Online Learning via Offline Greedy Algorithms : Applications in Market Design…

Motivated by online decision making in time-varying combinatorial environments, we study the problem of transforming offline algorithms to their online counterparts. We focus on offline combinatori…

Contextual Bandits with Cross-Learning

In the classic contextual bandits problem, in each round t, a learner observes some context c, chooses some action i to perform, and receives some reward ri,t(c) . We consider the variant of this …

Product Ranking on Online Platforms

On online platforms, consumers face an abundance of options that are displayed in the form of a position ranking. Only products placed in the first few positions are readily accessible to the consu…

Linear Program-Based Approximation for Personalized Reserve Prices

We study the problem of computing data-driven personalized reserve prices in eager second price auctions without having any assumption on valuation distributions. Here, the input is a data set that…

Improved Revenue Bounds for Posted-Price and Second-Price Mechanisms

We study revenue maximization through sequential posted-price (SPP) mechanisms in single-dimensional settings with n buyers and independent but not necessarily identical value distributions. We con…

Dynamic Incentive-Aware Learning : Robust Pricing in Contextual Auctions

Motivated by pricing in ad exchange markets, we consider the problem of robust learning of reserve prices against strategic buyers in repeated contextual second-price auctions. Buyers’ valuations…

Auctions with Dynamic Costly Information Acquisition

Real-Time Optimization of Personalized Assortments

Femtocaching and Device-to-Device Collaboration: A New Architecture for Wirel…