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GECCO
2000
Springer
143views Optimization» more  GECCO 2000»
15 years 5 months ago
A Genetic Algorithm for Automatically Designing Modular Reinforcement Learning Agents
Reinforcement learning (RL) is one of the machine learning techniques and has been received much attention as a new self-adaptive controller for various systems. The RL agent auto...
Isao Ono, Tetsuo Nijo, Norihiko Ono
WEBI
2005
Springer
15 years 7 months ago
Measuring the Relative Performance of Schema Matchers
Schema matching is a complex process focusing on matching between concepts describing the data in heterogeneous data sources. There is a shift from manual schema matching, done by...
Shlomo Berkovsky, Yaniv Eytani, Avigdor Gal
JMLR
2012
13 years 4 months ago
Metric and Kernel Learning Using a Linear Transformation
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
PAMI
2012
13 years 4 months ago
Task-Driven Dictionary Learning
—Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal proce...
Julien Mairal, Francis Bach, Jean Ponce
EUROGP
2009
Springer
132views Optimization» more  EUROGP 2009»
15 years 8 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...