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TNN
1998
112views more  TNN 1998»
15 years 6 months ago
A class of competitive learning models which avoids neuron underutilization problem
— In this paper, we study a qualitative property of a class of competitive learning (CL) models, which is called the multiplicatively biased competitive learning (MBCL) model, na...
Clifford Sze-Tsan Choy, Wan-Chi Siu
ICONIP
2009
15 years 4 months ago
Tracking in Reinforcement Learning
Reinforcement learning induces non-stationarity at several levels. Adaptation to non-stationary environments is of course a desired feature of a fair RL algorithm. Yet, even if the...
Matthieu Geist, Olivier Pietquin, Gabriel Fricout
CORR
2010
Springer
148views Education» more  CORR 2010»
15 years 1 months ago
A Unifying View of Multiple Kernel Learning
Recent research on multiple kernel learning has lead to a number of approaches for combining kernels in regularized risk minimization. The proposed approaches include different for...
Marius Kloft, Ulrich Rückert, Peter L. Bartle...
CVPR
2007
IEEE
16 years 8 months ago
Regularized Mixed Dimensionality and Density Learning in Computer Vision
A framework for the regularized estimation of nonuniform dimensionality and density in high dimensional data is introduced in this work. This leads to learning stratifications, th...
Gloria Haro, Gregory Randall, Guillermo Sapiro
ECCV
2006
Springer
16 years 8 months ago
Riemannian Manifold Learning for Nonlinear Dimensionality Reduction
In recent years, nonlinear dimensionality reduction (NLDR) techniques have attracted much attention in visual perception and many other areas of science. We propose an efficient al...
Tony Lin, Hongbin Zha, Sang Uk Lee