Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
The authors developed an extensible system for video exploitation that puts the user in control to better accommodate novel situations and source material. Visually dense displays...
Ming-yu Chen, Michael G. Christel, Alexander G. Ha...
Learning the user’s semantics for CBIR involves two different sources of information: the similarity relations entailed by the content-based features, and the relevance relatio...
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Technical support procedures are typically very complex. Users often have trouble following printed instructions describing how to perform these procedures, and these instructions...
Tessa A. Lau, Lawrence D. Bergman, Vittorio Castel...