Eric P. Xing

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

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.

Large-Scale Category Structure Aware Image Categorization

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

Parallel Markov Chain Monte Carlo for Pitman-Yor Mixture Models

Eric P. Xing, Kumar Avinava Dubey, Sinead Williamson, 2014, UAI.

Visualizing brand associations from web community photos

Eric P. Xing, Gunhee Kim, 2014, WSDM.

Multi-Modal Distance Metric Learning

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

Exploiting Genome Structure in Association Analysis

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

Turbo Parsers: Dependency Parsing by Approximate Variational Inference

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

Addressing the straggler problem for iterative convergent parallel ML

Eric P. Xing, Henggang Cui, Gregory R. Ganger, 2016, SoCC.

Self-Training for Jointly Learning to Ask and Answer Questions

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

Population Stratification with Mixed Membership Models

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

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 .

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

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

Nonextensive Information Theoretic Kernels on Measures

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

Ultra-high Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit: Screening Approach

Eric P. Xing, Mladen Kolar, 2010, AISTATS.

Enabling dynamic network analysis through visualization in TVNViewer

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

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.

Personalized regression enables sample-specific pan-cancer analysis

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

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

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

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

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

Few-Shot Semantic Segmentation with Prototype Learning

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

Probabilistic Graphical Models-Theory, Algorithm, and Application

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

Automatic mining of fruit fly embryo images

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

High-Dimensional Feature Selection by Feature-Wise Kernelized Lasso

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

Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices

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

Nonoverlap-Promoting Variable Selection

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

Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models

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

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).

Post-Inference Prior Swapping

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

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

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

Harmonium Models for Semantic Video Representation and Classification

Eric P. Xing, Jun Yang, Yan Liu, 2007, SDM.

Network Completion and Survey Sampling

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

Dynamic Language Models for Streaming Text

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

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

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

Minimizing Nonconvex Non-Separable Functions

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

Self-Challenging Improves Cross-Domain Generalization pdf

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

Asymptotically Exact, Embarrassingly Parallel MCMC pdf

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

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.

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.

CryptGraph: Privacy Preserving Graph Analytics on Encrypted Graph pdf

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

SeDMiD for Confusion Detection: Uncovering Mind State from Time Series Brain Wave Data pdf

Eric P. Xing, Jun Zhu, Haohan Wang, 2016, ArXiv.

Heterogeneous multitask learning with joint sparsity constraints

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

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

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

A Spectral Algorithm for Latent Tree Graphical Models

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

Advanced Machine Learning for Healthcare

Jimeng Sun, Suchi Saria, Eric P. Xing, 2016, CRI.

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

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

Admixtures of latent blocks with application to protein interaction networks

Eric P. Xing, Stephen E. Fienberg, David M. Blei, 2007 .

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..

Stability Selection for Structured Variable Selection pdf

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

Transformation Autoregressive Networks

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

TopicViz: interactive topic exploration in document collections

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

Augmenting Dual Decomposition for MAP Inference

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

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.

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

Ramesh Nallapati, Eric P. Xing, William W. Cohen, 2007 .

Regularized Adversarial Training (RAT) for Robust Cellular Electron Cryo Tomograms Classification

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

Multimodal Data Mining in a Multimedia Database Based on Structured Max Margin Learning

Christos Faloutsos, Zhen Guo, Eric P. Xing, 2016, TKDD.

Petuum: A New Platform for Distributed Machine Learning on Big Data

Yaoliang Yu, Pengtao Xie, Seunghak Lee, 2015, IEEE Trans. Big Data.

Approximating Correlated Equilibria using Relaxations on the Marginal Polytope

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

Nonparametric decentralized detection based on weighted count kernel

Yingbin Liang, Eric P. Xing, Jiayao Hu, 2012, 2012 IEEE International Symposium on Information Theory Proceedings.

Multiplex confounding factor correction for genomic association mapping with squared sparse linear mixed model

Ming Xu, Eric P. Xing, Yunpeng Xiao, 2017, BIBM.

