Contextual bandit learning is a reinforcement learning problem where the learner repeatedly receives a set of features (context), takes an action and receives a reward based on th...
We report on the effectiveness of language models for personalization of retrieval results based on a searcher’s preference for document genre. In principle, such preferences ca...
Gheorghe Muresan, Catherine L. Smith, Michael Cole...
We provide an answer to an open question, posed by van Glabbeek [4], regarding the axiomatizability of ready trace semantics. We prove that if the alphabet of actions is finite, t...
Abstract. Agents situated in proactive environments are acting autonomously while the environment is evolving alongside, whether or not the agents carry out any particular actions....
We present a knowledge and context-based system for parsing and translating natural language and evaluate it on sentences from the Wall Street Journal. Applying machine learning t...