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» A New Approximate Maximal Margin Classification Algorithm
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STOC
2002
ACM
118views Algorithms» more  STOC 2002»
14 years 7 months ago
On the advantage over a random assignment
: We initiate the study of a new measure of approximation. This measure compares the performance of an approximation algorithm to the random assignment algorithm. This is a useful ...
Johan Håstad, Srinivasan Venkatesh
ICCV
1995
IEEE
13 years 11 months ago
Alignment by Maximization of Mutual Information
A new information-theoretic approach is presented for finding the pose of an object in an image. The technique does not require information about the surface properties of the ob...
Paul A. Viola, William M. Wells III
RECOMB
2003
Springer
14 years 7 months ago
Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals
We propose a framework for modeling sequence motifs based on the maximum entropy principle (MEP). We recommend approximating short sequence motif distributions with the maximum en...
Gene W. Yeo, Christopher B. Burge
COLING
1992
13 years 8 months ago
Syntactic Ambiguity Resolution Using A Discrimination and Robustness Oriented Adaptive Learning Algorithm
In this paper, a discrimination and robusmess oriented adaptive learning procedure is proposed to deal with the task of syntactic ambiguity resolution. Owing to the problem of ins...
Tung-Hui Chiang, Yi-Chung Lin, Keh-Yih Su
CVPR
2009
IEEE
14 years 2 months ago
Manifold Discriminant Analysis
This paper presents a novel discriminative learning method, called Manifold Discriminant Analysis (MDA), to solve the problem of image set classification. By modeling each image s...
Ruiping Wang, Xilin Chen