Domain Adaption in One-Shot Learning

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

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

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

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

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

On Unifying Deep Generative Models pdf

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

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

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

Deep Kernel Learning pdf

Andrew Gordon Wilson, Eric P. Xing, Zhiting Hu, 2015, AISTATS.

Symmetric Correspondence Topic Models for Multilingual Text Analysis

Eric P. Xing, Koji Eguchi, Kosuke Fukumasu, 2012, NIPS.

Text Infilling pdf

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

Visual Explanations for Convolutional Neural Networks via Input Resampling pdf

Stephanie Rosenthal, Manuela M. Veloso, Eric P. Xing, 2017, ArXiv.

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

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

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

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

Dynamic-Structured Semantic Propagation Network

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

A generalized mean field algorithm for variational inference in exponential families

Michael I. Jordan, Eric P. Xing, Stuart J. Russell, 2002, UAI.

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.

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

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

TopicScape: Semantic Navigation of Document Collections pdf

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

Partially Observed Maximum Entropy Discrimination Markov Networks

Bo Zhang, Eric P. Xing, Jun Zhu, 2008, NIPS.

Supervised Adversarial Alignment of Single-Cell RNA-seq Data

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

Solving the Straggler Problem with Bounded Staleness

Seunghak Lee, Eric P. Xing, Kimberly Keeton, 2013, HotOS.

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

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

Toward personalized pan-omic association analysis under complex structures and big data

Eric P. Xing, 2015, BIBM.

Smoothing proximal gradient method for general structured sparse regression

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

Graph Partition Strategies for Generalized Mean Field Inference

Michael I. Jordan, Eric P. Xing, 2004, UAI.

Neural Architecture Search with Bayesian Optimisation and Optimal Transport pdf

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

Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces

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

Free Energy Estimates of All-Atom Protein Structures Using Generalized Belief Propagation

Eric P. Xing, Christopher James Langmead, Hetunandan Kamisetty, 2007, RECOMB.

Infinite Latent SVM for Classification and Multi-task Learning

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

Sparse sensor selection for nonparametric decentralized detection via L1 regularization

Yingbin Liang, Lixin Shen, Eric P. Xing, 2014, 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP).

Personalized Regression Enables Sample-Specific Pan-Cancer Analysis

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

Fast Distribution To Real Regression

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

Web image prediction using multivariate point processes

Fei-Fei Li, Eric P. Xing, Gunhee Kim, 2012, KDD.

A Multiscale Community Blockmodel for Network Exploration

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

Structured correspondence topic models for mining captioned figures in biological literature

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

Feature Selection in Microarray Analysis

Eric P. Xing, 2003 .

Poseidon: A System Architecture for Efficient GPU-based Deep Learning on Multiple Machines pdf

Pengtao Xie, Eric P. Xing, Zhiting Hu, 2015, ArXiv.

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.

Adaptive Multi-Task Lasso: with Application to eQTL Detection

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

Quasi Real-Time Summarization for Consumer Videos

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

MedLDA: maximum margin supervised topic models

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

Bayesian inference with posterior regularization and applications to infinite latent SVMs

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

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

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

Asynchronous Parallel Block-Coordinate Frank-Wolfe

Eric P. Xing, Yu-Xiang Wang, Wei Dai, 2014 .

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).

Distributed Proximal Gradient Algorithm for Partially Asynchronous Computer Clusters

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

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).

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).

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.

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

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

KELLER: estimating time-varying interactions between genes

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

Inferring Gene Interaction Networks from ISH Images via Kernelized Graphical Models

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

Latent Space Inference of Internet-Scale Networks

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

Feature Selection via Block-Regularized Regression

Eric P. Xing, Seyoung Kim, 2008, UAI.

Online Learning of Structured Predictors with Multiple Kernels

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

Supervised Probabilistic Robust Embedding with Sparse Noise

Eric P. Xing, Dit-Yan Yeung, Yu Zhang, 2012, AAAI.

Bayesian Nonparametric Kernel-Learning

Barnabás Póczos, Andrew Gordon Wilson, Eric P. Xing, 2015, AISTATS.

