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cs.LG2025
Why Most Optimism Bandit Algorithms Have the Same Regret Analysis: A Simple Unifying Theorem
Vikram Krishnamurthy
Several optimism-based stochastic bandit algorithms -- including UCB, UCB-V, linear UCB, and finite-arm GP-UCB -- achieve logarithmic regret using proofs that, despite superficial…
cs.LG2025
Inverse Reinforcement Learning using Revealed Preferences and Passive Stochastic Optimization
Vikram Krishnamurthy
This monograph, spanning three chapters, explores Inverse Reinforcement Learning (IRL). The first two chapters view inverse reinforcement learning (IRL) through the lens of reveale…
cs.LG2025
Efficient Neural SDE Training using Wiener-Space Cubature
Luke Snow, Vikram Krishnamurthy
A neural stochastic differential equation (SDE) is an SDE with drift and diffusion terms parametrized by neural networks. The training procedure for neural SDEs consists of optimiz…