Carbonell, Eric P. Xing, 2010, ArXiv.

Sparsistent Estimation of Time-Varying Discrete Markov Random Fields

Eric P. Xing, Mladen Kolar, E. Xing, 2009, 0907.2337.

Diffusion of Lexical Change in Social Media pdf

Brendan T. O'Connor, Eric P. Xing, Noah A. Smith, 2012, PloS one.

Generative Semantic Manipulation with Mask-Contrasting GAN

Eric P. Xing, Liang Lin, Hao Zhang, 2018, ECCV.

Probabilistic Graphical Models-Theory, Algorithm, and Application

Eric P. Xing, E. Xing, 2007, International Conference on Machine Learning and Applications.

Socioscape: Real-Time Analysis of Dynamic Heterogeneous Networks In Complex Socio-Cultural Systems

Eric P Xing, E. Xing, 2015 .

Stackelberg GAN: Towards Provable Minimax Equilibrium via Multi-Generator Architectures pdf

Pengtao Xie, Eric P. Xing, Ruslan Salakhutdinov, 2018, ArXiv.

Learning from Imperfect Annotations pdf

Eric Xing, Tom Mitchell, Maruan Al-Shedivat, 2020, ArXiv.

Judging LLM-as-a-judge with MT-Bench and Chatbot Arena

Joseph E. Gonzalez, E. Xing, Lianmin Zheng, 2023, 2306.05685.

Joint latent topic models for text and citations

Ramesh Nallapati, Eric P. Xing, William W. Cohen, 2008, KDD.

Distributed Training of Deep Neural Networks with Theoretical Analysis: Under SSP Setting pdf

Pengtao Xie, Eric P. Xing, Junming Yin, 2015, ArXiv.

Spectral Unsupervised Parsing with Additive Tree Metrics

Eric P. Xing, Shay B. Cohen, Ankur P. Parikh, 2014, ACL.

A Latent Variable Model for Geographic Lexical Variation

Brendan T. O'Connor, Eric P. Xing, Noah A. Smith, 2010, EMNLP.

Group Sparse Additive Models

Xi Chen, Eric P. Xing, Junming Yin, 2012, ICML.

MedLDA: maximum margin supervised topic models

Eric P. Xing, Jun Zhu, Amr Ahmed, 2012, J. Mach. Learn. Res..

A Nonparametric Mixture Model for Topic Modeling over Time

Eric P. Xing, Avinava Dubey, Ahmed Hefny, 2012, SDM.

Timeline: A Dynamic Hierarchical Dirichlet Process Model for Recovering Birth/Death and Evolution of Topics in Text Stream

Eric P. Xing, Amr Ahmed, E. Xing, 2010, UAI.

Ying Huang, Eric P. Xing, Zhiting Hu, 2017, KDD.

CLIFF: clustering of high-dimensional microarray data via iterative feature filtering using normalized cuts

Richard M. Karp, Eric P. Xing, E. Xing, 2001, ISMB.

MotifPrototyper: A Bayesian profile model for motif families

Eric P Xing, Richard M Karp, E. Xing, 2004, Proc. Natl. Acad. Sci. USA.

Estimating networks with jumps.

Mladen Kolar, Eric P Xing, E. Xing, 2010, Electronic journal of statistics.

Web Semantics: Science, Services and Agents on the World Wide Web

Eric P. Xing, William W. Cohen, Robert F. Murphy, 2010 .

Complex Event Detection using Semantic Saliency and Nearly-Isotonic SVM

Yi Yang, Yaoliang Yu, Eric P. Xing, 2015, ICML.

Machine Comprehension using Rich Semantic Representations

Eric P. Xing, Mrinmaya Sachan, E. Xing, 2016, ACL.

TopicScape: Semantic Navigation of Document Collections pdf

Aniket Kittur, Eric P. Xing, Jacob Eisenstein, 2011, ArXiv.

TopicViz: Semantic Navigation of Document Collections

Aniket Kittur, Eric P. Xing, Jacob Eisenstein, 2011, 1110.6200.

Trade-offs of Linear Mixed Models in Genome-Wide Association Studies

E. Xing, Haohan Wang, Bryon Aragam, 2022, J. Comput. Biol..

Adversarial Connective-exploiting Networks for Implicit Discourse Relation Classification

Hai Zhao, Eric P. Xing, Zhiting Hu, 2017, ACL.

