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» On regularization algorithms in learning theory
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ML
2010
ACM
159views Machine Learning» more  ML 2010»
15 years 2 months ago
Algorithms for optimal dyadic decision trees
Abstract A dynamic programming algorithm for constructing optimal dyadic decision trees was recently introduced, analyzed, and shown to be very effective for low dimensional data ...
Don R. Hush, Reid B. Porter
CRV
2006
IEEE
90views Robotics» more  CRV 2006»
15 years 10 months ago
Photo Hull Regularized Stereo
A regularization-based approach to 3-D reconstruction from multiple images is proposed. As one of the most widely used multiple-view 3-D reconstruction algorithms, Space Carving c...
Shufei Fan, Frank P. Ferrie
ICML
2007
IEEE
16 years 5 months ago
Full regularization path for sparse principal component analysis
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a particular linear combination of the input variables while constraining the numb...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
AAAI
1993
15 years 5 months ago
Finding Accurate Frontiers: A Knowledge-Intensive Approach to Relational Learning
learning (EBL) component. In this paper we provide a brief review of FOIL and FOCL, then discuss how operationalizing a domain theory can adversely affect the accuracy of a learned...
Michael J. Pazzani, Clifford Brunk
TNN
2008
88views more  TNN 2008»
15 years 4 months ago
A Fault-Tolerant Regularizer for RBF Networks
In classical training methods for node open fault, we need to consider many potential faulty networks. When the multinode fault situation is considered, the space of potential faul...
Chi-Sing Leung, J. P. F. Sum