AutoLoss: Learning Discrete Schedules for Alternate Optimization pdf

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

Dilated temporal relational adversarial network for generic video summarization

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

A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences

Michael I. Jordan, Richard M. Karp, Eric P. Xing, 2002, NIPS.

Distributed Machine Learning via Sufficient Factor Broadcasting pdf

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

Large Scale Distributed Multiclass Logistic Regression pdf

Pengtao Xie, Eric P. Xing, Jin Kyu Kim, 2014, ArXiv.

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.

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

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

Analyzing Time-Evolving Networks

Eric P. Xing, Qirong Ho, 2014, Handbook of Mixed Membership Models and Their Applications.

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).

Social Links from Latent Topics in Microblogs

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

Block Regularized Lasso for Multivariate Multi-Response Linear Regression

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

Structure-Aware Dynamic Scheduler for Parallel Machine Learning pdf

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

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).

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

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

Laplace maximum margin Markov networks

Bo Zhang, Eric P. Xing, Jun Zhu, 2008, ICML '08.

Learning Robust Global Representations by Penalizing Local Predictive Power

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

Document hierarchies from text and links

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

Time-sensitive web image ranking and retrieval via dynamic multi-task regression

Eric P. Xing, Gunhee Kim, 2013, WSDM '13.

Mixed Membership Stochastic Blockmodels

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

Learning Latent Space Models with Angular Constraints

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

Deep Neural Networks with Massive Learned Knowledge

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

Complex Event Detection using Semantic Saliency and Nearly-Isotonic SVM

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

Logos: a Modular Bayesian Model for de Novo Motif Detection

Wei Wu, Michael I. Jordan, Richard M. Karp, 2004, J. Bioinform. Comput. Biol..

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

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

Litz: Elastic Framework for High-Performance Distributed Machine Learning

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

Spectral Unsupervised Parsing with Additive Tree Metrics

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

Supplementary Material for: Spectral Unsupervised Parsing with Additive Tree Metrics

Eric P. Xing, Shay B. Cohen, Ankur P. Parikh, 2011 .

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

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

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

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

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

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

Linear Time Samplers for Supervised Topic Models using Compositional Proposals

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

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.

Personalized Survival Prediction with Contextual Explanation Networks pdf

Eric P. Xing, Maruan Al-Shedivat, Avinava Dubey, 2018, ArXiv.

Large-scale Distributed Dependent Nonparametric Trees

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

Theoretically Principled Trade-off between Robustness and Accuracy

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

A Spectral Algorithm for Latent Junction Trees pdf

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

Predicting protein folds with structural repeats using a chain graph model

Jaime G. Carbonell, Eric P. Xing, Yan Liu, 2005, ICML '05.

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.

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

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

Exploiting Bounded Staleness to Speed Up Big Data Analytics

Seunghak Lee, Eric P. Xing, Henggang Cui, 2014, USENIX Annual Technical Conference.

Diversity-Promoting Bayesian Learning of Latent Variable Models pdf

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

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).

Nonextensive entropic kernels

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

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

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

Polyhedral outer approximations with application to natural language parsing

Eric P. Xing, Noah A. Smith, André F. T. Martins, 2009, ICML '09.

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.

Smoothing Proximal Gradient Method for General Structured Sparse Learning

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

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.

Monte Carlo Methods for Maximum Margin Supervised Topic Models

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

Enhanced max margin learning on multimodal data mining in a multimedia database

Christos Faloutsos, Zhen Guo, Eric P. Xing, 2007, KDD '07.

Controllable Text Generation pdf

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

Bayesian Inference with Posterior Regularization and Infinite Latent SVMs

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

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

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

Latent Variable Modeling with Diversity-Inducing Mutual Angular Regularization pdf

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

Toward Unsupervised Text Content Manipulation pdf

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

Machine Comprehension using Rich Semantic Representations

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

Group Sparse Additive Models

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

Probabilistic Graphical Models-Theory, Algorithm, and Application

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

Hidden Markov Dirichlet Process: Modeling Genetic Recombination in Open Ancestral Space

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

Structured literature image finder: Parsing text and figures in biomedical literature

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

Robust Reverse Engineering of Dynamic Gene Networks Under Sample Size Heterogeneity

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

Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks

Yihong Gong, Eric P. Xing, Amr Ahmed, 2008, ECCV.