Nonparametric Variational Auto-Encoders for Hierarchical Representation Learning

Eric P. Xing, Zhiting Hu, Prasoon Goyal, 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

What If We Simply Swap the Two Text Fragments? A Straightforward yet Effective Way to Test the Robustness of Methods to Confounding Signals in Nature Language Inference Tasks pdf

Eric P. Xing, Haohan Wang, Da Sun, 2018, AAAI.

Feature selection for grasp recognition from optical markers

Tom M. Mitchell, Eric P. Xing, Nancy S. Pollard, 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

The Dependent Dirichlet Process Mixture of Objects for Detection-free Tracking and Object Modeling

Eric P. Xing, Frank D. Wood, Willie Neiswanger, 2014, AISTATS.

Mixed membership analysis of genome-wide expression data

Eric P Xing, Edoardo M Airoldi, Stephen E Fienberg, 2007, 0711.2520.

Distributed Proximal Gradient Algorithm for Partially Asynchronous Computer Clusters

Yaoliang Yu, Yi Zhou, Yingbin Liang, 2017, J. Mach. Learn. Res..

A Data-Centric Framework for Composable NLP Workflows

Eric Xing, Zhiting Hu, Wei Wei, 2020, EMNLP.

Concise Integer Linear Programming Formulations for Dependency Parsing

Eric P. Xing, Noah A. Smith, André F. T. Martins, 2009, ACL.

Iterative Graph Self-Distillation

E. Xing, Xiaodan Liang, Pan Zhou, 2020, IEEE Transactions on Knowledge and Data Engineering.

Generalized Zero-Shot Text Classification for ICD Coding

Pengtao Xie, Eric P. Xing, Congzheng Song, 2020, IJCAI.

From Lasso regression to Feature vector machine

Yiming Yang, Fan Li, Eric P. Xing, 2005, NIPS.

Hierarchical Tensor Decomposition of Latent Tree Graphical Models

Le Song, Eric P. Xing, Haesun Park, 2013, ICML.

Distributed cosegmentation via submodular optimization on anisotropic diffusion

Takeo Kanade, Fei-Fei Li, Eric P. Xing, 2011, 2011 International Conference on Computer Vision.

BertNet: Harvesting Knowledge Graphs with Arbitrary Relations from Pretrained Language Models

E. Xing, Zhiting Hu, Bowen Tan, 2022, ACL.

Nonextensive Information Theoretic Kernels on Measures

Eric P. Xing, Noah A. Smith, André F. T. Martins, 2009, J. Mach. Learn. Res..

FlexiFaCT: Scalable Flexible Factorization of Coupled Tensors on Hadoop

Christos Faloutsos, Eric P. Xing, Partha Pratim Talukdar, 2014, SDM.

Deep Determinantal Point Process for Large-Scale Multi-label Classification

Pengtao Xie, Eric P. Xing, Luntian Mou, 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

Generative Semantic Manipulation with Contrasting GAN pdf

Eric P. Xing, Hao Zhang, Xiaodan Liang, 2017, ArXiv.

Summarizing Text on Any Aspects: A Knowledge-Informed Weakly-Supervised Approach pdf

Eric P. Xing, Zhiting Hu, Lianhui Qin, 2020, EMNLP.

Deep Neural Networks with Massive Learned Knowledge

Eric P. Xing, Zhiting Hu, Ruslan Salakhutdinov, 2016, EMNLP.

Judging LLM-as-a-judge with MT-Bench and Chatbot Arena

E. Xing, Joseph Gonzalez, Lianmin Zheng, 2023, ArXiv.

A Constituent-Centric Neural Architecture for Reading Comprehension

Pengtao Xie, Eric P. Xing, E. Xing, 2017, ACL.

Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis pdf

Wei Wu, Pengtao Xie, Eric P. Xing, 2018, ICML.

Randomization or Condensation?: Linear-Cost Matrix Sketching Via Cascaded Compression Sampling

Hui Xiong, Jie Zhang, Jieping Ye, 2017, KDD.

Structure-Aware Dynamic Scheduler for Parallel Machine Learning pdf

Seunghak Lee, Eric P. Xing, Garth A. Gibson, 2013, ArXiv.

Word Shape Matters: Robust Machine Translation with Visual Embedding pdf

Eric P. Xing, Haohan Wang, Peiyan Zhang, 2020, ArXiv.

