We initiate the study of incentives in a general machine learning framework. We focus on a game-theoretic regression learning setting where private information is elicited from mu...
We present the design and analysis of an approximately incentive-compatible combinatorial auction. In just a single run, the auction is able to extract enough value information fr...
We study the Cost-Per-Action or Cost-Per-Acquisition (CPA) charging scheme in online advertising. In this scheme, instead of paying per click, the advertisers pay only when a user...
In pay-per click sponsored search auctions which are cur-
rently extensively used by search engines, the auction for
a keyword involves a certain number of advertisers (say k)
c...
This paper investigates a novel model-free reinforcement learning architecture, the Natural Actor-Critic. The actor updates are based on stochastic policy gradients employing Amari...