We study the problem of estimating mixtures of Gaussians under the const...
We consider the problem of maximizing the gains from trade (GFT) in two-...
We study the problem of privately estimating the parameters of
d-dimensi...
We propose a new Markov Decision Process (MDP) model for ad auctions to
...
Auto-bidding is now widely adopted as an interface between advertisers a...
Prediction with experts' advice is one of the most fundamental problems ...
We present a fairly general framework for reducing (ε, δ)
differentially...
We consider the problem of learning mixtures of Gaussians under the
cons...
The connection between games and no-regret algorithms has been widely st...
The multiplicative weights method is an algorithm for the problem of
pre...
We consider stochastic gradient descent algorithms for minimizing a
non-...
Bulow and Klemperer's well-known result states that, in a single-item au...
Consider the problem of minimizing functions that are Lipschitz and stro...
MapReduce has become the de facto standard model for designing distribut...
The shifting strategy, introduced by Hochbaum and Maass, and independent...