Toward Unsupervised Text Content Manipulation pdf

Eric P. Xing, Zhiting Hu, Haoran Shi, 2019, ArXiv.

Training Larger Models on TensorFlow without Additional GPU

Garth A. Gibson, E. Xing, Jinliang Wei, 2019 .

Sparsistent Learning of Varying-coefficient Models with Structural Changes

Le Song, Eric P. Xing, Mladen Kolar, 2009, NIPS.

Ellipse Detection of Optic Disc-and-Cup Boundary in Fundus Images

Eric P. Xing, Zeya Wang, Min Xu, 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

Text Infilling pdf

Eric P. Xing, Zhiting Hu, Wanrong Zhu, 2019, ArXiv.

Cooperative Multi-Agent Actor-Critic for Privacy-Preserving Load Scheduling in a Residential Microgrid pdf

Eric P. Xing, Nanqing Dong, Zhaoming Qin, 2021, ArXiv.

GWAS in a Box: Statistical and Visual Analytics of Structured Associations via GenAMap

Wei Wu, Seunghak Lee, Eric P. Xing, 2014, PloS one.

Discriminative Training of Mixed Membership Models

Eric P. Xing, Jun Zhu, E. Xing, 2014, Handbook of Mixed Membership Models and Their Applications.

Structured association analysis leads to insight into Saccharomyces cerevisiae gene regulation by finding multiple contributing eQTL hotspots associated with functional gene modules

Ross E. Curtis, E. Xing, Seyoung Kim, 2013, BMC Genomics.

Efficient Multiple Instance Metric Learning Using Weakly Supervised Data

Yaoliang Yu, Eric P. Xing, Raquel Urtasun, 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

DiCE: The Infinitely Differentiable Monte-Carlo Estimator pdf

Shimon Whiteson, Eric P. Xing, Jakob N. Foerster, 2018, ICML.

Cavs: An Efficient Runtime System for Dynamic Neural Networks

E. Xing, Qirong Ho, Jin Kyu Kim, 2018, USENIX Annual Technical Conference.

Towards robust partially supervised multi-structure medical image segmentation on small-scale data

Irina Voiculescu, Michael Kampffmeyer, Eric P. Xing, 2020, Appl. Soft Comput..

Effective Use of Bidirectional Language Modeling for Medical Named Entity Recognition pdf

Pengtao Xie, Eric P. Xing, Devendra Singh Sachan, 2017, ArXiv.

Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation pdf

Eric P. Xing, Zhiting Hu, Haoran Shi, 2018, ACL.

Texar: A Modularized, Versatile, and Extensible Toolbox for Text Generation

Devendra Singh Sachan, E. Xing, Xiaodan Liang, 2018 .

Transformation Autoregressive Networks

Barnabás Póczos, Eric P. Xing, Ruslan Salakhutdinov, 2018, ICML.

Recurrent Estimation of Distributions pdf

Barnabás Póczos, Eric P. Xing, Jeff G. Schneider, 2017, ArXiv.

Language Modeling with Power Low Rank Ensembles

Eric P. Xing, Chris Dyer, Ankur P. Parikh, 2013, EMNLP.

TVNViewer: An interactive visualization tool for exploring networks that change over time or space

Le Song, Eric P. Xing, Ross E. Curtis, 2011, Bioinform..

Deep Generative Models with Learnable Knowledge Constraints

R. Salakhutdinov, E. Xing, Xiaodan Liang, 2018, NeurIPS.

On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks

Eric P. Xing, Qirong Ho, Junming Yin, 2012, NIPS.

Latent Space Inference of Internet-Scale Networks

Eric P. Xing, Qirong Ho, Junming Yin, 2016, J. Mach. Learn. Res..

Evaluation of normalization methods for cDNA microarray data by k-NN classification

E. Xing, I. Mian, Wei Wu, 2005, BMC Bioinform..

Stackelberg GAN: Towards Provable Minimax Equilibrium via Multi-Generator Architectures

R. Salakhutdinov, E. Xing, P. Xie, 2018, ArXiv.

Exploiting iterative-ness for parallel ML computations

Eric P. Xing, Wei Dai, Henggang Cui, 2014, SoCC.

