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 ...
Abstract. Service and process-oriented systems promise to provide more effective business and work processes and more flexible and adaptable enterprise IT systems. However, the t...
Abstract. One of the key challenges faced when developing contextaware pervasive systems is to capture the set of inputs that we want a system to adapt to. Arbitrarily specifying r...
Adrian K. Clear, Ross Shannon, Thomas Holland, Aar...
Recommender systems are gaining widespread acceptance in e-commerce applications to confront the “information overload” problem. Collaborative Filtering (CF) is a successful re...
Traditional techniques for building dependable, highperformance distributed systems are too expensive for most non-critical systems, often causing dependability to be sidelined as...
Vikram S. Adve, Adnan Agbaria, Matti A. Hiltunen, ...