Abstract. We formulate the multiperiod, distribution-free perishable inventory problem as a problem of prediction with expert advice and apply an online learning method (the Weak A...
Tatsiana Levina, Yuri Levin, Jeff McGill, Mikhail ...
A new algorithm for performing classification with imperfectly labeled data is presented. The proposed approach is motivated by the insight that the average prediction of a group ...
Mixture-of-Experts (MoE) systems solve intricate problems by combining results generated independently by multiple computational models (the “experts”). Given an instance of a...
Abstract. In this paper we derive an upper bound for the average-case generalization error of the mixture of experts modular neural network, based on an average-case generalization...
Abstract. We study online regret minimization algorithms in a bicriteria setting, examining not only the standard notion of regret to the best expert, but also the regret to the av...
Eyal Even-Dar, Michael J. Kearns, Yishay Mansour, ...