Identification of Nonlinear Latent Hierarchical Models

E. Xing, Yuejie Chi, Biwei Huang, 2023, ArXiv.

Understanding Masked Autoencoders via Hierarchical Latent Variable Models

Martin Q. Ma, E. Xing, Yuejie Chi, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Closed-Form Training of Mahalanobis Distance for Supervised Clustering

Matthieu Cord, Yaoliang Yu, Eric P. Xing, 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Online Learning of Structured Predictors with Multiple Kernels

Eric P. Xing, Noah A. Smith, André F. T. Martins, 2011, AISTATS.

Online Multiple Kernel Learning for Structured Prediction

Eric P. Xing, Noah A. Smith, André F. T. Martins, 2010, 1010.2770.

MLSys: The New Frontier of Machine Learning Systems

Christopher De Sa, Michael I. Jordan, Phillip B. Gibbons, 2019, 1904.03257.

SysML: The New Frontier of Machine Learning Systems

Christopher De Sa, Michael I. Jordan, Phillip B. Gibbons, 2019, ArXiv.

Multi-task Learning of Order-Consistent Causal Graphs pdf

Le Song, Eric Xing, Xinshi Chen, 2021, NeurIPS.

Sharp Threshold for Multivariate Multi-Response Linear Regression via Block Regularized Lasso pdf

Yingbin Liang, Eric P. Xing, Weiguang Wang, 2013, ArXiv.

Block Regularized Lasso for Multivariate Multi-Response Linear Regression

Yingbin Liang, Eric P. Xing, Weiguang Wang, 2013, AISTATS.

AutoLoss: Learning Discrete Schedules for Alternate Optimization pdf

Eric P. Xing, Zhiting Hu, Ruslan Salakhutdinov, 2018, ICLR 2018.

Progressive Generation of Long Text pdf

Eric P. Xing, Zhiting Hu, Maruan Al-Shedivat, 2020, ArXiv.

Dilated temporal relational adversarial network for generic video summarization

Michael Kampffmeyer, Eric P. Xing, Xiaodan Liang, 2018, Multimedia Tools and Applications.

On the Complexity of Exploration in Goal-Driven Navigation pdf

Eric P. Xing, Ruslan Salakhutdinov, Maruan Al-Shedivat, 2018, ArXiv.

Joint Summarization of Large-Scale Collections of Web Images and Videos for Storyline Reconstruction

Eric P. Xing, Gunhee Kim, Leonid Sigal, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Community Specific Temporal Topic Discovery from Social Media pdf

Junjie Yao, Chong Wang, Eric P. Xing, 2013, ArXiv.

Scalable Dynamic Nonparametric Bayesian Models of Content and Users

Eric P. Xing, Amr Ahmed, E. Xing, 2013, IJCAI.

Modeling and Analysis of Dynamic Behaviors of Web Image Collections

Eric P. Xing, Antonio Torralba, Gunhee Kim, 2010, ECCV.

Dependent nonparametric trees for dynamic hierarchical clustering : Supplementary material

E. Xing, Qirong Ho, Kumar Avinava Dubey, 2014 .

Collapsed Variational Inference for Time-varying Dirichlet Process Mixture Models

E. Xing, Amr Ahmed, 2009 .

NP-MuScL: Unsupervised Global Prediction of Interaction Networks from Multiple Data Sources

Eric P. Xing, Kriti Puniyani, E. Xing, 2013, RECOMB.

Genome-Phenome Association Analysis of Complex Diseases a Structured Sparse Regression Approach - (Keynote Talk)

Eric P. Xing, E. Xing, 2011, ISBRA.

Convolutional Neural Networks for Medical Diagnosis from Admission Notes pdf

Pengtao Xie, Eric P. Xing, Graham Neubig, 2017, ArXiv.

Enhancing the usability and performance of structured association mapping algorithms using automation, parallelization, and visualization in the GenAMap software system

Ross E. Curtis, E. Xing, Anuj Goyal, 2012, BMC Genetics.

On Sparse Nonparametric Conditional Covariance Selection

Eric P. Xing, Mladen Kolar, Ankur P. Parikh, 2010, ICML.

Variable Selection in Heterogeneous Datasets: A Truncated-rank Sparse Linear Mixed Model with Applications to Genome-wide Association Studies

Eric P. Xing, Bryon Aragam, Haohan Wang, 2017, bioRxiv.

2018 Formatting Instructions for Authors Using LaTeX

E. Xing, Haohan Wang, Xiang Liu, 2017 .

Variable selection in heterogeneous datasets: A truncated-rank sparse linear mixed model with applications to genome-wide association studies

Eric P. Xing, Bryon Aragam, Haohan Wang, 2017, BIBM.