Convolutional Neural Networks for Medical Diagnosis from Admission Notes pdf

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

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

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

On Time Varying Undirected Graphs

Eric P. Xing, Mladen Kolar, 2011, AISTATS.

Unsupervised Real-to-Virtual Domain Unification for End-to-End Highway Driving pdf

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

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

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

Smooth Kernels Improve Adversarial Robustness and Perceptually-Aligned Gradients

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

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

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

On the Complexity of Exploration in Goal-Driven Navigation pdf

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

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

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

Max margin learning on domain-independent web information extraction

Bin Zhao, Eric P. Xing, Xiaoxin Yin, 2011, CIKM '11.

Free Energy Estimates of All-Atom Protein Structures Using Generalized Belief Propagation

Eric P. Xing, Christopher James Langmead, Hetunandan Kamisetty, 2007, RECOMB.

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.

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

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

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

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

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

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

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

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

Iterative Graph Self-Distillation pdf

Pan Zhou, Eric P. Xing, Hanlin Zhang, 2020, ArXiv.

Distributed cosegmentation via submodular optimization on anisotropic diffusion

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

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

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

Lighter-Communication Distributed Machine Learning via Sufficient Factor Broadcasting

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

Sparsistent Estimation of Time-Varying Discrete Markov Random Fields

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

Aggressive Online Learning of Structured Classifiers

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

Connecting the Dots Between MLE and RL for Sequence Generation pdf

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

Scalable Dynamic Nonparametric Bayesian Models of Content and Users

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

Hierarchical Tensor Decomposition of Latent Tree Graphical Models

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

Multimodal Machine Learning for Automated ICD Coding pdf

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

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

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

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

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

Petuum: A Framework for Iterative-Convergent Distributed ML pdf

Seunghak Lee, Eric P. Xing, Xun Zheng, 2013, ArXiv.

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

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

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.

Bilingual Word Spectral Clustering for Statistical Machine Translation

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

Structured Literature Image Finder

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

Variance Reduction for Stochastic Gradient Optimization

Xi Chen, Alexander J. Smola, Chong Wang, 2013, NIPS.

Time-Varying Dynamic Bayesian Networks

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

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

Eric P. Xing, William W. Cohen, Haohan Wang, 2018 .

Semi-Supervised Learning Based on Semiparametric Regularization

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

Discovering Demographic Language Variation

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

Model-Parallel Inference for Big Topic Models pdf

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

A Joint Topic and Perspective Model for Ideological Discourse

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

Topic Models, Latent Space Models, Sparse Coding, and All That: A Systematic Understanding of Probabilistic Semantic Extraction in Large Corpus

Eric P. Xing, 2012, ACL.

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

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

A Latent Variable Model for Geographic Lexical Variation

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

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

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

Unsupervised Text Style Transfer using Language Models as Discriminators

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

Prior Swapping for Data-Independent Inference pdf

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

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

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

Discrete Temporal Models of Social Networks

Eric P. Xing, Steve Hanneke, E. Xing, 2006, SNA@ICML.

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

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

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

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

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

Spectrum: joint bayesian inference of population structure and recombination events

Eric P. Xing, Kyung-Ah Sohn, 2007, ISMB/ECCB.

Uncorrelation and Evenness: a New Diversity-Promoting Regularizer

Pengtao Xie, Eric P. Xing, Aarti Singh, 2017, ICML.

A Mixture Model of Demographic Lexical Variation

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

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

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

Diffusion of Lexical Change in Social Media pdf

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

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

Pengtao Xie, Eric P. Xing, Zhiting Hu, 2017, USENIX Annual Technical Conference.

