4 papers
Posterior Tempering Explains Variance Inflation in Linear and Generalized Linear Thompson Sampling
Prateek Jaiswal, Debdeep Pati, Anirban Bhattacharya +1
We study a variant of the Thompson Sampling (TS) algorithm, called -TS, for solving stochastic generalized linear bandit problems. Existing analyses of TS require inflating the…
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…
Deconfounded Warm-Start Thompson Sampling with Applications to Precision Medicine
Prateek Jaiswal, Esmaeil Keyvanshokooh, Junyu Cao
Randomized clinical trials often require large patient cohorts before drawing definitive conclusions, yet abundant observational data from parallel studies remains underutilized du…
Leveraging Offline Data from Similar Systems for Online Linear Quadratic Control
Shivam Bajaj, Prateek Jaiswal, Vijay Gupta
``Sim2real gap", in which the system learned in simulations is not the exact representation of the real system, can lead to loss of stability and performance when controllers learn…