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2020 – today
- 2024
[j11]Bekir Oguzhan Turkkan
, Ting Dai, Adithya Raman, Tevfik Kosar, Changyou Chen, Muhammed Fatih Bulut, Jaroslav Zola, Daby Sow:
GreenABR+: Generalized Energy-Aware Adaptive Bitrate Streaming. ACM Trans. Multim. Comput. Commun. Appl. 20(9): 269:1-269:24 (2024)- [c104]Ruiyi Zhang, Yanzhe Zhang, Jian Chen, Yufan Zhou, Jiuxiang Gu, Changyou Chen, Tong Sun:
TRINS: Towards Multimodal Language Models that Can Read. CVPR 2024: 22584-22594 - [c103]Jian Chen, Ruiyi Zhang, Yufan Zhou, Jennifer Healey, Jiuxiang Gu, Zhiqiang Xu, Changyou Chen:
TextLap: Customizing Language Models for Text-to-Layout Planning. EMNLP (Findings) 2024: 14275-14289 - [c102]Changyou Chen, Han Ding, Bunyamin Sisman, Yi Xu, Ouye Xie, Benjamin Z. Yao, Son Dinh Tran, Belinda Zeng:
Diffusion Models for Multi-Task Generative Modeling. ICLR 2024 - [c101]Jian Chen, Ruiyi Zhang, Yufan Zhou, Changyou Chen:
Towards Aligned Layout Generation via Diffusion Model with Aesthetic Constraints. ICLR 2024 - [c100]Ashmit Khandelwal, Aditya Agrawal, Aanisha Bhattacharyya, Yaman Kumar, Somesh Singh, Uttaran Bhattacharya, Ishita Dasgupta, Stefano Petrangeli, Rajiv Ratn Shah, Changyou Chen, Balaji Krishnamurthy:
Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior. ICLR 2024 - [c99]Rohan Sharma, Kaiyi Ji, Zhiqiang Xu, Changyou Chen:
AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning. ICLR 2024 - [i95]Jian Chen, Ruiyi Zhang, Yufan Zhou, Changyou Chen:
Towards Aligned Layout Generation via Diffusion Model with Aesthetic Constraints. CoRR abs/2402.04754 (2024) - [i94]Rohan Sharma, Shijie Zhou, Kaiyi Ji, Changyou Chen:
Discriminative Adversarial Unlearning. CoRR abs/2402.06864 (2024) - [i93]Somesh Singh, Harini S. I, Yaman Kumar Singla, Veeky Baths, Rajiv Ratn Shah, Changyou Chen, Balaji Krishnamurthy:
LLaVA Finds Free Lunch: Teaching Human Behavior Improves Content Understanding Abilities Of LLMs. CoRR abs/2405.00942 (2024) - [i92]Ruiyi Zhang, Yanzhe Zhang, Jian Chen, Yufan Zhou, Jiuxiang Gu, Changyou Chen, Tong Sun:
TRINS: Towards Multimodal Language Models that Can Read. CoRR abs/2406.06730 (2024) - [i91]Jingchen Sun, Rohan Sharma, Vishnu Suresh Lokhande, Changyou Chen:
Craft: Cross-modal Aligned Features Improve Robustness of Prompt Tuning. CoRR abs/2407.15894 (2024) - [i90]Changyou Chen, Han Ding, Bunyamin Sisman, Yi Xu, Ouye Xie, Benjamin Z. Yao, Son Dinh Tran, Belinda Zeng:
Diffusion Models for Multi-Task Generative Modeling. CoRR abs/2407.17571 (2024) - [i89]Ruiyi Zhang, Yufan Zhou, Jian Chen, Jiuxiang Gu, Changyou Chen, Tong Sun:
LLaVA-Read: Enhancing Reading Ability of Multimodal Language Models. CoRR abs/2407.19185 (2024) - [i88]Jian Chen, Ruiyi Zhang, Yufan Zhou, Ryan A. Rossi, Jiuxiang Gu, Changyou Chen:
MMR: Evaluating Reading Ability of Large Multimodal Models. CoRR abs/2408.14594 (2024) - [i87]Jian Chen, Ruiyi Zhang, Yufan Zhou, Jennifer Healey, Jiuxiang Gu, Zhiqiang Xu, Changyou Chen:
TextLap: Customizing Language Models for Text-to-Layout Planning. CoRR abs/2410.12844 (2024) - [i86]Jian Chen, Ruiyi Zhang, Yufan Zhou, Tong Yu, Franck Dernoncourt, Jiuxiang Gu, Ryan A. Rossi, Changyou Chen, Tong Sun:
LoRA-Contextualizing Adaptation of Large Multimodal Models for Long Document Understanding. CoRR abs/2411.01106 (2024) - [i85]Shijie Zhou, Huaisheng Zhu, Rohan Sharma, Ruiyi Zhang, Kaiyi Ji, Changyou Chen:
Enhancing Diffusion Posterior Sampling for Inverse Problems by Integrating Crafted Measurements. CoRR abs/2411.09850 (2024) - 2023
- [j10]Yaman Kumar, Swapnil Parekh, Somesh Singh, Junyi Jessy Li, Rajiv Ratn Shah, Changyou Chen:
Automatic Essay Scoring Systems Are Both Overstable And Oversensitive: Explaining Why And Proposing Defenses. Dialogue Discourse 14(1): 1-33 (2023) - [c98]Yaman Kumar, Rajat Jha, Arunim Gupta, Milan Aggarwal, Aditya Garg, Tushar Malyan, Ayush Bhardwaj, Rajiv Ratn Shah, Balaji Krishnamurthy, Changyou Chen:
Persuasion Strategies in Advertisements. AAAI 2023: 57-66 - [c97]Ngoc Dang Nguyen, Wei Tan, Lan Du, Wray L. Buntine, Richard Beare, Changyou Chen:
AUC Maximization for Low-Resource Named Entity Recognition. AAAI 2023: 13389-13399 - [c96]Jianyi Zhang, Aashiq Muhamed, Aditya Anantharaman, Guoyin Wang, Changyou Chen, Kai Zhong, Qingjun Cui, Yi Xu, Belinda Zeng, Trishul Chilimbi, Yiran Chen:
ReAugKD: Retrieval-Augmented Knowledge Distillation For Pre-trained Language Models. ACL (2) 2023: 1128-1136 - [c95]Qian Jiang, Changyou Chen, Han Zhao, Liqun Chen, Qing Ping, Son Dinh Tran, Yi Xu, Belinda Zeng, Trishul Chilimbi:
