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» An improvement on learning with local and global consistency
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AAAI
1998
13 years 9 months ago
Learning Evaluation Functions for Global Optimization and Boolean Satisfiability
This paper describes STAGE, a learning approach to automatically improving search performance on optimization problems.STAGElearns an evaluation function which predicts the outcom...
Justin A. Boyan, Andrew W. Moore
ICCS
2009
Springer
13 years 5 months ago
Bending Virtual Spring-Damper: A Solution to Improve Local Platoon Control
This article presents a local control approach to linear vehicle platooning. Linear platoon systems are sets of vehicles that use local or global perception capabilities to form a ...
Jean-Michel Contet, Franck Gechter, Pablo Gruer, A...
CSL
2010
Springer
13 years 8 months ago
Active learning and semi-supervised learning for speech recognition: A unified framework using the global entropy reduction maxi
We propose a unified global entropy reduction maximization (GERM) framework for active learning and semi-supervised learning for speech recognition. Active learning aims to select...
Dong Yu, Balakrishnan Varadarajan, Li Deng, Alex A...
BMCBI
2005
125views more  BMCBI 2005»
13 years 7 months ago
DIALIGN-T: An improved algorithm for segment-based multiple sequence alignment
Background: We present a complete re-implementation of the segment-based approach to multiple protein alignment that contains a number of improvements compared to the previous ver...
Amarendran R. Subramanian, Jan Weyer-Menkhoff, Mic...
ECAI
2004
Springer
14 years 1 months ago
Improving Asynchronous Backtracking for Dealing with Complex Local Problems
Distributed constraint satisfaction, in its most general acceptation, involves a collection of agents solving local constraint satisfaction subproblems, and a communication protoco...
Arnold Maestre, Christian Bessière