566 search results - page 75 / 114 » Approximation Spaces in Machine Learning and Pattern Recogni... |
167
Voted
ALT
2008
Springer
16 years 7 days ago
2008
Springer
Abstract For many centuries scientists have wondered how the human brain represents thoughts in terms of the underlying biology of neural activity. Philosophers, linguists, cogniti...
146
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ICML
1996
IEEE
16 years 4 months ago
1996
IEEE
Some of the most successful recent applications of reinforcement learning have used neural networks and the TD algorithm to learn evaluation functions. In this paper, we examine t...
152
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ACCV
2010
Springer
14 years 10 months ago
2010
Springer
Abstract. In set-based face recognition, each set of face images is often represented as a linear/nonlinear manifold and the Principal Angles (PA) or Kernel PAs are exploited to me...
129
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ICML
2010
IEEE
15 years 4 months ago
2010
IEEE
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
132
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COLT
2010
Springer
15 years 1 months ago
2010
Springer
In recent years analysis of complexity of learning Gaussian mixture models from sampled data has received significant attention in computational machine learning and theory commun...