8 citations · 21 across the 17 of their papers we have counts for
12 papers · 1 filter
Learning Kernel-Based MDPs from Episodic Preferential Feedback
Nikola Pavlovic, Sattar Vakili, Qing Zhao
Human feedback often arrives as preferences rather than calibrated numeric rewards, motivating reinforcement learning from preferential feedback, also referred to as reinforcement…
Adversarial Contextual Bandits Go Kernelized
Gergely Neu, Julia Olkhovskaya, Sattar Vakili
We study a generalization of the problem of online learning in adversarial linear contextual bandits by incorporating loss functions that belong to a reproducing kernel Hilbert spa…
Open Problem: Tight Online Confidence Intervals for RKHS Elements
Sattar Vakili, Jonathan Scarlett, Tara Javidi
Confidence intervals are a crucial building block in the analysis of various online learning problems. The analysis of kernel based bandit and reinforcement learning problems utili…
Optimal Order Simple Regret for Gaussian Process Bandits
Sattar Vakili, Nacime Bouziani, Sepehr Jalali +2
Consider the sequential optimization of a continuous, possibly non-convex, and expensive to evaluate objective function . The problem can be cast as a Gaussian Process (GP) band…
A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret Performance
Sudeep Salgia, Sattar Vakili, Qing Zhao
We consider sequential optimization of an unknown function in a reproducing kernel Hilbert space. We propose a Gaussian process-based algorithm and establish its order-optimal regr…
On Information Gain and Regret Bounds in Gaussian Process Bandits
Sattar Vakili, Kia Khezeli, Victor Picheny
Consider the sequential optimization of an expensive to evaluate and possibly non-convex objective function from noisy feedback, that can be considered as a continuum-armed ban…