Changyou Chen

发表

On Connecting Stochastic Gradient MCMC and Differential Privacy

Lawrence Carin, Bai Li, Changyou Chen, 2017, AISTATS.

Yee Whye Teh, Vinayak A. Rao, Wray L. Buntine, 2013, ICML.

Supplementary material for Dependent Normalized Random Measures

Vinayak A. Rao, Wray L. Buntine, Changyou Chen, 2013 .

Distance Approximating Dimension Reduction of Riemannian Manifolds

Rudolf Fleischer, Junping Zhang, Changyou Chen, 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Bayesian Sampling Using Stochastic Gradient Thermostats

Ryan Babbush, Hartmut Neven, Nan Ding, 2014, NIPS.

On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators

Lawrence Carin, Nan Ding, Changyou Chen, 2015, NIPS.

Continuous-Time Flows for Deep Generative Models

L. Carin, Liqun Chen, Chunyuan Li, 2017 .

Distributionally Adversarial Attack pdf

Kui Ren, Changyou Chen, Tianhang Zheng, 2018, AAAI.

Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks

Lawrence Carin, David E. Carlson, Chunyuan Li, 2015, AAAI.

Particle Optimization in Stochastic Gradient MCMC

Ruiyi Zhang, Changyou Chen, 2017, 1711.10927.

Learning Structured Weight Uncertainty in Bayesian Neural Networks

Lawrence Carin, Shengyang Sun, Changyou Chen, 2017, AISTATS.

Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization pdf

Zhe Gan, Lawrence Carin, David E. Carlson, 2015, AISTATS.

Learning Weight Uncertainty with Stochastic Gradient MCMC for Shape Classification

Zhe Gan, Lawrence Carin, Yunchen Pu, 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Monomial Gamma Monte Carlo Sampling

L. Carin, Changyou Chen, Kai Fan, 2016 .

Nested-Wasserstein Distance for Sequence Generation

L. Carin, Zheng Wen, Wenlin Wang, 2019 .

Deep Distance Metric Learning with Data Summarization

L. Carin, Wenlin Wang, Changyou Chen, 2016 .

Supplemental Material For " Differenctially Private Empirical Risk Minimization with Non-convex Loss Functions "

Changyou Chen, Jinhui Xu, Di Wang, 2019 .

3 Deep Neural Networks with Matrix Variate Gaussian Priors

L. Carin, Changyou Chen, Shengyang Sun, 2017 .

Differentially Private Empirical Risk Minimization with Non-convex Loss Functions

Di Wang, Changyou Chen, Jinhui Xu, 2019, ICML.

Supplement for Differential Topic Modeling

Wray L. Buntine, Changyou Chen, N. Ding, 2014 .

Certified Adversarial Robustness with Additive Noise

L. Carin, Wenlin Wang, Bai Li, 2018, NeurIPS.

MINIMAL: Mining Models for Universal Adversarial Triggers

Yaman Kumar Singla, Changyou Chen, Balaji Krishnamurthy, 2022, AAAI.

Outline to Story: Fine-grained Controllable Story Generation from Cascaded Events pdf

Tao Zeng, Changyou Chen, Liefeng Bo, 2021, ArXiv.

Learning High-Dimensional Distributions with Latent Neural Fokker-Planck Kernels pdf

Changyou Chen, Jinhui Xu, Yufan Zhou, 2021, ArXiv.

Persuasion Strategies in Advertisements: Dataset, Modeling, and Baselines

Yaman Kumar Singla, Changyou Chen, Milan Aggarwal, 2022, ArXiv.

GreenABR: energy-aware adaptive bitrate streaming with deep reinforcement learning

Muhammed Fatih Bulut, Daby M. Sow, Bekir O. Turkkan, 2022, MMSys.

GreenABR

Muhammed Fatih Bulut, Bekir O. Turkkan, Changyou Chen, 2022, Proceedings of the 13th ACM Multimedia Systems Conference.

Transformer-based Conditional Variational Autoencoder for Controllable Story Generation pdf

Changyou Chen, Liefeng Bo, Chaochun Liu, 2021, ArXiv.

