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JMLR
2006
89views more  JMLR 2006»
13 years 7 months ago
Maximum-Gain Working Set Selection for SVMs
Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
Tobias Glasmachers, Christian Igel
AAAI
2006
13 years 8 months ago
Efficient L1 Regularized Logistic Regression
L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...
IJHPCA
2006
99views more  IJHPCA 2006»
13 years 7 months ago
A Pragmatic Analysis Of Scheduling Environments On New Computing Platforms
Today, large scale parallel systems are available at relatively low cost. Many powerful such systems have been installed all over the world and the number of users is always incre...
Lionel Eyraud
AUTOMATICA
2010
110views more  AUTOMATICA 2010»
13 years 7 months ago
Moving-horizon partition-based state estimation of large-scale systems
This paper presents three novel Moving Horizon Estimation (MHE) methods for discrete-time partitioned linear systems, i.e. systems decomposed into coupled subsystems with non-over...
Marcello Farina, Giancarlo Ferrari-Trecate, Riccar...
KDD
2010
ACM
195views Data Mining» more  KDD 2010»
13 years 11 months ago
Universal multi-dimensional scaling
In this paper, we propose a unified algorithmic framework for solving many known variants of MDS. Our algorithm is a simple iterative scheme with guaranteed convergence, and is m...
Arvind Agarwal, Jeff M. Phillips, Suresh Venkatasu...