A Sparse Graph-Structured Lasso Mixed Model for Genetic Association with Confounding Correction pdf

Eric P. Xing, Xiang Liu, Haohan Wang, 2017, ArXiv.

Hierarchical Feature Hashing for Fast Dimensionality Reduction

Bin Zhao, Eric P. Xing, E. Xing, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Multi-Level Structured Image Coding on High-Dimensional Image Representation

Hao Su, Fei-Fei Li, Eric P. Xing, 2012, ACCV.

Community Level Diffusion Extraction

Junjie Yao, Eric P. Xing, Zhiting Hu, 2015, SIGMOD Conference.

Regularizing Black-box Models for Improved Interpretability pdf

Ameet Talwalkar, Eric P. Xing, Maruan Al-Shedivat, 2019, NeurIPS.

StructHDP: automatic inference of number of clusters and population structure from admixed genotype data

Eric P. Xing, Daegun Won, Suyash Shringarpure, 2011, Bioinform..

Information Theory

Eric P. Xing, Scribes Fan Guo, E. Xing, 2019, Nature.

Incorporating Word Correlation Knowledge into Topic Modeling

Diyi Yang, Pengtao Xie, Eric P. Xing, 2015, NAACL.

Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks

Tom M. Mitchell, Eric P. Xing, Dan Roth, 2020, Computational Linguistics.

Discourse in Multimedia: A Case Study in Information Extraction pdf

Tom M. Mitchell, Eric P. Xing, Dan Roth, 2018, ArXiv.

Turbo Parsers: Dependency Parsing by Approximate Variational Inference

Eric P. Xing, Noah A. Smith, André F. T. Martins, 2010, EMNLP.

Network Completion and Survey Sampling

Eric P. Xing, Steve Hanneke, E. Xing, 2009, AISTATS.

Combining Stochastic Block Models and Mixed Membership for Statistical Network Analysis

Edoardo M. Airoldi, Eric P. Xing, Stephen E. Fienberg, 2006, SNA@ICML.

Inferring Gene Interaction Networks from ISH Images via Kernelized Graphical Models

Eric P. Xing, Kriti Puniyani, E. Xing, 2012, ECCV.

Personalized regression enables sample-specific pan-cancer analysis

Eric P. Xing, Bryon Aragam, Benjamin J. Lengerich, 2018, bioRxiv.

Diversifying Restricted Boltzmann Machine for Document Modeling

Pengtao Xie, Eric P. Xing, Yuntian Deng, 2015, KDD.

Nonextensive entropic kernels

Eric P. Xing, Noah A. Smith, André F. T. Martins, 2008, ICML '08.

They are Not Equally Reliable: Semantic Event Search Using Differentiated Concept Classifiers

Yi Yang, Yaoliang Yu, Eric P. Xing, 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Nonparametric decision making based on tree-structured information aggregation

Yingbin Liang, Eric P. Xing, Jiayao Hu, 2011, 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

KELLER: estimating time-varying interactions between genes

Le Song, Eric P. Xing, Mladen Kolar, 2009, Bioinform..

Time-Varying Networks: Recovering Temporally Rewiring Genetic Networks During the Life Cycle of Drosophila melanogaster

Eric P. Xing, Amr Ahmed, Le Song, 2008, 0901.0138.

Multi-modal Self-supervised Pre-training for Regulatory Genome Across Cell Types pdf

Yanyan Lan, Eric P Xing, Yuxuan Zheng, 2021, ArXiv.

Bayesian multi-population haplotype inference via a hierarchical dirichlet process mixture

Michael I. Jordan, E. Xing, Y. Teh, 2006, ICML.

Multi-Modal Distance Metric Learning

Pengtao Xie, Eric P. Xing, E. Xing, 2013, IJCAI.

Cauchy Principal Component Analysis pdf

Pengtao Xie, Eric P. Xing, E. Xing, 2014, ArXiv.

Variable selection in heterogeneous datasets: A truncated-rank sparse linear mixed model with applications to genome-wide association studies.

E. Xing, Haohan Wang, Bryon Aragam, 2018, Methods.

Robust Estimation of Local Genetic Ancestry in Admixed Populations Using a Nonparametric Bayesian Approach

E. Xing, Zoubin Ghahramani, Kyung-ah Sohn, 2012, Genetics.

Medical Diagnosis From Laboratory Tests by Combining Generative and Discriminative Learning pdf

Dong Wang, Shiyue Zhang, Pengtao Xie, 2017, ArXiv.

