Chao-Kai Chiang

According to our database, Chao-Kai Chiang authored at least 16 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models.

Jongyeong Lee, Chao-Kai Chiang, Masashi Sugiyama

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Unified Risk Analysis for Weakly Supervised Learning.

Chao-Kai Chiang, Masashi Sugiyama

CoRR, 2023

Asymptotically Optimal Thompson Sampling Based Policy for the Uniform Bandits and the Gaussian Bandits.

Jongyeong Lee, Chao-Kai Chiang, Masashi Sugiyama

CoRR, 2023

Imitation Learning from Vague Feedback.

Xin-Qiang Cai, Yu-Jie Zhang, Chao-Kai Chiang, Masashi Sugiyama

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits.

Jongyeong Lee, Junya Honda, Chao-Kai Chiang, Masashi Sugiyama

Proceedings of the International Conference on Machine Learning, 2023

2019

Hyper-parameter Tuning under a Budget Constraint.

Zhiyun Lu, Chao-Kai Chiang, Fei Sha

CoRR, 2019

Hyper-parameter Tuning under a Budget Constraint.

Zhiyun Lu, Liyu Chen, Chao-Kai Chiang, Fei Sha

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2017

Online Learning Problems against Dynamic Strategies in Gradually Evolving Worlds.

Chia-Jung Lee, Chao-Kai Chiang, Mu-En Wu

J. Inf. Hiding Multim. Signal Process., 2017

Federated Multi-Task Learning.

Virginia Smith, Chao-Kai Chiang, Maziar Sanjabi, Ameet Talwalkar

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

An algorithm with nearly optimal pseudo-regret for both stochastic and adversarial bandits.

Peter Auer, Chao-Kai Chiang

Proceedings of the 29th Conference on Learning Theory, 2016

Pareto Front Identification from Stochastic Bandit Feedback.

Peter Auer, Chao-Kai Chiang, Ronald Ortner, Madalina M. Drugan

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Resisting Dynamic Strategies in Gradually Evolving Worlds.

Chia-Jung Lee, Chao-Kai Chiang, Mu-En Wu

Proceedings of the Third International Conference on Robot, Vision and Signal Processing, 2015

2014

Pseudo-reward Algorithms for Contextual Bandits with Linear Payoff Functions.

Ku-Chun Chou, Hsuan-Tien Lin, Chao-Kai Chiang, Chi-Jen Lu

Proceedings of the Sixth Asian Conference on Machine Learning, 2014

2013

Beating Bandits in Gradually Evolving Worlds.

Chao-Kai Chiang, Chia-Jung Lee, Chi-Jen Lu

Proceedings of the COLT 2013, 2013

2012

Online Optimization with Gradual Variations.

Chao-Kai Chiang, Tianbao Yang, Chia-Jung Lee, Mehrdad Mahdavi, Chi-Jen Lu, Rong Jin, Shenghuo Zhu

Proceedings of the COLT 2012, 2012

2010

Online Learning with Queries.

Chao-Kai Chiang, Chi-Jen Lu

Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms, 2010