Learning Concept Taxonomies from Multi-modal Data pdf

Eric P. Xing, Zhiting Hu, Mrinmaya Sachan, 2016, ACL.

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

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

GenAMap: Visualization strategies for structured association mapping

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

Interpretable Structure-Evolving LSTM

Shuicheng Yan, Eric P. Xing, Liang Lin, 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

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.

DAGs with NO TEARS: Continuous Optimization for Structure Learning

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

Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio pdf

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

Hybrid Subspace Learning for High-Dimensional Data pdf

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

Cauchy Principal Component Analysis pdf

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

Information Theory

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

Structured Databases of Named Entities from Bayesian Nonparametrics

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

More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server

Seunghak Lee, Eric P. Xing, Henggang Cui, 2013, NIPS.

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 .

Feature selection for high-dimensional genomic microarray data

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

Sparsistent Learning of Varying-coefficient Models with Structural Changes

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

MoGUL: Detecting Common Insertions and Deletions in a Population

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

Learning Structured Classifiers with Dual Coordinate Ascent

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

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

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

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

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

A Constituent-Centric Neural Architecture for Reading Comprehension

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

Restricting exchangeable nonparametric distributions

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

Mining User Interests from Personal Photos

Pengtao Xie, Eric P. Xing, Yulong Pei, 2015, AAAI.

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.

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

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

Symbolic Graph Reasoning Meets Convolutions

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

Learning Scalable Deep Kernels with Recurrent Structure

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

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

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

On Sparse Nonparametric Conditional Covariance Selection

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

Identifiability of Nonparametric Mixture Models and Bayes Optimal Clustering pdf

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

An Active Learning Approach to Coreference Resolution

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

On the Automatic Generation of Medical Imaging Reports

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

Recurrent Topic-Transition GAN for Visual Paragraph Generation

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

Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms

Eric P. Xing, Suvrit Sra, Yu-Xiang Wang, 2014, ICML.

Consistency Models for Distributed ML with Theoretical Guarantees

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

Discourse in Multimedia: A Case Study in Information Extraction pdf

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

SysML: On System and Algorithm Co-design for Practical Machine Learning

Eric P. Xing, 2018, KDD.

More Effective Distributed ML via a Structure-Aware Dynamic Scheduler

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

Online Multiple Kernel Learning for Structured Prediction

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

Fast structure learning in generalized stochastic processes with latent factors

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

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

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

GINI: From ISH Images to Gene Interaction Networks

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

A network-driven approach for genome-wide association mapping

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

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

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

On multiple foreground cosegmentation

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

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

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

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

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

Variance Reduction in Stochastic Gradient Langevin Dynamics

Alexander J. Smola, Barnabás Póczos, Eric P. Xing, 2016, NIPS.

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

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

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

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

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

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

Seeing the Forest from the Trees in Two Looks: Matrix Sketching by Cascaded Bilateral Sampling pdf

Hui Xiong, Jieping Ye, Eric P. Xing, 2016, ArXiv.

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).

Progressive Generation of Long Text pdf

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

Markov Network Estimation From Multi-attribute Data

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

Squared 𝓁2 Norm as Consistency Loss for Leveraging Augmented Data to Learn Robust and Invariant Representations pdf

Eric P. Xing, Zeyi Huang, Haohan Wang, 2020, ArXiv.

Predicting Discharge Medications at Admission Time Based on Deep Learning pdf

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

Community Specific Temporal Topic Discovery from Social Media pdf

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

Generalized Zero-Shot Text Classification for ICD Coding

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

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

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

Diversifying Restricted Boltzmann Machine for Document Modeling

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

Primitives for Dynamic Big Model Parallelism pdf

Seunghak Lee, Eric P. Xing, Xun Zheng, 2014, ArXiv.

Near-Orthogonality Regularization in Kernel Methods

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

Concise Integer Linear Programming Formulations for Dependency Parsing

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

Grafting-light: fast, incremental feature selection and structure learning of Markov random fields

Eric P. Xing, Ni Lao, Jun Zhu, 2010, KDD '10.