Shifted Diffusion for Text-to-image Generation

Changyou Chen, Xiao Yang, Yizhe Zhu, 2022, ArXiv.

Lafite2: Few-shot Text-to-Image Generation

Changyou Chen, Jianfeng Gao, Jinhui Xu, 2022, ArXiv.

AUC Maximization for Low-Resource Named Entity Recognition

Wray L. Buntine, Changyou Chen, R. Beare, 2022, ArXiv.

Non-Parametric Kernel Learning with robust pairwise constraints

Changyou Chen, Junping Zhang, Xuefang He, 2011, International Journal of Machine Learning and Cybernetics.

Nonparametric Bayesian Topic Modelling with the Hierarchical Pitman-Yor Processes pdf

Lan Du, Wray L. Buntine, Changyou Chen, 2016, Int. J. Approx. Reason..

Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning pdf

Andrew Gordon Wilson, Changyou Chen, Chunyuan Li, 2019, ICLR.

Towards Language-Free Training for Text-to-Image Generation

Ruiyi Zhang, Chunyuan Li, Changyou Chen, 2021, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

CrossTx: Cross-cell line Transcriptomic Signature Predictions

Changyou Chen, Rudiyanto Gunawan, P. Chrysinas, 2023, bioRxiv.

Reward Constrained Interactive Recommendation with Natural Language Feedback pdf

Hongxia Jin, Lawrence Carin, Changyou Chen, 2020, ArXiv.

Scalable Thompson Sampling via Optimal Transport

Lawrence Carin, Changyou Chen, Zheng Wen, 2019, AISTATS.

Learning Structural Weight Uncertainty for Sequential Decision-Making

Lawrence Carin, Chunyuan Li, Changyou Chen, 2017, AISTATS.

Holistic Brain Tumor Screening and Classification Based on DenseNet and Recurrent Neural Network

Kai Xu, Hong Zhu, Jinhui Xu, 2018, BrainLes@MICCAI.

Zero-Shot Learning via Class-Conditioned Deep Generative Models

Kai Fan, Lawrence Carin, Piyush Rai, 2017, AAAI.

Policy Optimization as Wasserstein Gradient Flows

Lawrence Carin, Chunyuan Li, Changyou Chen, 2018, ICML.

A Unified Particle-Optimization Framework for Scalable Bayesian Sampling pdf

Bai Li, Liqun Chen, Changyou Chen, 2018, UAI.

Towards Fair Federated Learning with Zero-Shot Data Augmentation

Lawrence Carin, Changyou Chen, Jungwon Lee, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Semantic Matching for Sequence-to-Sequence Learning

Lawrence Carin, Changyou Chen, Ruiyi Zhang, 2020, Findings of the Association for Computational Linguistics: EMNLP 2020.

Improving Adversarial Text Generation by Modeling the Distant Future

Zhe Gan, Lawrence Carin, Dinghan Shen, 2020, ACL.

Nested-Wasserstein Self-Imitation Learning for Sequence Generation pdf

Zhe Gan, Lawrence Carin, Changyou Chen, 2020, AISTATS.

Topic-Guided Variational Auto-Encoder for Text Generation pdf

Guoyin Wang, Zhe Gan, Lawrence Carin, 2019, NAACL.

Improving Sequence-to-Sequence Learning via Optimal Transport pdf

Zhe Gan, Haichao Zhang, Liqun Chen, 2019, ICLR.

Sequence Generation with Guider Network pdf

Guoyin Wang, Zhe Gan, Liqun Chen, 2018, ArXiv.

Perception Point: Identifying Critical Learning Periods in Speech for Bilingual Networks pdf

Rajiv Ratn Shah, Changyou Chen, Anuj Saraswat, 2021, ArXiv.

Shifted Diffusion for Text-to-image Generation

Changyou Chen, Xiao Yang, Yizhe Zhu, 2022, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

A Generic Approach for Enhancing GANs by Regularized Latent Optimization pdf

Changyou Chen, Chunyuan Li, Jinhui Xu, 2021, ArXiv.

