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» On the Complexity of Function Learning
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CRYPTO
2006
Springer
89views Cryptology» more  CRYPTO 2006»
15 years 4 months ago
Oblivious Transfer and Linear Functions
Abstract. We study unconditionally secure 1-out-of-2 Oblivious Transfer (1-2 OT). We first point out that a standard security requirement for 1-2 OT of bits, namely that the receiv...
Ivan Damgård, Serge Fehr, Louis Salvail, Chr...
PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
15 years 7 months ago
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
Tobias Jung, Peter Stone
108
Voted
IJCNN
2008
IEEE
15 years 7 months ago
A comparison of architectural varieties in Radial Basis Function Neural Networks
— Representation of knowledge within a neural model is an active field of research involved with the development of alternative structures, training algorithms, learning modes an...
Mehmet Önder Efe, Cosku Kasnakoglu
104
Voted
VISUAL
1999
Springer
15 years 5 months ago
Genetic Algorithm for Weights Assignment in Dissimilarity Function for Trademark Retrieval
Abstract. Trademark image retrieval is becoming an important application for logo registry, veri cation, and design. There are two major problems about the current approaches to tr...
David Yuk-Ming Chan, Irwin King
AAAI
2008
15 years 3 months ago
Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiya...