Regularization plays a central role in the analysis of modern data, where non-regularized fitting is likely to lead to over-fitted models, useless for both prediction and interpre...
Designing the dialogue strategy of a spoken dialogue system involves many nontrivial choices. This paper presents a reinforcement learning approach for automatically optimizing di...
Diane J. Litman, Michael S. Kearns, Satinder P. Si...
In this paper, we present an approach for measuring certain properties of synthetic optimization problems based on the assumed distribution of coefficient values. We show how to e...
One of the most important open problems of parallel LTL model-checking is to design an on-the-fly scalable parallel algorithm with linear time complexity. Such an algorithm would g...
We consider the problem of designing a revenue-maximizing auction for a single item, when the values of the bidders are drawn from a correlated distribution. We observe that there...