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» On learning algorithm selection for classification
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106
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ICPR
2008
IEEE
16 years 3 months ago
Prototype learning with margin-based conditional log-likelihood loss
The classification performance of nearest prototype classifiers largely relies on the prototype learning algorithms, such as the learning vector quantization (LVQ) and the minimum...
Cheng-Lin Liu, Xiaobo Jin, Xinwen Hou
116
Voted
IAT
2003
IEEE
15 years 7 months ago
Integrating Reinforcement Learning, Bidding and Genetic Algorithms
This paper presents a multi-agent reinforcement learning bidding approach (MARLBS) for performing multi-agent reinforcement learning. MARLBS integrates reinforcement learning, bid...
Dehu Qi, Ron Sun
MLDM
2007
Springer
15 years 8 months ago
Nonlinear Feature Selection by Relevance Feature Vector Machine
Support vector machine (SVM) has received much attention in feature selection recently because of its ability to incorporate kernels to discover nonlinear dependencies between feat...
Haibin Cheng, Haifeng Chen, Guofei Jiang, Kenji Yo...
137
Voted
ISCI
2008
95views more  ISCI 2008»
15 years 2 months ago
Modified constrained learning algorithms incorporating additional functional constraints into neural networks
In this paper, two modified constrained learning algorithms are proposed to obtain better generalization performance and faster convergence rate. The additional cost terms of the ...
Fei Han, Qing-Hua Ling, De-Shuang Huang
KI
2005
Springer
15 years 8 months ago
Selecting What Is Important: Training Visual Attention
We present a new, sophisticated algorithm to select suitable training images for our biologically motivated attention system VOCUS. The system detects regions of interest depending...
Simone Frintrop, Gerriet Backer, Erich Rome