A Spectral Algorithm for Latent Junction Trees pdf

Le Song, Eric P. Xing, Ankur P. Parikh, 2012, UAI.

Classification of Breast Cancer Histopathological Images using Convolutional Neural Networks with Hierarchical Loss and Global Pooling

Eric P. Xing, Wei Dai, Nanqing Dong, 2018, ICIAR.

SPEX2: automated concise extraction of spatial gene expression patterns from Fly embryo ISH images

Christos Faloutsos, Eric P. Xing, Kriti Puniyani, 2010, Bioinform..

Judging LLM-as-a-judge with MT-Bench and Chatbot Arena

E. Xing, Joseph Gonzalez, Lianmin Zheng, 2023, NeurIPS.

XRayGAN: Consistency-preserving Generation of X-ray Images from Radiology Reports pdf

Xingyi Yang, Nandiraju Gireesh, Eric Xing, 2020, ArXiv.

Population Stratification with Mixed Membership Models

E. Xing, S. Shringarpure, 2014, Handbook of Mixed Membership Models and Their Applications.

mStruct: Inference of Population Structure in Light of Both Genetic Admixing and Allele Mutations

E. Xing, S. Shringarpure, 2009, Genetics.

Fast structure learning in generalized stochastic processes with latent factors

Eric P. Xing, Yan Liu, Mohammad Taha Bahadori, 2013, KDD.

Identification of Nonlinear Latent Hierarchical Models

E. Xing, Yuejie Chi, Biwei Huang, 2023, NeurIPS.

Efficient Algorithm for Extremely Large Multi-task Regression with Massive Structured Sparsity

Seunghak Lee, Eric P. Xing, E. Xing, 2012, 1208.3014.

Smoothing proximal gradient method for general structured sparse regression

E. Xing, X. Chen, J. Carbonell, 2010, The Annals of Applied Statistics.

Markov Network Estimation From Multi-attribute Data

Eric P. Xing, Mladen Kolar, Han Liu, 2013, ICML.

Infinite SVM: a Dirichlet Process Mixture of Large-margin Kernel Machines

Ning Chen, Eric P. Xing, Jun Zhu, 2011, ICML.

Sparse Output Coding for Large-Scale Visual Recognition

Bin Zhao, Eric P. Xing, E. Xing, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

MedLDA: maximum margin supervised topic models for regression and classification

E. Xing, Amr Ahmed, Jun Zhu, 2009, ICML '09.

LightLDA: Big Topic Models on Modest Compute Clusters

E. Xing, Qirong Ho, Wei Dai, 2014, ArXiv.

ZM-Net: Real-time Zero-shot Image Manipulation Network pdf

Eric P. Xing, Hao Zhang, Dit-Yan Yeung, 2017, ArXiv.

Staying Informed: Supervised and Semi-Supervised Multi-View Topical Analysis of Ideological Perspective

E. Xing, Amr Ahmed, 2010, EMNLP.

Automatic Human-like Mining and Constructing Reliable Genetic Association Database with Deep Reinforcement Learning

William W. Cohen, E. Xing, Haohan Wang, 2018, bioRxiv.

Unsupervised Pseudo-Labeling for Extractive Summarization on Electronic Health Records pdf

Pengtao Xie, Eric P. Xing, Keyang Xu, 2018, ArXiv.

Panoramic Learning with A Standardized Machine Learning Formalism pdf

Eric P. Xing, Zhiting Hu, E. Xing, 2021, ArXiv.

Iterative Graph Self-Distillation

E. Xing, Xiaodan Liang, Pan Zhou, 2020, IEEE Transactions on Knowledge and Data Engineering.

Robust Reverse Engineering of Dynamic Gene Networks Under Sample Size Heterogeneity

Wei Wu, Eric P. Xing, Ankur P. Parikh, 2013, Pacific Symposium on Biocomputing.

Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications

Eric P. Xing, Haohan Wang, Zhenglin Wu, 2018, bioRxiv.

