21 citations · 33 across the 4 of their papers we have counts for
4 papers
Optimal anytime regret with two experts
Nicholas J. A. Harvey, Christopher Liaw, Edwin Perkins +1
We consider the classical problem of prediction with expert advice. In the fixed-time setting, where the time horizon is known in advance, algorithms that achieve the optimal regre…
Simple and optimal high-probability bounds for strongly-convex stochastic gradient descent
Nicholas J. A. Harvey, Christopher Liaw, Sikander Randhawa
We consider stochastic gradient descent algorithms for minimizing a non-smooth, strongly-convex function. Several forms of this algorithm, including suffix averaging, are known to…
The Vickrey Auction with a Single Duplicate Bidder Approximates the Optimal Revenue
Hu Fu, Christopher Liaw, Sikander Randhawa
Bulow and Klemperer's well-known result states that, in a single-item auction where the bidders' values are independently and identically drawn from a regular distribution, the…
Tight Analyses for Non-Smooth Stochastic Gradient Descent
Nicholas J. A. Harvey, Christopher Liaw, Yaniv Plan +1
Consider the problem of minimizing functions that are Lipschitz and strongly convex, but not necessarily differentiable. We prove that after steps of stochastic gradient descen…