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» Sublinear Optimization for Machine Learning
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ICPR
2006
IEEE
14 years 11 months ago
A novel SVM Geometric Algorithm based on Reduced Convex Hulls
Geometric methods are very intuitive and provide a theoretically solid viewpoint to many optimization problems. SVM is a typical optimization task that has attracted a lot of atte...
Michael E. Mavroforakis, Margaritis Sdralis, Sergi...
ICML
1995
IEEE
14 years 11 months ago
Learning to Make Rent-to-Buy Decisions with Systems Applications
In the single rent-to-buy decision problem, without a priori knowledge of the amount of time a resource will be used we need to decide when to buy the resource, given that we can ...
P. Krishnan, Philip M. Long, Jeffrey Scott Vitter
UAI
2003
13 years 11 months ago
On the Convergence of Bound Optimization Algorithms
Many practitioners who use EM and related algorithms complain that they are sometimes slow. When does this happen, and what can be done about it? In this paper, we study the gener...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...
JMLR
2012
12 years 20 days ago
Online Incremental Feature Learning with Denoising Autoencoders
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
Guanyu Zhou, Kihyuk Sohn, Honglak Lee
ICDM
2009
IEEE
154views Data Mining» more  ICDM 2009»
13 years 8 months ago
GSML: A Unified Framework for Sparse Metric Learning
There has been significant recent interest in sparse metric learning (SML) in which we simultaneously learn both a good distance metric and a low-dimensional representation. Unfor...
Kaizhu Huang, Yiming Ying, Colin Campbell