4 papers · 1 filter
Adaptive Resolution for Finite-Rank Gaussian Processes
Jaehoan Kim, Anirban Bhattacharya, Debdeep Pati
Finite-rank approximations are widely used to scale Gaussian process (GP) regression, but their posterior behavior can differ from that of the corresponding parent GP prior. We stu…
Frequentist Regret Analysis of Gaussian Process Thompson Sampling via Fractional Posteriors
Somjit Roy, Prateek Jaiswal, Anirban Bhattacharya +2
We study Gaussian Process Thompson Sampling (GP-TS) for sequential decision-making over compact, continuous action spaces and provide a frequentist regret analysis based on fractio…
Adaptive Divide and Conquer with Two Rounds of Communication
Niladri Kal, Botond Szabó, Rajarshi Guhaniyogi +2
We introduce a two-round adaptive communication strategy that enables rate-optimal estimation in the white noise model without requiring prior knowledge of the underlying smoothnes…
Tail-adaptive Bayesian shrinkage
Se Yoon Lee, Peng Zhao, Debdeep Pati +1
Robust Bayesian methods for high-dimensional regression problems under diverse sparse regimes are studied. Traditional shrinkage priors are primarily designed to detect a handful o…