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» An Exploration of the Permanent-Determinant Method
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NN
2010
Springer
187views Neural Networks» more  NN 2010»
15 years 23 days ago
Efficient exploration through active learning for value function approximation in reinforcement learning
Appropriately designing sampling policies is highly important for obtaining better control policies in reinforcement learning. In this paper, we first show that the least-squares ...
Takayuki Akiyama, Hirotaka Hachiya, Masashi Sugiya...
GIR
2006
ACM
15 years 12 months ago
Exploring Probabilistic Toponym Resolution for Geographical Information Retrieval
A key problem that arises when unstructured text is being queried is that of properly recognizing and exploiting geographical terms and entities. Here we describe a mechanism for ...
Yi Li, Alistair Moffat, Nicola Stokes, Lawrence Ca...
IICAI
2007
15 years 7 months ago
Exploring Translation Similarities for Building a Better Sentence Aligner
Abstract. The approaches previously used for sentence alignment (sentence length, word correspondence and cognate matching) take into account different aspects of similarity betwe...
Anil Kumar Singh, Samar Husain
ISVLSI
2008
IEEE
173views VLSI» more  ISVLSI 2008»
16 years 12 days ago
System Level Design Space Exploration for Multiprocessor System on Chip
Future embedded systems will integrate hundreds of processors. Current design space exploration methods cannot cope with such a complexity. It is mandatory to extend these methods...
Issam Maalej, Guy Gogniat, Jean Luc Philippe, Moha...
IJCAI
2007
15 years 7 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup