2017
Online Learning of Optimal Bidding Strategy in Repeated Multi-Commodity Auctions
NeurIPS 2017poster
We study the online learning problem of a bidder who participates in repeated auctions. With the goal of maximizing his T-period payoff, the bidder determines the optimal allocation of his budget among his bids for $K$ goods at each period. As a bidding strategy, we propose a polynomial-time algorit…