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ICML
2007
IEEE
16 years 4 months ago
Scalable training of L1-regularized log-linear models
The l-bfgs limited-memory quasi-Newton method is the algorithm of choice for optimizing the parameters of large-scale log-linear models with L2 regularization, but it cannot be us...
Galen Andrew, Jianfeng Gao
ISSAC
2007
Springer
153views Mathematics» more  ISSAC 2007»
15 years 10 months ago
On exact and approximate interpolation of sparse rational functions
The black box algorithm for separating the numerator from the denominator of a multivariate rational function can be combined with sparse multivariate polynomial interpolation alg...
Erich Kaltofen, Zhengfeng Yang
ADMA
2006
Springer
127views Data Mining» more  ADMA 2006»
15 years 10 months ago
Feature Selection for Complex Patterns
Feature selection is an important data preprocessing step in data mining and pattern recognition. Many algorithms have been proposed in the past for simple patterns that can be cha...
Peter Schenkel, Wanqing Li, Wanquan Liu
CORR
2010
Springer
131views Education» more  CORR 2010»
15 years 2 months ago
Ideal forms of Coppersmith's theorem and Guruswami-Sudan list decoding
: We develop a framework for solving polynomial equations with size constraints on solutions. We obtain our results by showing how to apply a technique of Coppersmith for finding ...
Henry Cohn, Nadia Heninger
CORR
2010
Springer
93views Education» more  CORR 2010»
15 years 4 months ago
Rank Awareness in Joint Sparse Recovery
In this paper we revisit the sparse multiple measurement vector (MMV) problem, where the aim is to recover a set of jointly sparse multichannel vectors from incomplete measurement...
Mike E. Davies, Yonina C. Eldar