180 search results - page 4 / 36 » Introduction to Statistical Learning Theory |
EUROGP
2009
Springer
14 years 2 months ago
2009
Springer
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in GP from the perspec...
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Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms sy...
STOC
1993
ACM
13 years 11 months ago
1993
ACM
In this paper, we study the problem of learning in the presence of classification noise in the probabilistic learning model of Valiant and its variants. In order to identify the cl...
NIPS
2000
13 years 8 months ago
2000
We propose a general framework for performing independent component analysis (ICA) which relies on ensemble learning and linear response theory known from statistical physics. We ...
CVPR
2001
IEEE
14 years 9 months ago
2001
IEEE
This paper describes a machine learning approach for visual
object detection which is capable of processing images
extremely rapidly and achieving high detection rates. This
wor...