Chao-Kai Chiang

23 papers A* 8A 2C 1Journal 10Unranked 2
YearRankTypeTitle / Venue / Authors
2025 A conf
Domain Adaptation and Entanglement: an Optimal Transport Perspective.
AISTATS
Okan Koc, Alexander Soen, Chao-Kai Chiang, Masashi Sugiyama
2025 J jnl
Domain Adaptation and Entanglement: an Optimal Transport Perspective.
CoRR
Okan Koc, Alexander Soen, Chao-Kai Chiang, Masashi Sugiyama
2025 J jnl
LLM Routing with Dueling Feedback.
CoRR
Chao-Kai Chiang, Takashi Ishida, Masashi Sugiyama
2025 J jnl
Unified Risk Analysis for Weakly Supervised Learning.
Trans. Mach. Learn. Res.
Chao-Kai Chiang, Masashi Sugiyama
2024 A* conf
The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models.
AAAI
Jongyeong Lee, Chao-Kai Chiang, Masashi Sugiyama
2023 J jnl
Asymptotically Optimal Thompson Sampling Based Policy for the Uniform Bandits and the Gaussian Bandits.
CoRR
Jongyeong Lee, Chao-Kai Chiang, Masashi Sugiyama
2023 A* conf
Imitation Learning from Vague Feedback.
NeurIPS
Xin-Qiang Cai, Yu-Jie Zhang, Chao-Kai Chiang, Masashi Sugiyama
2023 A* conf
Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits.
ICML
Jongyeong Lee, Junya Honda, Chao-Kai Chiang, Masashi Sugiyama
2023 J jnl
Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits.
CoRR
Jongyeong Lee, Junya Honda, Chao-Kai Chiang, Masashi Sugiyama
2023 J jnl
Unified Risk Analysis for Weakly Supervised Learning.
CoRR
Chao-Kai Chiang, Masashi Sugiyama
2019 A* conf
Hyper-parameter Tuning under a Budget Constraint.
IJCAI
Zhiyun Lu, Liyu Chen, Chao-Kai Chiang, Fei Sha
2019 J jnl
Hyper-parameter Tuning under a Budget Constraint.
CoRR
Zhiyun Lu, Chao-Kai Chiang, Fei Sha
2017 — conf
Federated Multi-Task Learning.
NIPS
Virginia Smith, Chao-Kai Chiang, Maziar Sanjabi, Ameet Talwalkar
2017 J jnl
Federated Multi-Task Learning.
CoRR
Virginia Smith, Chao-Kai Chiang, Maziar Sanjabi, Ameet Talwalkar
2017 J jnl
Online Learning Problems against Dynamic Strategies in Gradually Evolving Worlds.
J. Inf. Hiding Multim. Signal Process.
Chia-Jung Lee, Chao-Kai Chiang, Mu-En Wu
2016 A* conf
An algorithm with nearly optimal pseudo-regret for both stochastic and adversarial bandits.
COLT
Peter Auer, Chao-Kai Chiang
2016 J jnl
An algorithm with nearly optimal pseudo-regret for both stochastic and adversarial bandits.
CoRR
Peter Auer, Chao-Kai Chiang
2016 A conf
Pareto Front Identification from Stochastic Bandit Feedback.
AISTATS
Peter Auer, Chao-Kai Chiang, Ronald Ortner, Madalina M. Drugan
2015 — conf
Resisting Dynamic Strategies in Gradually Evolving Worlds.
RVSP
Chia-Jung Lee, Chao-Kai Chiang, Mu-En Wu
2014 C conf
Pseudo-reward Algorithms for Contextual Bandits with Linear Payoff Functions.
ACML
Ku-Chun Chou, Hsuan-Tien Lin, Chao-Kai Chiang, Chi-Jen Lu
2013 A* conf
Beating Bandits in Gradually Evolving Worlds.
COLT
Chao-Kai Chiang, Chia-Jung Lee, Chi-Jen Lu
2012 A* conf
Online Optimization with Gradual Variations.
COLT
Chao-Kai Chiang, Tianbao Yang, Chia-Jung Lee, Mehrdad Mahdavi, Chi-Jen Lu, Rong Jin, Shenghuo Zhu
2010 A* conf
Online Learning with Queries.
SODA
Chao-Kai Chiang, Chi-Jen Lu