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

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

Toward Controllable Text Content Manipulation

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

An Adaptive Learning Rate for Stochastic Variational Inference

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

Community Level Diffusion Extraction

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

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

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

Fault Tolerance in Iterative-Convergent Machine Learning pdf

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

Grounding Topic Models with Knowledge Bases

Eric P. Xing, Zhiting Hu, Mrinmaya Sachan, 2016, IJCAI.

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.

Structured Generative Adversarial Networks

Eric P. Xing, Hao Zhang, Jun Zhu, 2017, NIPS.

Learning to Solve Geometry Problems from Natural Language Demonstrations in Textbooks

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

State Space LSTM Models with Particle MCMC Inference pdf

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

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..

Standardized Tests as benchmarks for Artificial Intelligence

Eric P. Xing, Mrinmaya Sachan, Hannaneh Hajishirzi, 2018, EMNLP 2018.

Toward Controlled Generation of Text

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

Mining Associated Text and Images with Dual-Wing Harmoniums pdf

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

A latent mixed membership model for relational data

Edoardo M. Airoldi, Eric P. Xing, Stephen E. Fienberg, 2005, LinkKDD '05.

Kernel methods for large-scale genomic data analysis

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

Discovering Sociolinguistic Associations with Structured Sparsity

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

Exploiting iterative-ness for parallel ML computations

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

FlexiFaCT: Scalable Flexible Factorization of Coupled Tensors on Hadoop

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

HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation

Eric P. Xing, Bing Zhao, 2007, NIPS.

Learning Sample-Specific Models with Low-Rank Personalized Regression

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

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.

C-DEM: a multi-modal query system for Drosophila Embryo databases

Christos Faloutsos, Fan Guo, Eric P. Xing, 2008, Proc. VLDB Endow..

Supervised Adversarial Alignment of Single-Cell RNA-seq Data

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

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

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

Petuum: A New Platform for Distributed Machine Learning on Big Data

Yaoliang Yu, Pengtao Xie, Seunghak Lee, 2013, IEEE Transactions on Big Data.

Large Margin Learning of Upstream Scene Understanding Models

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

PPDsparse: A Parallel Primal-Dual Sparse Method for Extreme Classification

Pradeep Ravikumar, Inderjit S. Dhillon, Eric P. Xing, 2017, KDD.

Learning Data Manipulation for Augmentation and Weighting

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

Scalable Overlapping Community Detection in Internet-Scale Networks

Eric P. Xing, Qirong Ho, Junming Yin, 2014 .

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

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

Fast Function to Function Regression pdf

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

Nonparametric Variational Auto-Encoders for Hierarchical Representation Learning

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

Validate and Enable Machine Learning in Industrial AI pdf

Pengtao Xie, Eric P. Xing, Yuqi Wang, 2020, ArXiv.

LightLDA: Big Topic Models on Modest Computer Clusters

Tie-Yan Liu, Wei-Ying Ma, Eric P. Xing, 2014, WWW.

Generative Semantic Manipulation with Contrasting GAN pdf

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

Strategies and Principles of Distributed Machine Learning on Big Data pdf

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

On primal and dual sparsity of Markov networks

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

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.

On Model Parallelization and Scheduling Strategies for Distributed Machine Learning

Seunghak Lee, Eric P. Xing, Xun Zheng, 2014, NIPS.

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

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

TopicViz: Semantic Navigation of Document Collections

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

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.

Primal sparse Max-margin Markov networks

Bo Zhang, Eric P. Xing, Jun Zhu, 2009, KDD.

Object Bank: A High-Level Image Representation for Scene Classification & Semantic Feature Sparsification

Hao Su, Fei-Fei Li, Eric P. Xing, 2010, NIPS.

Incorporating Word Correlation Knowledge into Topic Modeling

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

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

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

Embarrassingly Parallel Variational Inference in Nonconjugate Models pdf

Chong Wang, Eric P. Xing, Willie Neiswanger, 2015, ArXiv.

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

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

Techniques for proving Asynchronous Convergence results for Markov Chain Monte Carlo methods pdf

Eric P. Xing, Alexander Terenin, 2017, ArXiv.

Bayesian haplo-type inference via the dirichlet process

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

Generative Semantic Manipulation with Mask-Contrasting GAN

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

Target-Guided Open-Domain Conversation

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

Language Modeling with Power Low Rank Ensembles

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

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

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

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.

Sparse Output Coding for Scalable Visual Recognition

Bin Zhao, Eric P. Xing, 2015, International Journal of Computer Vision.

Nonparametric Decentralized Detection and Sparse Sensor Selection Via Weighted Kernel

Yingbin Liang, Lixin Shen, Eric P. Xing, 2016, IEEE Transactions on Signal Processing.

From Lasso regression to Feature vector machine

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

Adversarial Connective-exploiting Networks for Implicit Discourse Relation Classification

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

Integrating Image Clustering and Codebook Learning

Pengtao Xie, Eric P. Xing, 2015, AAAI.

Learning Sparse Nonparametric DAGs

Pradeep Ravikumar, Eric P. Xing, Chen Dan, 2020, AISTATS.

Comparison of normalization methods for CodeLink Bioarray data

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

Multi-population GWA mapping via multi-task regularized regression

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

Contextual Explanation Networks pdf

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

Maximum Entropy Discrimination Markov Networks

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

Kernel Embeddings of Latent Tree Graphical Models

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

Discovering Pictorial Brand Associations from Large-Scale Online Image Data

Eric P. Xing, Gunhee Kim, 2013, 2013 IEEE International Conference on Computer Vision Workshops.

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

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

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

Ramesh Nallapati, Eric P. Xing, William W. Cohen, 2007, Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007).

Entity Hierarchy Embedding

Eric P. Xing, Zhiting Hu, Yuntian Deng, 2015, ACL.

Stochastic Variational Deep Kernel Learning

Andrew Gordon Wilson, Eric P. Xing, Zhiting Hu, 2016, NIPS.

An Augmented Lagrangian Approach to Constrained MAP Inference

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

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

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

Large Scale Distributed Distance Metric Learning pdf

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

Unified analysis of streaming news

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

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).

Image Segmentation with Topic Random Field

Fei-Fei Li, Eric P. Xing, Bin Zhao, 2010, ECCV.

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

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

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

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

Fair Deep Learning Prediction for Healthcare Applications with Confounder Filtering pdf

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

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

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

Conditional Topic Random Fields

Eric P. Xing, Jun Zhu, 2010, ICML.

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

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

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

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

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.

On the Generation of Medical Dialogues for COVID19

Xingyi Yang, Pengtao Xie, Eric P. Xing, 2020 .

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

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

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).

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

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

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

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

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).

Modeling and Analysis of Dynamic Behaviors of Web Image Collections

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

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

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

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..

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

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

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

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

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

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

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

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

Towards Visual Question Answering on Pathology Images

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

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

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

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

Eric P. Xing, Ivet Bahar, Fen Pei, 2021, BMC Bioinform..

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

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

Text Generation with Efficient (Soft) Q-Learning pdf

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

Panoramic Learning with A Standardized Machine Learning Formalism pdf

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

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

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

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

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

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

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

Towards Principled Disentanglement for Domain Generalization pdf

Eric P. Xing, Adrian Weller, Weiyang Liu, 2021, ArXiv.

On the Generation of Medical Dialogs for COVID-19

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

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.

Exact and Efficient Parallel Inference for Nonparametric Mixture Models

Eric P. Xing, Avinava Dubey, Sinead A. Williamson, 2012 .

An Efficient Proximal Gradient Method for General Structured Structured Sparse Learning

Eric P. Xing, Xi Chen Qihang Lin Seyoung Kim Jaime Carbonell, 2010 .

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

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

MedLDA: A General Framework of Maximum Margin Supervised Topic Models

Eric P. Xing, Jun Zhu, Amr Ahmed, 2009 .

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.