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NIPS
2007
14 years 11 months ago
Online Linear Regression and Its Application to Model-Based Reinforcement Learning
We provide a provably efficient algorithm for learning Markov Decision Processes (MDPs) with continuous state and action spaces in the online setting. Specifically, we take a mo...
Alexander L. Strehl, Michael L. Littman
IJCAI
2001
14 years 11 months ago
Adaptive Control of Acyclic Progressive Processing Task Structures
The progressive processing model allows a system to trade off resource consumption against the quality of the outcome by mapping each activity to a graph of potential solution met...
Stéphane Cardon, Abdel-Illah Mouaddib, Shlo...
JIRS
2000
121views more  JIRS 2000»
14 years 9 months ago
Entropy-Based Markov Chains for Multisensor Fusion
Abstract. This paper proposes an entropy based Markov chain (EMC) fusion technique and demonstrates its applications in multisensor fusion. Self-entropy and conditional entropy, wh...
Albert C. S. Chung, Helen C. Shen
ECML
2007
Springer
14 years 11 months ago
Sequence Labeling with Reinforcement Learning and Ranking Algorithms
Many problems in areas such as Natural Language Processing, Information Retrieval, or Bioinformatic involve the generic task of sequence labeling. In many cases, the aim is to assi...
Francis Maes, Ludovic Denoyer, Patrick Gallinari
ATVA
2006
Springer
123views Hardware» more  ATVA 2006»
15 years 1 months ago
Symmetry Reduction for Probabilistic Model Checking Using Generic Representatives
Generic representatives have been proposed for the effective combination of symmetry reduction and symbolic representation with BDDs in non-probabilistic model checking. This appro...
Alastair F. Donaldson, Alice Miller