Understanding and Constructing Latent Modality Structures in Multi-Modal Representation Learning. CVPR 2023: 7661-7671 - [c94]Yufan Zhou, Bingchen Liu, Yizhe Zhu, Xiao Yang, Changyou Chen, Jinhui Xu:
Shifted Diffusion for Text-to-image Generation. CVPR 2023: 10157-10166 - [c93]Aanisha Bhattacharyya, Yaman Singla, Balaji Krishnamurthy, Rajiv Ratn Shah, Changyou Chen:
A Video Is Worth 4096 Tokens: Verbalize Story Videos To Understand Them In Zero Shot. EMNLP 2023: 9822-9839 - [c92]Zihao He, Weituo Hao, Wei Tsung Lu, Changyou Chen, Kristina Lerman, Xuchen Song:
ALCAP: Alignment-Augmented Music Captioner. EMNLP 2023: 16501-16512 - [c91]Ngoc Dang Nguyen, Wei Tan, Lan Du, Wray L. Buntine, Richard Beare, Changyou Chen:
Low-Resource Named Entity Recognition: Can One-vs-All AUC Maximization Help? ICDM 2023: 1241-1246 - [c90]Wei Jiang, Jiayu Qin, Lingyu Wu, Changyou Chen, Tianbao Yang, Lijun Zhang:
Learning Unnormalized Statistical Models via Compositional Optimization. ICML 2023: 15105-15124 - [c89]Jianyi Zhang, Ang Li, Minxue Tang, Jingwei Sun, Xiang Chen, Fan Zhang, Changyou Chen, Yiran Chen, Hai Li:
Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction. ICML 2023: 41354-41381 - [c88]Jian Chen, Ruiyi Zhang, Tong Yu, Rohan Sharma, Zhiqiang Xu, Tong Sun, Changyou Chen:
Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels. NeurIPS 2023 - [i84]Qian Jiang, Changyou Chen, Han Zhao, Liqun Chen, Qing Ping, Son Dinh Tran, Yi Xu, Belinda Zeng, Trishul Chilimbi:
Understanding and Constructing Latent Modality Structures in Multi-modal Representation Learning. CoRR abs/2303.05952 (2023) - [i83]Jingchen Sun, Jiayu Qin, Zihao Lin, Changyou Chen:
Prompt Tuning based Adapter for Vision-Language Model Adaption. CoRR abs/2303.15234 (2023) - [i82]Aanisha Bhattacharya, Yaman Kumar Singla, Balaji Krishnamurthy, Rajiv Ratn Shah, Changyou Chen:
A Video Is Worth 4096 Tokens: Verbalize Story Videos To Understand Them In Zero Shot. CoRR abs/2305.09758 (2023) - [i81]Jian Chen, Ruiyi Zhang, Tong Yu, Rohan Sharma, Zhiqiang Xu, Tong Sun, Changyou Chen:
Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels. CoRR abs/2305.19518 (2023) - [i80]Wei Jiang, Jiayu Qin, Lingyu Wu, Changyou Chen, Tianbao Yang, Lijun Zhang:
Learning Unnormalized Statistical Models via Compositional Optimization. CoRR abs/2306.07485 (2023) - [i79]Ashmit Khandelwal, Aditya Agrawal, Aanisha Bhattacharyya, Yaman Kumar Singla, Somesh Singh, Uttaran Bhattacharya, Ishita Dasgupta, Stefano Petrangeli, Rajiv Ratn Shah, Changyou Chen, Balaji Krishnamurthy:
Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior. CoRR abs/2309.00359 (2023) - [i78]Harini S. I, Somesh Singh, Yaman Kumar Singla, Aanisha Bhattacharyya, Veeky Baths, Changyou Chen, Rajiv Ratn Shah, Balaji Krishnamurthy:
Long-Term Memorability On Advertisements. CoRR abs/2309.00378 (2023) - [i77]Ngoc Dang Nguyen, Wei Tan, Lan Du, Wray L. Buntine, Richard Beare, Changyou Chen:
Low-Resource Named Entity Recognition: Can One-vs-All AUC Maximization Help? CoRR abs/2311.04918 (2023) - [i76]Varun Khurana, Yaman Kumar Singla, Jayakumar Subramanian, Rajiv Ratn Shah, Changyou Chen, Zhiqiang Xu, Balaji Krishnamurthy:
Behavior Optimized Image Generation. CoRR abs/2311.10995 (2023) - 2022
- [j9]Yitong Yan, Chuangchuang Liu, Changyou Chen, Xianfang Sun, Longcun Jin, Xinyi Peng, Xiang Zhou:
Fine-Grained Attention and Feature-Sharing Generative Adversarial Networks for Single Image Super-Resolution. IEEE Trans. Multim. 24: 1473-1487 (2022) - [c87]Yufan Zhou, Ruiyi Zhang, Jiuxiang Gu, Chris Tensmeyer, Tong Yu, Changyou Chen, Jinhui Xu, Tong Sun:
TiGAN: Text-Based Interactive Image Generation and Manipulation. AAAI 2022: 3580-3588 - [c86]Yaman Kumar Singla, Swapnil Parekh, Somesh Singh, Changyou Chen, Balaji Krishnamurthy, Rajiv Ratn Shah:
MINIMAL: Mining Models for Universal Adversarial Triggers. AAAI 2022: 11330-11339 - [c85]Yaman Kumar Singla, Sriram Krishna, Rajiv Ratn Shah, Changyou Chen:
Using Sampling to Estimate and Improve Performance of Automated Scoring Systems with Guarantees. AAAI 2022: 12835-12843 - [c84]Yang Zhao, Yu-Chuan Su, Chun-Te Chu, Yandong Li, Marius Renn, Yukun Zhu, Changyou Chen, Xuhui Jia:
Rethinking Deep Face Restoration. CVPR 2022: 7642-7651 - [c83]Yufan Zhou, Ruiyi Zhang, Changyou Chen, Chunyuan Li, Chris Tensmeyer, Tong Yu, Jiuxiang Gu, Jinhui Xu, Tong Sun:
Towards Language-Free Training for Text-to-Image Generation. CVPR 2022: 17886-17896 - [c82]Ngoc Dang Nguyen, Lan Du, Wray L. Buntine, Changyou Chen, Richard Beare:
Hardness-guided domain adaptation to recognise biomedical named entities under low-resource scenarios. EMNLP 2022: 4063-4071 - [c81]Yaman Kumar Singla, Jui Shah, Changyou Chen, Rajiv Ratn Shah:
What Do Audio Transformers Hear? Probing Their Representations For Language Delivery & Structure. ICDM (Workshops) 2022: 910-925 - [c80]Ping Yu, Wei Wang, Chunyuan Li, Ruiyi Zhang, Zhanpeng Jin, Changyou Chen:
STT: Soft Template Tuning for Few-Shot Adaptation. ICDM (Workshops) 2022: 941-946 - [c79]Bekir Oguzhan Turkkan, Ting Dai, Adithya Raman, Tevfik Kosar, Changyou Chen, Muhammed Fatih Bulut, Jaroslaw Zola, Daby Sow:
GreenABR: energy-aware adaptive bitrate streaming with deep reinforcement learning. MMSys 2022: 150-163 - [c78]Changyou Chen, Jianyi Zhang, Yi Xu, Liqun Chen, Jiali Duan, Yiran Chen, Son Tran, Belinda Zeng, Trishul Chilimbi:
Why do We Need Large Batchsizes in Contrastive Learning? A Gradient-Bias Perspective. NeurIPS 2022 - [i75]Ping Yu, Wei Wang, Chunyuan Li, Ruiyi Zhang, Zhanpeng Jin, Changyou Chen:
STT: Soft Template Tuning for Few-Shot Adaptation. CoRR abs/2207.08408 (2022) - [i74]Yaman Kumar Singla, Rajat Jha, Arunim Gupta, Milan Aggarwal, Aditya Garg, Ayush Bhardwaj, Tushar Malyan, Balaji Krishnamurthy, Rajiv Ratn Shah, Changyou Chen:
Persuasion Strategies in Advertisements: Dataset, Modeling, and Baselines. CoRR abs/2208.09626 (2022) - [i73]Jianyi Zhang, Ang Li, Minxue Tang, Jingwei Sun, Xiang Chen, Fan Zhang, Changyou Chen, Yiran Chen, Hai Li:
Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction. CoRR abs/2209.15245 (2022) - [i72]Yufan Zhou, Chunyuan Li, Changyou Chen, Jianfeng Gao, Jinhui Xu:
Lafite2: Few-shot Text-to-Image Generation. CoRR abs/2210.14124 (2022) - [i71]Ngoc Dang Nguyen, Lan Du, Wray L. Buntine, Changyou Chen, Richard Beare:
Hardness-guided domain adaptation to recognise biomedical named entities under low-resource scenarios. CoRR abs/2211.05980 (2022) - [i70]Yufan Zhou, Bingchen Liu, Yizhe Zhu, Xiao Yang, Changyou Chen, Jinhui Xu:
Shifted Diffusion for Text-to-image Generation. CoRR abs/2211.15388 (2022) - [i69]Ngoc Dang Nguyen, Wei Tan, Wray L. Buntine, Richard Beare, Changyou Chen, Lan Du:
AUC Maximization for Low-Resource Named Entity Recognition. CoRR abs/2212.04800 (2022) - 2021
- [c77]Zijing Ou, Qinliang Su, Jianxing Yu, Bang Liu, Jingwen Wang, Ruihui Zhao, Changyou Chen, Yefeng Zheng:
Integrating Semantics and Neighborhood Information with Graph-Driven Generative Models for Document Retrieval. ACL/IJCNLP (1) 2021: 2238-2249 - [c76]Yaman Kumar Singla, Avyakt Gupta, Shaurya Bagga, Changyou Chen, Balaji Krishnamurthy, Rajiv Ratn Shah:
Speaker-Conditioned Hierarchical Modeling for Automated Speech Scoring. CIKM 2021: 1681-1691 - [c75]Yang Zhao, Chunyuan Li, Ping Yu, Changyou Chen:
ReMP: Rectified Metric Propagation for Few-Shot Learning. CVPR Workshops 2021: 2581-2590 - [c74]Weituo Hao, Mostafa El-Khamy, Jungwon Lee, Jianyi Zhang, Kevin J. Liang, Changyou Chen, Lawrence Carin:
Towards Fair Federated Learning With Zero-Shot Data Augmentation. CVPR Workshops 2021: 3310-3319 - [c73]Yang Zhao, Changyou Chen:
Unpaired Image-to-Image Translation via Latent Energy Transport. CVPR 2021: 16418-16427 - [c72]Ping Yu, Yang Zhao, Chunyuan Li, Changyou Chen:
Rethinking Sentiment Style Transfer. EMNLP (Findings) 2021: 1569-1582 - [c71]Aradhya Neeraj Mathur, Devansh Batra, Yaman Kumar Singla, Rajiv Ratn Shah, Changyou Chen, Roger Zimmermann:
LIFI: Towards Linguistically Informed Frame Interpolation. ICASSP 2021: 7593-7597 - [c70]Changyou Chen, Jiansheng Yang, Wen Shu, Peichi Tu:
Measurement of premixed propane combustion equivalence ratio based on flame image color and support vector machine. ICCDA 2021: 96-101 - [c69]Kevin J. Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin:
MixKD: Towards Efficient Distillation of Large-scale Language Models. ICLR 2021 - [c68]Yufan Zhou, Zhenyi Wang, Jiayi Xian, Changyou Chen, Jinhui Xu:
Meta-Learning with Neural Tangent Kernels. ICLR 2021 - [c67]Zexuan Qiu, Qinliang Su, Zijing Ou, Jianxing Yu, Changyou Chen:
Unsupervised Hashing with Contrastive Information Bottleneck. IJCAI 2021: 959-965 - [i68]Jui Shah, Yaman Kumar Singla, Changyou Chen, Rajiv Ratn Shah:
What all do audio transformer models hear? Probing Acoustic Representations for Language Delivery and its Structure. CoRR abs/2101.00387 (2021) - [i67]Le Fang, Tao Zeng, Chaochun Liu, Liefeng Bo, Wen Dong, Changyou Chen:
Outline to Story: Fine-grained Controllable Story Generation from Cascaded Events. CoRR abs/2101.00822 (2021) - [i66]Le Fang, Tao Zeng, Chaochun Liu, Liefeng Bo, Wen Dong, Changyou Chen:
Transformer-based Conditional Variational Autoencoder for Controllable Story Generation. CoRR abs/2101.00828 (2021) - [i65]Ping Yu, Ruiyi Zhang, Yang Zhao, Yizhe Zhang, Chunyuan Li, Changyou Chen:
SDA: Improving Text Generation with Self Data Augmentation. CoRR abs/2101.03236 (2021) - [i64]Yufan Zhou, Zhenyi Wang, Jiayi Xian, Changyou Chen, Jinhui Xu:
Meta-Learning with Neural Tangent Kernels. CoRR abs/2102.03909 (2021) - [i63]Weituo Hao, Mostafa El-Khamy, Jungwon Lee, Jianyi Zhang, Kevin J. Liang, Changyou Chen, Lawrence Carin:
Towards Fair Federated Learning with Zero-Shot Data Augmentation. CoRR abs/2104.13417 (2021) - [i62]Yufan Zhou, Changyou Chen, Jinhui Xu:
Learning High-Dimensional Distributions with Latent Neural Fokker-Planck Kernels. CoRR abs/2105.04538 (2021) - [i61]Zexuan Qiu, Qinliang Su, Zijing Ou, Jianxing Yu, Changyou Chen:
Unsupervised Hashing with Contrastive Information Bottleneck. CoRR abs/2105.06138 (2021) - [i60]Zijing Ou, Qinliang Su, Jianxing Yu, Bang Liu, Jingwen Wang, Ruihui Zhao, Changyou Chen, Yefeng Zheng:
Integrating Semantics and Neighborhood Information with Graph-Driven Generative Models for Document Retrieval. CoRR abs/2105.13066 (2021) - [i59]Yaman Kumar Singla, Avyakt Gupta, Shaurya Bagga, Changyou Chen, Balaji Krishnamurthy, Rajiv Ratn Shah:
Speaker-Conditioned Hierarchical Modeling for Automated Speech Scoring. CoRR abs/2109.00928 (2021) - [i58]Yaman Kumar Singla, Swapnil Parekh, Somesh Singh, Junyi Jessy Li, Rajiv Ratn Shah, Changyou Chen:
AES Systems Are Both Overstable And Oversensitive: Explaining Why And Proposing Defenses. CoRR abs/2109.11728 (2021) - [i57]Swapnil Parekh, Yaman Kumar Singla, Somesh Singh, Changyou Chen, Balaji Krishnamurthy, Rajiv Ratn Shah:
MINIMAL: Mining Models for Data Free Universal Adversarial Triggers. CoRR abs/2109.12406 (2021) - [i56]Anuj Saraswat, Mehar Bhatia, Yaman Kumar Singla, Changyou Chen, Rajiv Ratn Shah:
Perception Point: Identifying Critical Learning Periods in Speech for Bilingual Networks. CoRR abs/2110.06507 (2021) - [i55]Yaman Kumar Singla, Sriram Krishna, Rajiv Ratn Shah, Changyou Chen:
Using Sampling to Estimate and Improve Performance of Automated Scoring Systems with Guarantees. CoRR abs/2111.08906 (2021) - [i54]Yufan Zhou, Ruiyi Zhang, Changyou Chen, Chunyuan Li, Chris Tensmeyer, Tong Yu, Jiuxiang Gu, Jinhui Xu, Tong Sun:
LAFITE: Towards Language-Free Training for Text-to-Image Generation. CoRR abs/2111.13792 (2021) - [i53]Yufan Zhou, Chunyuan Li, Changyou Chen, Jinhui Xu:
A Generic Approach for Enhancing GANs by Regularized Latent Optimization. CoRR abs/2112.03502 (2021) - 2020
- [c66]Fan Yang, Alina Vereshchaka, Yufan Zhou, Changyou Chen, Wen Dong:
Variational Adversarial Kernel Learned Imitation Learning. AAAI 2020: 6599-6606 - [c65]Zhenyi Wang, Ping Yu, Yang Zhao, Ruiyi Zhang, Yufan Zhou, Junsong Yuan, Changyou Chen:
Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions. AAAI 2020: 12281-12288 - [c64]Lin Zheng, Qinliang Su, Dinghan Shen, Changyou Chen:
Generative Semantic Hashing Enhanced via Boltzmann Machines. ACL 2020: 777-788 - [c63]Zhenyi Wang, Xiaoyang Wang, Bang An, Dong Yu, Changyou Chen:
Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints. ACL 2020: 1072-1086 - [c62]Ruiyi Zhang, Changyou Chen, Zhe Gan, Wenlin Wang, Dinghan Shen, Guoyin Wang, Zheng Wen, Lawrence Carin:
Improving Adversarial Text Generation by Modeling the Distant Future. ACL 2020: 2516-2531 - [c61]Ruiyi Zhang, Changyou Chen, Zhe Gan, Zheng Wen, Wenlin Wang, Lawrence Carin:
Nested-Wasserstein Self-Imitation Learning for Sequence Generation. AISTATS 2020: 422-433 - [c60]Jianyi Zhang, Ruiyi Zhang, Lawrence Carin, Changyou Chen:
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory. AISTATS 2020: 1877-1887 - [c59]Qiuling Suo, Weida Zhong, Guangxu Xun, Jianhui Sun, Changyou Chen, Aidong Zhang:
GLIMA: Global and Local Time Series Imputation with Multi-directional Attention Learning. IEEE BigData 2020: 798-807 - [c58]Ping Yu, Yang Zhao, Chunyuan Li, Junsong Yuan, Changyou Chen:
Structure-Aware Human-Action Generation. ECCV (30) 2020: 18-34 - [c57]Ruiyi Zhang, Changyou Chen, Xinyuan Zhang, Ke Bai, Lawrence Carin:
Semantic Matching via Optimal Partial Transport. EMNLP (Findings) 2020: 212-222 - [c56]Bang An, Jie Lyu, Zhenyi Wang, Chunyuan Li, Changwei Hu, Fei Tan, Ruiyi Zhang, Yifan Hu, Changyou Chen:
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference. EMNLP (1) 2020: 236-255 - [c55]Zhenyi Wang, Yang Zhao, Ping Yu, Ruiyi Zhang, Changyou Chen:
Bayesian Meta Sampling for Fast Uncertainty Adaptation. ICLR 2020 - [c54]Ruqi Zhang, Chunyuan Li, Jianyi Zhang, Changyou Chen, Andrew Gordon Wilson:
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning. ICLR 2020 - [c53]Jianyi Zhang, Yang Zhao, Changyou Chen:
Variance Reduction in Stochastic Particle-Optimization Sampling. ICML 2020: 11307-11316 - [c52]Yang Zhao, Chunyuan Li, Ping Yu, Jianfeng Gao, Changyou Chen:
Feature Quantization Improves GAN Training. ICML 2020: 11376-11386 - [c51]Yufan Zhou, Zheshuo Li, Chunwei Ma, Changyou Chen, Mingchen Gao, Hong Zhu, Jinhui Xu:
Weakly-Supervised Brain Tumor Classification with Global Diagnosis Label. ISBI 2020: 1-5 - [c50]Fan Yang, Alina Vereshchaka, Changyou Chen, Wen Dong:
Bayesian Multi-type Mean Field Multi-agent Imitation Learning. NeurIPS 2020 - [c49]Yufan Zhou, Changyou Chen, Jinhui Xu:
Learning Manifold Implicitly via Explicit Heat-Kernel Learning. NeurIPS 2020 - [i52]Ruiyi Zhang, Changyou Chen, Zhe Gan, Zheng Wen, Wenlin Wang, Lawrence Carin:
Nested-Wasserstein Self-Imitation Learning for Sequence Generation. CoRR abs/2001.06944 (2020) - [i51]Yang Zhao, Chunyuan Li, Ping Yu, Jianfeng Gao, Changyou Chen:
Feature Quantization Improves GAN Training. CoRR abs/2004.02088 (2020) - [i50]Alexander Hanbo Li, Yaqing Wang, Changyou Chen, Jing Gao:
Decomposed Adversarial Learned Inference. CoRR abs/2004.10267 (2020) - [i49]Yang Zhao, Ping Yu, Suchismit Mahapatra, Qinliang Su, Changyou Chen:
Discretized Bottleneck in VAE: Posterior-Collapse-Free Sequence-to-Sequence Learning. CoRR abs/2004.10603 (2020) - [i48]Zhenyi Wang, Xiaoyang Wang, Bang An, Dong Yu, Changyou Chen:
Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints. CoRR abs/2005.00969 (2020) - [i47]Ruiyi Zhang, Changyou Chen, Zhe Gan, Wenlin Wang, Dinghan Shen, Guoyin Wang, Zheng Wen, Lawrence Carin:
Improving Adversarial Text Generation by Modeling the Distant Future. CoRR abs/2005.01279 (2020) - [i46]Ruiyi Zhang, Tong Yu, Yilin Shen, Hongxia Jin, Changyou Chen, Lawrence Carin:
Reward Constrained Interactive Recommendation with Natural Language Feedback. CoRR abs/2005.01618 (2020) - [i45]Tianhang Zheng, Sheng Liu, Changyou Chen, Junsong Yuan, Baochun Li, Kui Ren:
Towards Understanding the Adversarial Vulnerability of Skeleton-based Action Recognition. CoRR abs/2005.07151 (2020) - [i44]Yufan Zhou, Jiayi Xian, Changyou Chen, Jinhui Xu:
Graph Neural Networks with Composite Kernels. CoRR abs/2005.07869 (2020) - [i43]Lin Zheng, Qinliang Su, Dinghan Shen, Changyou Chen:
Generative Semantic Hashing Enhanced via Boltzmann Machines. CoRR abs/2006.08858 (2020) - [i42]Ping Yu, Yang Zhao, Chunyuan Li, Junsong Yuan, Changyou Chen:
Structure-Aware Human-Action Generation. CoRR abs/2007.01971 (2020) - [i41]Bang An, Jie Lyu, Zhenyi Wang, Chunyuan Li, Changwei Hu, Fei Tan, Ruiyi Zhang, Yifan Hu, Changyou Chen:
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference. CoRR abs/2009.09364 (2020) - [i40]Yufan Zhou, Changyou Chen, Jinhui Xu:
Learning Manifold Implicitly via Explicit Heat-Kernel Learning. CoRR abs/2010.01761 (2020) - [i39]Kevin J. Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin:
MixKD: Towards Efficient Distillation of Large-scale Language Models. CoRR abs/2011.00593 (2020) - [i38]Yang Zhao, Changyou Chen:
Unpaired Image-to-Image Translation via Latent Energy Transport. CoRR abs/2012.00649 (2020) - [i37]Yang Zhao, Chunyuan Li, Ping Yu, Changyou Chen:
ReMP: Rectified Metric Propagation for Few-Shot Learning. CoRR abs/2012.00904 (2020) - [i36]Swapnil Parekh, Yaman Kumar Singla, Changyou Chen, Junyi Jessy Li, Rajiv Ratn Shah:
My Teacher Thinks The World Is Flat! Interpreting Automatic Essay Scoring Mechanism. CoRR abs/2012.13872 (2020)
2010 – 2019
- 2019
- [j8]Chuangchuang Liu, Xianfang Sun, Changyou Chen, Paul L. Rosin, Yitong Yan, Longcun Jin, Xinyi Peng:
Multi-Scale Residual Hierarchical Dense Networks for Single Image Super-Resolution. IEEE Access 7: 60572-60583 (2019) - [j7]Changyou Chen, Wenlin Wang, Yizhe Zhang, Qinliang Su, Lawrence Carin:
A convergence analysis for a class of practical variance-reduction stochastic gradient MCMC. Sci. China Inf. Sci. 62(1): 12101:1-12101:13 (2019) - [c48]Tianhang Zheng, Changyou Chen, Kui Ren:
Distributionally Adversarial Attack. AAAI 2019: 2253-2260 - [c47]Chunyuan Li, Changyou Chen, Yunchen Pu, Ricardo Henao, Lawrence Carin:
Communication-Efficient Stochastic Gradient MCMC for Neural Networks. AAAI 2019: 4173-4180 - [c46]Yang Zhao, Jianyi Zhang, Changyou Chen:
Self-Adversarially Learned Bayesian Sampling. AAAI 2019: 5893-5900 - [c45]Ruiyi Zhang, Zheng Wen, Changyou Chen, Chen Fang, Tong Yu, Lawrence Carin:
Scalable Thompson Sampling via Optimal Transport. AISTATS 2019: 87-96 - [c44]Bai Li, Changyou Chen, Hao Liu, Lawrence Carin:
On Connecting Stochastic Gradient MCMC and Differential Privacy. AISTATS 2019: 557-566 - [c43]Chunyuan Li, Ke Bai, Jianqiao Li, Guoyin Wang, Changyou Chen, Lawrence Carin:
Adversarial Learning of a Sampler Based on an Unnormalized Distribution. AISTATS 2019: 3302-3311 - [c42]Le Fang, Chunyuan Li, Jianfeng Gao, Wen Dong, Changyou Chen:
Implicit Deep Latent Variable Models for Text Generation. EMNLP/IJCNLP (1) 2019: 3944-3954 - [c41]Wei Dong, Qinliang Su, Dinghan Shen, Changyou Chen:
Document Hashing with Mixture-Prior Generative Models. EMNLP/IJCNLP (1) 2019: 5225-5234 - [c40]Tianhang Zheng, Changyou Chen, Junsong Yuan, Bo Li, Kui Ren:
PointCloud Saliency Maps. ICCV 2019: 1598-1606 - [c39]Liqun Chen, Yizhe Zhang, Ruiyi Zhang, Chenyang Tao, Zhe Gan, Haichao Zhang, Bai Li, Dinghan Shen, Changyou Chen, Lawrence Carin:
Improving Sequence-to-Sequence Learning via Optimal Transport. ICLR (Poster) 2019 - [c38]Qi Wei, Kai Fan, Wenlin Wang, Tianhang Zheng, Amit Chakraborty, Katherine A. Heller, Changyou Chen, Kui Ren:
InverseNet: Solving Inverse Problems of Multimedia Data with Splitting Networks. ICME 2019: 1324-1329 - [c37]Di Wang, Changyou Chen, Jinhui Xu:
Differentially Private Empirical Risk Minimization with Non-convex Loss Functions. ICML 2019: 6526-6535 - [c36]Mengdi Huai, Hongfei Xue, Chenglin Miao, Liuyi Yao, Lu Su, Changyou Chen, Aidong Zhang:
Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm. IJCAI 2019: 2535-2541 - [c35]Jun Wen, Nenggan Zheng, Junsong Yuan, Zhefeng Gong, Changyou Chen:
Bayesian Uncertainty Matching for Unsupervised Domain Adaptation. IJCAI 2019: 3849-3855 - [c34]Wenlin Wang, Zhe Gan, Hongteng Xu, Ruiyi Zhang, Guoyin Wang, Dinghan Shen, Changyou Chen, Lawrence Carin:
Topic-Guided Variational Auto-Encoder for Text Generation. NAACL-HLT (1) 2019: 166-177 - [c33]Bai Li, Changyou Chen, Wenlin Wang, Lawrence Carin:
Certified Adversarial Robustness with Additive Noise. NeurIPS 2019: 9459-9469 - [c32]Ruiyi Zhang, Tong Yu, Yilin Shen, Hongxia Jin, Changyou Chen:
Text-Based Interactive Recommendation via Constraint-Augmented Reinforcement Learning. NeurIPS 2019: 15188-15198 - [i35]Chunyuan Li, Ke Bai, Jianqiao Li, Guoyin Wang, Changyou Chen, Lawrence Carin:
Adversarial Learning of a Sampler Based on an Unnormalized Distribution. CoRR abs/1901.00612 (2019) - [i34]Liqun Chen, Yizhe Zhang, Ruiyi Zhang, Chenyang Tao, Zhe Gan, Haichao Zhang, Bai Li, Dinghan Shen, Changyou Chen, Lawrence Carin:
Improving Sequence-to-Sequence Learning via Optimal Transport. CoRR abs/1901.06283 (2019) - [i33]Ruqi Zhang, Chunyuan Li, Jianyi Zhang, Changyou Chen, Andrew Gordon Wilson:
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning. CoRR abs/1902.03932 (2019) - [i32]Ruiyi Zhang, Zheng Wen, Changyou Chen, Lawrence Carin:
Scalable Thompson Sampling via Optimal Transport. CoRR abs/1902.07239 (2019) - [i31]Wenlin Wang, Zhe Gan, Hongteng Xu, Ruiyi Zhang, Guoyin Wang, Dinghan Shen, Changyou Chen, Lawrence Carin:
Topic-Guided Variational Autoencoders for Text Generation. CoRR abs/1903.07137 (2019) - [i30]Bai Li, Changyou Chen, Wenlin Wang, Lawrence Carin:
On Norm-Agnostic Robustness of Adversarial Training. CoRR abs/1905.06455 (2019) - [i29]Jun Wen, Nenggan Zheng, Junsong Yuan, Zhefeng Gong, Changyou Chen:
Bayesian Uncertainty Matching for Unsupervised Domain Adaptation. CoRR abs/1906.09693 (2019) - [i28]Wei Dong, Qinliang Su, Dinghan Shen, Changyou Chen:
Document Hashing with Mixture-Prior Generative Models. CoRR abs/1908.11078 (2019) - [i27]Le Fang, Chunyuan Li, Jianfeng Gao, Wen Dong, Changyou Chen:
Implicit Deep Latent Variable Models for Text Generation. CoRR abs/1908.11527 (2019) - [i26]Yitong Yan, Chuangchuang Liu, Changyou Chen, Xianfang Sun, Longcun Jin, Xiang Zhou:
Fine-grained Attention and Feature-sharing Generative Adversarial Networks for Single Image Super-Resolution. CoRR abs/1911.10773 (2019) - [i25]Yufan Zhou, Changyou Chen, Jinhui Xu:
KernelNet: A Data-Dependent Kernel Parameterization for Deep Generative Modeling. CoRR abs/1912.00979 (2019) - [i24]Zhenyi Wang, Ping Yu, Yang Zhao, Ruiyi Zhang, Yufan Zhou, Junsong Yuan, Changyou Chen:
Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions. CoRR abs/1912.10150 (2019) - 2018
- [c31]Wenlin Wang, Yunchen Pu, Vinay Kumar Verma, Kai Fan, Yizhe Zhang, Changyou Chen, Piyush Rai, Lawrence Carin:
Zero-Shot Learning via Class-Conditioned Deep Generative Models. AAAI 2018: 4211-4218 - [c30]Liqun Chen, Shuyang Dai, Yunchen Pu, Erjin Zhou, Chunyuan Li, Qinliang Su, Changyou Chen, Lawrence Carin:
Symmetric Variational Autoencoder and Connections to Adversarial Learning. AISTATS 2018: 661-669 - [c29]Ruiyi Zhang, Chunyuan Li, Changyou Chen, Lawrence Carin:
Learning Structural Weight Uncertainty for Sequential Decision-Making. AISTATS 2018: 1137-1146 - [c28]Changyou Chen, Chunyuan Li, Liquan Chen, Wenlin Wang, Yunchen Pu, Lawrence Carin:
Continuous-Time Flows for Efficient Inference and Density Estimation. ICML 2018: 823-832 - [c27]Ruiyi Zhang, Changyou Chen, Chunyuan Li, Lawrence Carin:
Policy Optimization as Wasserstein Gradient Flows. ICML 2018: 5741-5750 - [c26]Yifang Liu, Seyed Mahdi Shamsi, Le Fang, Changyou Chen, Nils Napp:
Deep Q-Learning for Dry Stacking Irregular Objects. IROS 2018: 1569-1576 - [c25]Yufan Zhou, Zheshuo Li, Hong Zhu, Changyou Chen, Mingchen Gao, Kai Xu, Jinhui Xu:
Holistic Brain Tumor Screening and Classification Based on DenseNet and Recurrent Neural Network. BrainLes@MICCAI (1) 2018: 208-217 - [c24]Changyou Chen, Ruiyi Zhang, Wenlin Wang, Bai Li, Liqun Chen:
A Unified Particle-Optimization Framework for Scalable Bayesian Sampling. UAI 2018: 746-755 - [i23]Ruiyi Zhang, Chunyuan Li, Changyou Chen, Lawrence Carin:
Learning Structural Weight Uncertainty for Sequential Decision-Making. CoRR abs/1801.00085 (2018) - [i22]Changyou Chen, Ruiyi Zhang, Wenlin Wang, Bai Li, Liqun Chen:
A Unified Particle-Optimization Framework for Scalable Bayesian Sampling. CoRR abs/1805.11659 (2018) - [i21]Ruiyi Zhang, Changyou Chen, Chunyuan Li, Lawrence Carin:
Policy Optimization as Wasserstein Gradient Flows. CoRR abs/1808.03030 (2018) - [i20]Tianhang Zheng, Changyou Chen, Kui Ren:
Distributionally Adversarial Attack. CoRR abs/1808.05537 (2018) - [i19]Jianyi Zhang, Ruiyi Zhang, Changyou Chen:
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory. CoRR abs/1809.01293 (2018) - [i18]Bai Li, Changyou Chen, Wenlin Wang, Lawrence Carin:
Second-Order Adversarial Attack and Certifiable Robustness. CoRR abs/1809.03113 (2018) - [i17]Ruiyi Zhang, Changyou Chen, Zhe Gan, Wenlin Wang, Liqun Chen, Dinghan Shen, Guoyin Wang, Lawrence Carin:
Sequence Generation with Guider Network. CoRR abs/1811.00696 (2018) - [i16]Jianyi Zhang, Yang Zhao, Changyou Chen:
Variance Reduction in Stochastic Particle-Optimization Sampling. CoRR abs/1811.08052 (2018) - [i15]Yang Zhao, Jianyi Zhang, Changyou Chen:
Self-Adversarially Learned Bayesian Sampling. CoRR abs/1811.08929 (2018) - [i14]Tianhang Zheng, Changyou Chen, Junsong Yuan, Kui Ren:
Learning Saliency Maps for Adversarial Point-Cloud Generation. CoRR abs/1812.01687 (2018) - 2017
- [c23]Zhe Gan, Chunyuan Li, Changyou Chen, Yunchen Pu, Qinliang Su, Lawrence Carin:
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling. ACL (1) 2017: 321-331 - [c22]Shengyang Sun, Changyou Chen, Lawrence Carin:
Learning Structured Weight Uncertainty in Bayesian Neural Networks. AISTATS 2017: 1283-1292 - [c21]Yizhe Zhang, Changyou Chen, Zhe Gan, Ricardo Henao, Lawrence Carin:
Stochastic Gradient Monomial Gamma Sampler. ICML 2017: 3996-4005 - [c20]Chunyuan Li, Hao Liu, Changyou Chen, Yunchen Pu, Liqun Chen, Ricardo Henao, Lawrence Carin:
ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching. NIPS 2017: 5495-5503 - [i13]Yizhe Zhang, Changyou Chen, Zhe Gan, Ricardo Henao, Lawrence Carin:
Stochastic Gradient Monomial Gamma Sampler. CoRR abs/1706.01498 (2017) - [i12]Chunyuan Li, Hao Liu, Changyou Chen, Yunchen Pu, Liqun Chen, Ricardo Henao, Lawrence Carin:
Towards Understanding Adversarial Learning for Joint Distribution Matching. CoRR abs/1709.01215 (2017) - [i11]Wenlin Wang, Yunchen Pu, Vinay Kumar Verma, Kai Fan, Yizhe Zhang, Changyou Chen, Piyush Rai, Lawrence Carin:
Zero-Shot Learning via Class-Conditioned Deep Generative Models. CoRR abs/1711.05820 (2017) - [i10]Bai Li, Changyou Chen, Hao Liu, Lawrence Carin:
On Connecting Stochastic Gradient MCMC and Differential Privacy. CoRR abs/1712.09097 (2017) - 2016
- [j6]Kar Wai Lim, Wray L. Buntine, Changyou Chen, Lan Du:
Nonparametric Bayesian topic modelling with the hierarchical Pitman-Yor processes. Int. J. Approx. Reason. 78: 172-191 (2016) - [c19]Chunyuan Li, Changyou Chen, David E. Carlson, Lawrence Carin:
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks. AAAI 2016: 1788-1794 - [c18]Chunyuan Li, Changyou Chen, Kai Fan, Lawrence Carin:
High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models. AAAI 2016: 1795-1801 - [c17]Changyou Chen, David E. Carlson, Zhe Gan, Chunyuan Li, Lawrence Carin:
Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization. AISTATS 2016: 1051-1060 - [c16]Chunyuan Li, Andrew Stevens, Changyou Chen, Yunchen Pu, Zhe Gan, Lawrence Carin:
Learning Weight Uncertainty with Stochastic Gradient MCMC for Shape Classification. CVPR 2016: 5666-5675 - [c15]Qinliang Su, Xuejun Liao, Changyou Chen, Lawrence Carin:
Nonlinear Statistical Learning with Truncated Gaussian Graphical Models. ICML 2016: 1948-1957 - [c14]Yizhe Zhang, Xiangyu Wang, Changyou Chen, Ricardo Henao, Kai Fan, Lawrence Carin:
Towards Unifying Hamiltonian Monte Carlo and Slice Sampling. NIPS 2016: 1741-1749 - [c13]Changyou Chen, Nan Ding, Chunyuan Li, Yizhe Zhang, Lawrence Carin:
Stochastic Gradient MCMC with Stale Gradients. NIPS 2016: 2937-2945 - [c12]Yizhe Zhang, Changyou Chen, Ricardo Henao, Lawrence Carin:
Laplacian Hamiltonian Monte Carlo. ECML/PKDD (1) 2016: 98-114 - [c11]Wenlin Wang, Changyou Chen, Wenlin Chen, Piyush Rai, Lawrence Carin:
Deep Metric Learning with Data Summarization. ECML/PKDD (1) 2016: 777-794 - [i9]Kar Wai Lim, Wray L. Buntine, Changyou Chen, Lan Du:
Nonparametric Bayesian Topic Modelling with the Hierarchical Pitman-Yor Processes. CoRR abs/1609.06783 (2016) - [i8]Kar Wai Lim, Changyou Chen, Wray L. Buntine:
Twitter-Network Topic Model: A Full Bayesian Treatment for Social Network and Text Modeling. CoRR abs/1609.06791 (2016) - [i7]Changyou Chen, Nan Ding, Chunyuan Li, Yizhe Zhang, Lawrence Carin:
Stochastic Gradient MCMC with Stale Gradients. CoRR abs/1610.06664 (2016) - [i6]Wenlin Wang, Changyou Chen, Wenqi Wang, Piyush Rai, Lawrence Carin:
Earliness-Aware Deep Convolutional Networks for Early Time Series Classification. CoRR abs/1611.04578 (2016) - [i5]Zhe Gan, Chunyuan Li, Changyou Chen, Yunchen Pu, Qinliang Su, Lawrence Carin:
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling. CoRR abs/1611.08034 (2016) - 2015
- [j5]Changyou Chen, Wray L. Buntine, Nan Ding, Lexing Xie, Lan Du:
Differential Topic Models. IEEE Trans. Pattern Anal. Mach. Intell. 37(2): 230-242 (2015) - [c10]Zhe Gan, Changyou Chen, Ricardo Henao, David E. Carlson, Lawrence Carin:
Scalable Deep Poisson Factor Analysis for Topic Modeling. ICML 2015: 1823-1832 - [c9]Changyou Chen, Nan Ding, Lawrence Carin:
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators. NIPS 2015: 2278-2286 - [c8]Changwei Hu, Piyush Rai, Changyou Chen, Matthew Harding, Lawrence Carin:
Scalable Bayesian Non-negative Tensor Factorization for Massive Count Data. ECML/PKDD (2) 2015: 53-70 - [i4]Changwei Hu, Piyush Rai, Changyou Chen, Matthew Harding, Lawrence Carin:
Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data. CoRR abs/1508.04211 (2015) - [i3]Changyou Chen, David E. Carlson, Zhe Gan, Chunyuan Li, Lawrence Carin:
Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization. CoRR abs/1512.07962 (2015) - 2014
- [c7]Changyou Chen, Jun Zhu, Xinhua Zhang:
Robust Bayesian Max-Margin Clustering. NIPS 2014: 532-540 - [c6]Nan Ding, Youhan Fang, Ryan Babbush, Changyou Chen, Robert D. Skeel, Hartmut Neven:
Bayesian Sampling Using Stochastic Gradient Thermostats. NIPS 2014: 3203-3211 - 2013
- [c5]Changyou Chen, Vinayak A. Rao, Wray L. Buntine, Yee Whye Teh:
Dependent Normalized Random Measures. ICML (3) 2013: 969-977 - 2012
- [j4]Lan Du, Wray L. Buntine, Huidong Jin, Changyou Chen:
Sequential latent Dirichlet allocation. Knowl. Inf. Syst. 31(3): 475-503 (2012) - [j3]Changyou Chen, Junping Zhang, Xuefang He, Zhi-Hua Zhou:
Non-Parametric Kernel Learning with robust pairwise constraints. Int. J. Mach. Learn. Cybern. 3(2): 83-96 (2012) - [c4]Changyou Chen, Nan Ding, Wray L. Buntine:
Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling. ICML 2012 - [i2]Changyou Chen, Wray L. Buntine, Nan Ding:
Theory of Dependent Hierarchical Normalized Random Measures. CoRR abs/1205.4159 (2012) - [i1]Changyou Chen, Nan Ding, Wray L. Buntine:
Dependent Hierarchical Normalized Random Measures for Dynamic Topic Modeling. CoRR abs/1206.4671 (2012) - 2011
- [c3]Changyou Chen, Lan Du, Wray L. Buntine:
Sampling Table Configurations for the Hierarchical Poisson-Dirichlet Process. ECML/PKDD (1) 2011: 296-311 - 2010
- [j2]Changyou Chen, Junping Zhang, Rudolf Fleischer:
Distance Approximating Dimension Reduction of Riemannian Manifolds. IEEE Trans. Syst. Man Cybern. Part B 40(1): 208-217 (2010) - [j1]Junping Zhang, Jian Pu, Changyou Chen, Rudolf Fleischer:
Low-Resolution Gait Recognition. IEEE Trans. Syst. Man Cybern. Part B 40(4): 986-996 (2010)
2000 – 2009
- 2009
- [c2]Changyou Chen, Junping Zhang, Rudolf Fleischer:
Multilinear Tensor-Based Non-parametric Dimension Reduction for Gait Recognition. ICB 2009: 1030-1039 - 2008
- [c1]Junping Zhang, Yuan Cheng, Changyou Chen:
Low Resolution Gait Recognition with High Frequency Super Resolution. PRICAI 2008: 533-543
Coauthor Index
[c74] [c69] [i63] [c62] [c61] [c60] [c57] [i52] [i47] [i46] [i39] [j7] [c47] [c45] [c44] [c43] [c39] [c34] [c33] [i35] [i34] [i32] [i31] [i30] [c31] [c30] [c29] [c28] [c27] [i23] [i21] [i18] [i17] [c23] [c22] [c21] [c20] [i13] [i12] [i11] [i10] [c19] [c18] [c17] [c16] [c15] [c14] [c13] [c12] [c11] [i7] [i6] [i5] [c10] [c9] [c8] [i4] [i3]
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