Data mining focuses on the development of methods and algorithms for such tasks as classification, clustering, rule induction, and discovery of associations. In the database fiel...
This paper addresses the problem of discriminative training of language models that does not require any transcribed acoustic data. We propose to minimize the conditional entropy ...
Open-class semantic lexicon induction is of great interest for current knowledge harvesting algorithms. We propose a general framework that uses patterns in bootstrapping fashion ...
Abstract. The Factored Markov Decision Process (FMDP) framework is a standard representation for sequential decision problems under uncertainty where the state is represented as a ...
Olga Kozlova, Olivier Sigaud, Pierre-Henri Wuillem...
We consider reinforcement learning in the parameterized setup, where the model is known to belong to a parameterized family of Markov Decision Processes (MDPs). We further impose ...