In spite of the great progress in the data mining field in recent years, the problem of missing and uncertain data has remained a great challenge for data mining algorithms. Many ...
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
Many interesting problems, such as power grids, network switches, and tra c ow, that are candidates for solving with reinforcement learningRL, alsohave properties that make distri...
Jeff G. Schneider, Weng-Keen Wong, Andrew W. Moore...
Contextual search refers to proactively capturing the information need of a user by automatically augmenting the user query with information extracted from the search context; for...
We describe a simple randomized construction for generating pairs of hash functions h1, h2 from a universe U to ranges V = [m] = {0, 1, . . . , m - 1} and W = [m] so that for ever...