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ICDM
2009
IEEE
174views Data Mining» more  ICDM 2009»
14 years 3 months ago
Non-sparse Multiple Kernel Learning for Fisher Discriminant Analysis
—We consider the problem of learning a linear combination of pre-specified kernel matrices in the Fisher discriminant analysis setting. Existing methods for such a task impose a...
Fei Yan, Josef Kittler, Krystian Mikolajczyk, Muha...
ICTAI
2008
IEEE
14 years 3 months ago
Ensemble Learning of Regional Classifiers
We present a new ensemble learning method that employs a set of regional classifiers, each of which learns to handle a subset of the training data. We split the training data and ...
Byungwoo Lee, Yong-chan Na, Byonghwa Oh, Jihoon Ya...
IJCNN
2007
IEEE
14 years 3 months ago
Incorporating Forgetting in a Category Learning Model
— We present a computational model of human category learning that learns the essential structures of the categories by forgetting information that is not useful for the given ta...
Yasuaki Sakamoto, Toshihiko Matsuka
AAAI
2010
13 years 10 months ago
Reinforcement Learning via AIXI Approximation
This paper introduces a principled approach for the design of a scalable general reinforcement learning agent. This approach is based on a direct approximation of AIXI, a Bayesian...
Joel Veness, Kee Siong Ng, Marcus Hutter, David Si...
CISST
2004
164views Hardware» more  CISST 2004»
13 years 10 months ago
Probabilistic Region Relevance Learning for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
Iker Gondra, Douglas R. Heisterkamp