Inferring Regulatory Networks Using a Hierarchical Bayesian Graphical Gaussian Model

E. Xing, Yiming Yang, Fan Li, 2006 .

On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks

E. Xing, Qirong Ho, Junming Yin, 2012, NIPS.

Finding Genome-Transcriptome-Phenome Associations with Structured Association Mapping and Visualization in GenAMap

Eric P. Xing, Ross E. Curtis, Peter Kinnaird, 2011, Pacific Symposium on Biocomputing.

Sparse Variable Selection on High Dimensional Heterogeneous Data With Tree Structured Responses

E. Xing, Haohan Wang, Xiang Liu, 2017, IEEE Access.

Joint latent topic models for text and citations

William W. Cohen, E. Xing, Amr Ahmed, 2008, KDD.

Large-scale Distributed Dependent Nonparametric Trees

Eric P. Xing, Zhiting Hu, Avinava Dubey, 2015, ICML.

A Multiscale Community Blockmodel for Network Exploration

Ankur P. Parikh, E. Xing, Qirong Ho, 2011, International Conference on Artificial Intelligence and Statistics.

Infinite Hierarchical MMSB Model for Nested Communities/Groups in Social Networks

Le Song, Eric P. Xing, Ankur P. Parikh, 2010, 1010.1868.

Scalable Modeling of Conversational-role based Self-presentation Characteristics in Large Online Forums pdf

Carolyn Penstein Rosé, Chong Wang, Eric P. Xing, 2015, ArXiv.

Understanding the Interaction between Interests, Conversations and Friendships in Facebook pdf

Rajat Raina, Rong Yan, Eric P. Xing, 2012, ArXiv.

Social Links from Latent Topics in Microblogs

Eric P. Xing, Shay B. Cohen, Jacob Eisenstein, 2010, HLT-NAACL 2010.

Sparse Additive Generative Models of Text

E. Xing, Amr Ahmed, Jacob Eisenstein, 2011, ICML.

Online Inference for the Infinite Topic-Cluster Model: Storylines from Streaming Text

E. Xing, Alex Smola, Qirong Ho, 2011, AISTATS.

Timeline: A Dynamic Hierarchical Dirichlet Process Model for Recovering Birth/Death and Evolution of Topics in Text Stream

E. Xing, Amr Ahmed, 2010, UAI.

MedLDA: maximum margin supervised topic models

E. Xing, Amr Ahmed, Jun Zhu, 2012, J. Mach. Learn. Res..

An E-cient Proximal Gradient Method for General Structured Sparse Learning

E. Xing, X. Chen, J. Carbonell, 2010 .

Dynamic Non-Parametric Mixture Models and the Recurrent Chinese Restaurant Process: with Applications to Evolutionary Clustering

E. Xing, Amr Ahmed, 2008, SDM.

Coupled Mixed Model for joint genetic analysis of complex disorders from independently collected data sets: application to Alzheimer’s disease and substance use disorder

E. Xing, Haohan Wang, M. Vanyukov, 2022 .

More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server

Phillip B. Gibbons, Garth A. Gibson, E. Xing, 2013, NIPS.

Knowledge-Aware Meta-learning for Low-Resource Text Classification

Eric P. Xing, Maruan Al-Shedivat, Huaxiu Yao, 2021, EMNLP.

On multiple foreground cosegmentation

Eric P. Xing, Gunhee Kim, E. Xing, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

GeePS: scalable deep learning on distributed GPUs with a GPU-specialized parameter server

Phillip B. Gibbons, E. Xing, Henggang Cui, 2016, EuroSys.

Kernel Embeddings of Latent Tree Graphical Models

Le Song, Eric P. Xing, Ankur P. Parikh, 2011, NIPS.

Distributed cosegmentation via submodular optimization on anisotropic diffusion

E. Xing, Li Fei-Fei, T. Kanade, 2011, 2011 International Conference on Computer Vision.

Cavs: A Vertex-centric Programming Interface for Dynamic Neural Networks pdf

Guangwen Yang, Eric P. Xing, Graham Neubig, 2017, ArXiv.

Deep Inductive Matrix Completion for Biomedical Interaction Prediction

Min Xu, Eric P. Xing, Wei Wu, 2019, 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Learning from All Types of Experiences: A Unifying Machine Learning Perspective

Eric P. Xing, Zhiting Hu, E. Xing, 2020, KDD.

A New Nonparametric Bayesian Model for Genetic Inference in Open Ancestral Space

Eric P. Xing, Kyung-Ah Sohn, E. Xing, 2006 .