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ECCV
2006
Springer
16 years 8 months ago
Learning Nonlinear Manifolds from Time Series
Abstract. There has been growing interest in developing nonlinear dimensionality reduction algorithms for vision applications. Although progress has been made in recent years, conv...
Ruei-Sung Lin, Che-Bin Liu, Ming-Hsuan Yang, Naren...
ALT
2006
Springer
16 years 3 months ago
Probabilistic Generalization of Simple Grammars and Its Application to Reinforcement Learning
Abstract. Recently, some non-regular subclasses of context-free grammars have been found to be efficiently learnable from positive data. In order to use these efficient algorithms ...
Takeshi Shibata, Ryo Yoshinaka, Takashi Chikayama
EUROGP
2009
Springer
132views Optimization» more  EUROGP 2009»
16 years 1 months ago
A Statistical Learning Perspective of Genetic Programming
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in GP from the perspec...
Nur Merve Amil, Nicolas Bredeche, Christian Gagn&e...
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
16 years 22 days ago
Learning noise
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Michael D. Schmidt, Hod Lipson
WAPCV
2007
Springer
16 years 21 days ago
Learning to Attend - From Bottom-Up to Top-Down
The control of overt visual attention relies on an interplay of bottom-up and top-down mechanisms. Purely bottom-up models may provide a reasonable account of the looking behaviors...
Hector Jasso, Jochen Triesch