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AI
2002
Springer
14 years 9 months ago
Multiagent learning using a variable learning rate
Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on ...
Michael H. Bowling, Manuela M. Veloso
ALT
2004
Springer
15 years 6 months ago
Convergence of a Generalized Gradient Selection Approach for the Decomposition Method
The decomposition method is currently one of the major methods for solving the convex quadratic optimization problems being associated with support vector machines. For a special c...
Nikolas List
WACV
2007
IEEE
15 years 3 months ago
Object Categorization Robust to Surface Markings using Entropy-guided Codebook
Visual categorization is fundamentally important for autonomous mobile robots to get intelligence such as novel object acquisition and topological place recognition. The main difï...
Sungho Kim, In-So Kweon
IJCNN
2006
IEEE
15 years 3 months ago
Model Selection via Bilevel Optimization
— A key step in many statistical learning methods used in machine learning involves solving a convex optimization problem containing one or more hyper-parameters that must be sel...
Kristin P. Bennett, Jing Hu, Xiaoyun Ji, Gautam Ku...
JMLR
2011
192views more  JMLR 2011»
14 years 4 months ago
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...