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» Feature Subset Selection Using a Genetic Algorithm
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ICASSP
2010
IEEE
15 years 2 months ago
Semi-Supervised Fisher Linear Discriminant (SFLD)
Supervised learning uses a training set of labeled examples to compute a classifier which is a mapping from feature vectors to class labels. The success of a learning algorithm i...
Seda Remus, Carlo Tomasi
AC
2000
Springer
15 years 6 months ago
Graph-Theoretical Methods in Computer Vision
The management of large databases of hierarchical (e.g., multi-scale or multilevel) image features is a common problem in object recognition. Such structures are often represented ...
Ali Shokoufandeh, Sven J. Dickinson
CORR
2010
Springer
204views Education» more  CORR 2010»
15 years 1 months ago
Predictive State Temporal Difference Learning
We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
Byron Boots, Geoffrey J. Gordon
156
Voted
LCTRTS
2010
Springer
15 years 11 days ago
Improving both the performance benefits and speed of optimization phase sequence searches
The issues of compiler optimization phase ordering and selection present important challenges to compiler developers in several domains, and in particular to the speed, code size,...
Prasad A. Kulkarni, Michael R. Jantz, David B. Wha...
172
Voted
AI
2002
Springer
15 years 2 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang