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» Approximation Methods for Supervised Learning
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AAAI
2012
11 years 11 months ago
Semi-Supervised Kernel Matching for Domain Adaptation
In this paper, we propose a semi-supervised kernel matching method to address domain adaptation problems where the source distribution substantially differs from the target distri...
Min Xiao, Yuhong Guo
RSCTC
2004
Springer
134views Fuzzy Logic» more  RSCTC 2004»
14 years 2 months ago
Rough Set Methods in Approximation of Hierarchical Concepts
Abstract. Many learning methods ignore domain knowledge in synthesis of concept approximation. We propose to use hierarchical schemes for learning approximations of complex concept...
Jan G. Bazan, Sinh Hoa Nguyen, Hung Son Nguyen, An...
SIAMCO
2000
117views more  SIAMCO 2000»
13 years 8 months ago
The O.D.E. Method for Convergence of Stochastic Approximation and Reinforcement Learning
It is shown here that stability of the stochastic approximation algorithm is implied by the asymptotic stability of the origin for an associated ODE. This in turn implies convergen...
Vivek S. Borkar, Sean P. Meyn
ICML
2006
IEEE
14 years 9 months ago
MISSL: multiple-instance semi-supervised learning
There has been much work on applying multiple-instance (MI) learning to contentbased image retrieval (CBIR) where the goal is to rank all images in a known repository using a smal...
Rouhollah Rahmani, Sally A. Goldman
ICML
2005
IEEE
14 years 9 months ago
Learning approximate preconditions for methods in hierarchical plans
A significant challenge in developing planning systems for practical applications is the difficulty of acquiring the domain knowledge needed by such systems. One method for acquir...
Dana S. Nau, David W. Aha, Héctor Muñ...