Unpaired Image-to-Image Translation via Latent Energy Transport

Changyou Chen, Yang Zhao, 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Feature Quantization Improves GAN Training pdf

Jianfeng Gao, Changyou Chen, Ping Yu, 2020, ICML.

Learning Manifold Implicitly via Explicit Heat-Kernel Learning

Changyou Chen, Jinhui Xu, Yufan Zhou, 2020, NeurIPS.

KernelNet: A Data-Dependent Kernel Parameterization for Deep Generative Modeling pdf

Changyou Chen, Yufan Zhou, Jinhui Xu, 2019, ArXiv.

What all do audio transformer models hear? Probing Acoustic Representations for Language Delivery and its Structure pdf

Rajiv Ratn Shah, Changyou Chen, Jui Shah, 2021, ArXiv.

Continuous-Time Flows for Efficient Inference and Density Estimation

Lawrence Carin, Yunchen Pu, Chunyuan Li, 2017, ICML.

Scalable Bayesian Non-negative Tensor Factorization for Massive Count Data

Matthew Harding, Lawrence Carin, Piyush Rai, 2015, ECML/PKDD.

ALCAP: Alignment-Augmented Music Captioner

Changyou Chen, Kristina Lerman, Weiyi Lu, 2022, 2212.10901.

Bayesian Multi-type Mean Field Multi-agent Imitation Learning

Fan Yang, Changyou Chen, Wen Dong, 2020, NeurIPS.

Rethinking Sentiment Style Transfer

Changyou Chen, Ping Yu, Chunyuan Li, 2021, EMNLP.

PointCloud Saliency Maps

Kui Ren, Changyou Chen, Junsong Yuan, 2018, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

Fine-Grained Attention and Feature-Sharing Generative Adversarial Networks for Single Image Super-Resolution

Changyou Chen, Xianfang Sun, Longcun Jin, 2019, IEEE Transactions on Multimedia.

Structure-Aware Human-Action Generation pdf

Yang Zhao, Changyou Chen, Ping Yu, 2020, ECCV.

Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions pdf

Yang Zhao, Changyou Chen, Ruiyi Zhang, 2019, AAAI.

Persuasion Strategies in Advertisements: Dataset, Modeling, and Baselines

Yaman Kumar Singla, Changyou Chen, Milan Aggarwal, 2022, AAAI.

MixKD: Towards Efficient Distillation of Large-scale Language Models pdf

Lawrence Carin, Dinghan Shen, Changyou Chen, 2020, ICLR.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation

Jun Wen, Nenggan Zheng, Zhefeng Gong, 2019, IJCAI.

Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints pdf

Dong Yu, Xiaoyang Wang, Changyou Chen, 2020, ACL.

ReMP: Rectified Metric Propagation for Few-Shot Learning pdf

Yang Zhao, Changyou Chen, Chunyuan Li, 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Second-Order Adversarial Attack and Certifiable Robustness

Lawrence Carin, Changyou Chen, Bai Li, 2018, ArXiv.

Unsupervised Hashing with Contrastive Information Bottleneck

Changyou Chen, Qinliang Su, Zijing Ou, 2021, IJCAI.

Multi-Scale Residual Hierarchical Dense Networks for Single Image Super-Resolution

Paul L. Rosin, Changyou Chen, Xianfang Sun, 2019, IEEE Access.

Prompt Tuning based Adapter for Vision-Language Model Adaption

Changyou Chen, Zihao Lin, Jingchen Sun, 2023, ArXiv.

ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching

Lawrence Carin, Liqun Chen, Yunchen Pu, 2017, NIPS.

TiGAN: Text-Based Interactive Image Generation and Manipulation

Ruiyi Zhang, Changyou Chen, Jiuxiang Gu, 2022, AAAI.

MINIMAL: Mining Models for Data Free Universal Adversarial Triggers pdf

Rajiv Ratn Shah, Swapnil Parekh, Changyou Chen, 2021, ArXiv.

Text-Based Interactive Recommendation via Constraint-Augmented Reinforcement Learning

Hongxia Jin, Lawrence Carin, Changyou Chen, 2019, NeurIPS.

Implicit Deep Latent Variable Models for Text Generation

Jianfeng Gao, Chunyuan Li, Changyou Chen, 2019, EMNLP.

Variance Reduction in Stochastic Particle-Optimization Sampling

Yang Zhao, Changyou Chen, Jianyi Zhang, 2018, ICML.

High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models

Kai Fan, Lawrence Carin, Chunyuan Li, 2015, AAAI.

SecSIFT: Secure Image SIFT Feature Extraction in Cloud Computing

Cong Wang, Chang Wen Chen, Kui Ren, 2016, ACM Trans. Multim. Comput. Commun. Appl..

Towards Efficient Privacy-preserving Image Feature Extraction in Cloud Computing

Cong Wang, Chang Wen Chen, Kui Ren, 2014, ACM Multimedia.

Bayesian Meta Sampling for Fast Uncertainty Adaptation

Yang Zhao, Changyou Chen, Ruiyi Zhang, 2020, ICLR.

Towards Understanding the Adversarial Vulnerability of Skeleton-based Action Recognition pdf

Sheng Liu, Junsong Yuan, Kui Ren, 2020, ArXiv.

On Norm-Agnostic Robustness of Adversarial Training pdf

Lawrence Carin, Changyou Chen, Wenlin Wang, 2019, ArXiv.

Understanding and Constructing Latent Modality Structures in Multi-Modal Representation Learning

Trishul M. Chilimbi, Liqun Chen, Changyou Chen, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling pdf

Zhe Gan, Lawrence Carin, Yunchen Pu, 2016, ACL.

Stochastic Gradient MCMC with Stale Gradients

Lawrence Carin, Nan Ding, Chunyuan Li, 2016, NIPS.

Automatic Essay Scoring Systems Are Both Overstable And Oversensitive: Explaining Why And Proposing Defenses

Yaman Kumar Singla, Changyou Chen, R. Shah, 2023, Dialogue Discourse.

Automatic Essay Scoring Systems Are Both Overstable And Oversensitive: Explaining Why And Proposing Defenses pdf

Rajiv Ratn Shah, Swapnil Parekh, Changyou Chen, 2021, Dialogue Discourse.

Hardness-guided domain adaptation to recognise biomedical named entities under low-resource scenarios

Wray L. Buntine, Changyou Chen, Changyou Chen, 2022, EMNLP.

! " ! " ! : Input Object " : Output Label : Hidden Units : Weight with 8 a fixed value : Weight with a distribution

L. Carin, Chunyuan Li, Changyou Chen, 2016 .

Meta-Learning with Neural Tangent Kernels pdf

Changyou Chen, Yufan Zhou, Jiayi Xian, 2021, ICLR.

Stochastic Gradient Monomial Gamma Sampler

Zhe Gan, Lawrence Carin, Changyou Chen, 2017, ICML.

Scalable Deep Poisson Factor Analysis for Topic Modeling

Zhe Gan, Lawrence Carin, David E. Carlson, 2015, ICML.

Discretized Bottleneck in VAE: Posterior-Collapse-Free Sequence-to-Sequence Learning pdf

Yang Zhao, Changyou Chen, Ping Yu, 2020, ArXiv.

Learning Unnormalized Statistical Models via Compositional Optimization

Tianbao Yang, Changyou Chen, Lijun Zhang, 2023, ICML.

STT: Soft Template Tuning for Few-Shot Adaptation

Chunyuan Li, Changyou Chen, Wei Wang, 2022, 2022 IEEE International Conference on Data Mining Workshops (ICDMW).

Non-Parametric Kernel Learning with robust pairwise constraints

Zhi-Hua Zhou, Junping Zhang, Changyou Chen, 2012, Int. J. Mach. Learn. Cybern..

Certified Adversarial Robustness with Additive Gaussian Noise

Lawrence Carin, Changyou Chen, Wenlin Wang, 2018, NeurIPS 2019.

Nonlinear Statistical Learning with Truncated Gaussian Graphical Models

Lawrence Carin, Changyou Chen, Xuejun Liao, 2016, ICML.

Low-Resolution Gait Recognition

Rudolf Fleischer, Junping Zhang, Changyou Chen, 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Differential Topic Models

Lan Du, Lexing Xie, Wray L. Buntine, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels

Ruiyi Zhang, Changyou Chen, Tong Yu, 2023, ArXiv.

Communication-Efficient Stochastic Gradient MCMC for Neural Networks

Lawrence Carin, Yunchen Pu, Chunyuan Li, 2019, AAAI.

Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference

Changyou Chen, Yifan Hu, Changwei Hu, 2020, EMNLP.

Speaker-Conditioned Hierarchical Modeling for Automated Speech Scoring

Rajiv Ratn Shah, Changyou Chen, Balaji Krishnamurthy, 2021, CIKM.

Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling pdf

Wray L. Buntine, Nan Ding, Changyou Chen, 2012, ICML.

Sequential latent Dirichlet allocation

Huidong Jin, Lan Du, Wray L. Buntine, 2012, Knowledge and Information Systems.

Earliness-Aware Deep Convolutional Networks for Early Time Series Classification pdf

Lawrence Carin, Piyush Rai, Wenqi Wang, 2016, ArXiv.

Why do We Need Large Batchsizes in Contrastive Learning? A Gradient-Bias Perspective

Trishul M. Chilimbi, Liqun Chen, Changyou Chen, 2022, NeurIPS.

Robust Bayesian Max-Margin Clustering

Xinhua Zhang, Jun Zhu, Changyou Chen, 2014, NIPS.

Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory pdf

Changyou Chen, Jianyi Zhang, Ruiyi Zhang, 2018, AISTATS.

GLIMA: Global and Local Time Series Imputation with Multi-directional Attention Learning

Changyou Chen, Weida Zhong, Qiuling Suo, 2020, 2020 IEEE International Conference on Big Data (Big Data).

Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm

Chenglin Miao, Lu Su, Mengdi Huai, 2019, IJCAI.

Adversarial Learning of a Sampler Based on an Unnormalized Distribution

Guoyin Wang, Lawrence Carin, Ke Bai, 2019, AISTATS.

Twitter-Network Topic Model: A Full Bayesian Treatment for Social Network and Text Modeling pdf

Wray L. Buntine, Changyou Chen, Kar Wai Lim, 2016, ArXiv.

Weakly-Supervised Brain Tumor Classification with Global Diagnosis Label

Jinhui Xu, Changyou Chen, Hong Zhu, 2020, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).

Laplacian Hamiltonian Monte Carlo

Lawrence Carin, Changyou Chen, Ricardo Henao, 2016, ECML/PKDD.

Towards Unifying Hamiltonian Monte Carlo and Slice Sampling

Xiangyu Wang, Kai Fan, Lawrence Carin, 2016, NIPS.

What Do Audio Transformers Hear? Probing Their Representations For Language Delivery & Structure

Yaman Kumar Singla, Changyou Chen, R. Shah, 2022, 2022 IEEE International Conference on Data Mining Workshops (ICDMW).

Constructing dependent random probability measures from completely random measures

Vinayak A. Rao, Wray L. Buntine, Y. Teh, 2013 .

SDA: Improving Text Generation with Self Data Augmentation pdf

Yang Zhao, Yizhe Zhang, Changyou Chen, 2021, ArXiv.

Deep Metric Learning with Data Summarization

Wenlin Chen, Lawrence Carin, Piyush Rai, 2016, ECML/PKDD.

Sampling Table Configurations for the Hierarchical Poisson-Dirichlet Process

Lan Du, Wray L. Buntine, Changyou Chen, 2011, ECML/PKDD.

Twitter-Network Topic Model : A Full Bayesian Treatment for Social Network and Text Modeling

Wray L. Buntine, Kar Wai Lim, Changyou Chen, 2013 .

Document Hashing with Mixture-Prior Generative Models pdf

Dinghan Shen, Wei Dong, Changyou Chen, 2019, EMNLP.

Structure-Aware Human-Action Generation

Chunyuan Li, Changyou Chen, Ping Yu, 2020, ECCV.

ReAugKD: Retrieval-Augmented Knowledge Distillation For Pre-trained Language Models

Trishul M. Chilimbi, Kai Zhong, Guoyin Wang, 2023, ACL.