no code implementations • 15 Sep 2023 • Chao-Kai Chiang, Masashi Sugiyama
The analysis component of the framework, viewed as a decontamination process, provides a systematic method of conducting risk rewrite.
no code implementations • 28 Feb 2023 • Jongyeong Lee, Chao-Kai Chiang, Masashi Sugiyama
Although the uniform prior is shown to be optimal, we highlight the inherent limitation of its optimality, which is limited to specific parameterizations and emphasizes the significance of the invariance property of priors.
no code implementations • 3 Feb 2023 • Jongyeong Lee, Junya Honda, Chao-Kai Chiang, Masashi Sugiyama
In addition to the empirical performance, TS has been shown to achieve asymptotic problem-dependent lower bounds in several models.
no code implementations • 1 Feb 2019 • Zhiyun Lu, Chao-Kai Chiang, Fei Sha
We study a budgeted hyper-parameter tuning problem, where we optimize the tuning result under a hard resource constraint.
2 code implementations • NeurIPS 2017 • Virginia Smith, Chao-Kai Chiang, Maziar Sanjabi, Ameet Talwalkar
Federated learning poses new statistical and systems challenges in training machine learning models over distributed networks of devices.
no code implementations • 27 May 2016 • Peter Auer, Chao-Kai Chiang
We present an algorithm that achieves almost optimal pseudo-regret bounds against adversarial and stochastic bandits.