Ke Bai

According to our database, Ke Bai authored at least 18 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Multiscale Visual-Attribute Co-Attention for Zero-Shot Image Recognition.

Hao Zhang, Long Tian, Zhengjue Wang, Yishi Xu, Pengyu Cheng, Ke Bai, Bo Chen

IEEE Trans. Neural Networks Learn. Syst., September, 2023

Learning in the Open World: Techniques for Identifying and Adapting to the Unknown.

Ke Bai

PhD thesis, 2023

Everyone Deserves A Reward: Learning Customized Human Preferences.

Pengyu Cheng, Jiawen Xie, Ke Bai, Yong Dai, Nan Du

CoRR, 2023

OssCSE: Overcoming Surface Structure Bias in Contrastive Learning for Unsupervised Sentence Embedding.

Zhan Shi, Guoyin Wang, Ke Bai, Jiwei Li, Xiang Li, Qingjun Cui, Belinda Zeng, Trishul Chilimbi, Xiaodan Zhu

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Estimating Total Correlation with Mutual Information Estimators.

Ke Bai, Pengyu Cheng, Weituo Hao, Ricardo Henao, Larry Carin

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Collaborative Anomaly Detection.

Ke Bai, Aonan Zhang, Zhizhong Li, Ricardo Henao, Chong Wang, Lawrence Carin

CoRR, 2022

Learning to Weight Filter Groups for Robust Classification.

Siyang Yuan, Yitong Li, Dong Wang, Ke Bai, Lawrence Carin, David E. Carlson

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Open World Classification with Adaptive Negative Samples.

Ke Bai, Guoyin Wang, Jiwei Li, Sunghyun Park, Sungjin Lee, Puyang Xu, Ricardo Henao, Lawrence Carin

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021

Variational Inference with Holder Bounds.

Junya Chen, Danni Lu, Zidi Xiu, Ke Bai, Lawrence Carin, Chenyang Tao

CoRR, 2021

2020

Weakly supervised cross-domain alignment with optimal transport.

Siyang Yuan, Ke Bai, Liqun Chen, Yizhe Zhang, Chenyang Tao, Chunyuan Li, Guoyin Wang, Ricardo Henao, Lawrence Carin

CoRR, 2020

Regularizing Reasons for Outfit Evaluation with Gradient Penalty.

Xingxing Zou, Zhizhong Li, Ke Bai, Dahua Lin, Waikeung Wong

CoRR, 2020

Semantic Matching via Optimal Partial Transport.

Ruiyi Zhang, Changyou Chen, Xinyuan Zhang, Ke Bai, Lawrence Carin

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Advancing weakly supervised cross-domain alignment with optimal transport.

Siyang Yuan, Ke Bai, Liqun Chen, Yizhe Zhang, Chenyang Tao, Chunyuan Li, Guoyin Wang, Ricardo Henao, Lawrence Carin

Proceedings of the 31st British Machine Vision Conference 2020, 2020

Sequence Generation with Optimal-Transport-Enhanced Reinforcement Learning.

Liqun Chen, Ke Bai, Chenyang Tao, Yizhe Zhang, Guoyin Wang, Wenlin Wang, Ricardo Henao, Lawrence Carin

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

On Fenchel Mini-Max Learning.

Chenyang Tao, Liqun Chen, Shuyang Dai, Junya Chen, Ke Bai, Dong Wang, Jianfeng Feng, Wenlian Lu, Georgiy V. Bobashev, Lawrence Carin

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Variational Annealing of GANs: A Langevin Perspective.

Chenyang Tao, Shuyang Dai, Liqun Chen, Ke Bai, Junya Chen, Chang Liu, Ruiyi Zhang, Georgiy V. Bobashev, Lawrence Carin

Proceedings of the 36th International Conference on Machine Learning, 2019

GO Gradient for Expectation-Based Objectives.

Yulai Cong, Miaoyun Zhao, Ke Bai, Lawrence Carin

Proceedings of the 7th International Conference on Learning Representations, 2019

Adversarial Learning of a Sampler Based on an Unnormalized Distribution.

Chunyuan Li, Ke Bai, Jianqiao Li, Guoyin Wang, Changyou Chen, Lawrence Carin

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019