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UPP
2004
Springer
15 years 8 months ago
Inverse Design of Cellular Automata by Genetic Algorithms: An Unconventional Programming Paradigm
Evolving solutions rather than computing them certainly represents an unconventional programming approach. The general methodology of evolutionary computation has already been know...
Thomas Bäck, Ron Breukelaar, Lars Willmes
NIPS
2007
15 years 4 months ago
A General Boosting Method and its Application to Learning Ranking Functions for Web Search
We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier C...
AAAI
2006
15 years 4 months ago
Semi-supervised Multi-label Learning by Constrained Non-negative Matrix Factorization
We present a novel framework for multi-label learning that explicitly addresses the challenge arising from the large number of classes and a small size of training data. The key a...
Yi Liu, Rong Jin, Liu Yang
ICML
1998
IEEE
16 years 3 months ago
Value Function Based Production Scheduling
Production scheduling, the problem of sequentially con guring a factory to meet forecasted demands, is a critical problem throughout the manufacturing industry. The requirement of...
Jeff G. Schneider, Justin A. Boyan, Andrew W. Moor...
GECCO
2000
Springer
101views Optimization» more  GECCO 2000»
15 years 6 months ago
Evolutionary Design of Behaviors for Action-Based Environment Modeling by a Mobile Robot
This paper describes an evolutionary way to acquire behaviors of a mobile robot for recognizing environments. We have proposed AEM (Action-based Environment Modeling) approach for...
Seiji Yamada