Nibedita Roy

collaborators

2 papers

stat.ML2026

Tight Convergence Rates for Online Distributed Linear Estimation with Adversarial Measurements

Nibedita Roy, Vishal Halder, Gugan Thoppe +4

We study mean estimation of a random vector $X$ in a distributed parameter-server-worker setup. Worker $i$ observes samples of $a_{i}^{⊤} X$ , where $a_{i}^{⊤}$ is the $i$ th row of a…

cs.LG2024

Reinforcement Learning with Quasi-Hyperbolic Discounting

S. R. Eshwar, Mayank Motwani, Nibedita Roy +1

Reinforcement learning has traditionally been studied with exponential discounting or the average reward setup, mainly due to their mathematical tractability. However, such framewo…