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09/07/2023
Mixtures of Gaussians are Privately Learnable with a Polynomial Number of Samples
We study the problem of estimating mixtures of Gaussians under the const...
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07/07/2023
The Power of Two-sided Recruitment in Two-sided Markets
We consider the problem of maximizing the gains from trade (GFT) in two-...
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03/07/2023
Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models
We study the problem of privately estimating the parameters of d-dimensi...
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02/16/2023
User Response in Ad Auctions: An MDP Formulation of Long-Term Revenue Optimization
We propose a new Markov Decision Process (MDP) model for ad auctions to ...
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07/08/2022
Efficiency of non-truthful auctions under auto-bidding
Auto-bidding is now widely adopted as an interface between advertisers a...
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06/01/2022
Continuous Prediction with Experts' Advice
Prediction with experts' advice is one of the most fundamental problems ...
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11/22/2021
Private and polynomial time algorithms for learning Gaussians and beyond
We present a fairly general framework for reducing (ε, δ) differentially...
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06/03/2021
Privately Learning Mixtures of Axis-Aligned Gaussians
We consider the problem of learning mixtures of Gaussians under the cons...
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09/14/2020
Convergence Analysis of No-Regret Bidding Algorithms in Repeated Auctions
The connection between games and no-regret algorithms has been widely st...
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02/20/2020
Optimal anytime regret with two experts
The multiplicative weights method is an algorithm for the problem of pre...
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09/02/2019
Simple and optimal high-probability bounds for strongly-convex stochastic gradient descent
We consider stochastic gradient descent algorithms for minimizing a non-...
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05/09/2019
The Vickrey Auction with a Single Duplicate Bidder Approximates the Optimal Revenue
Bulow and Klemperer's well-known result states that, in a single-item au...
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12/13/2018
Tight Analyses for Non-Smooth Stochastic Gradient Descent
Consider the problem of minimizing functions that are Lipschitz and stro...
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06/17/2018
Greedy and Local Ratio Algorithms in the MapReduce Model
MapReduce has become the de facto standard model for designing distribut...
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06/29/2017
