Markov Decision Problems, MDPs offer an effective mechanism for planning under uncertainty. However, due to unavoidable uncertainty over models, it is difficult to obtain an exac...
We study a game with strategic vendors (the agents) who own multiple items and a single buyer with a submodular valuation function. The goal of the vendors is to maximize their re...
Omer Lev, Joel Oren, Craig Boutilier, Jeffrey S. R...
Learning probabilistic predictive models that are well calibrated is critical for many prediction and decision-making tasks in artificial intelligence. In this paper we present a...
Mahdi Pakdaman Naeini, Gregory F. Cooper, Milos Ha...
We present an intuitive explanation for the limited effectiveness of front-to-end bidirectional heuristic search, supported with extensive evidence from many commonly-studied doma...
Ensemble learning is among the state-of-the-art learning techniques, which trains and combines many base learners. Ensemble pruning removes some of the base learners of an ensembl...