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» Generalized Boosting Algorithms for Convex Optimization
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CSB
2004
IEEE
126views Bioinformatics» more  CSB 2004»
14 years 13 days ago
Boosted PRIM with Application to Searching for Oncogenic Pathway of Lung Cancer
Boosted PRIM (Patient Rule Induction Method) is a new algorithm developed for two-class classification problems. PRIM is a variation of those Tree-Based methods ( [4] Ch9.3), seek...
Pei Wang, Young Kim, Jonathan R. Pollack, Robert T...
BMVC
2010
13 years 6 months ago
StyP-Boost: A Bilinear Boosting Algorithm for Learning Style-Parameterized Classifiers
We introduce a novel bilinear boosting algorithm, which extends the multi-class boosting framework of JointBoost to optimize a bilinear objective function. This allows style param...
Jonathan Warrell, Philip H. S. Torr, Simon Prince
ML
2007
ACM
106views Machine Learning» more  ML 2007»
13 years 8 months ago
Surrogate maximization/minimization algorithms and extensions
Abstract Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. A...
Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
SODA
1996
ACM
121views Algorithms» more  SODA 1996»
13 years 10 months ago
Optimal Placement of Convex Polygons to Maximize Point Containment
Given a convex polygon P with m vertices and a set S of n points in the plane, we consider the problem of nding a placement of P that contains the maximum number of points in S. W...
Matthew Dickerson, Daniel Scharstein
JMLR
2012
11 years 11 months ago
A General Framework for Structured Sparsity via Proximal Optimization
We study a generalized framework for structured sparsity. It extends the well known methods of Lasso and Group Lasso by incorporating additional constraints on the variables as pa...
Luca Baldassarre, Jean Morales, Andreas Argyriou, ...