8 citations · 21 across the 6 of their papers we have counts for
13 papers
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…
Uniform Generalization Bounds for Overparameterized Neural Networks
Sattar Vakili, Michael Bromberg, Jezabel Garcia +2
An interesting observation in artificial neural networks is their favorable generalization error despite typically being extremely overparameterized. It is well known that the clas…
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…
Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization
Sudeep Salgia, Qing Zhao, Sattar Vakili
A framework based on iterative coordinate minimization (CM) is developed for stochastic convex optimization. Given that exact coordinate minimization is impossible due to the unkno…