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ITCC
2000
IEEE
14 years 3 days ago
A Unified Derivation of Operational Matrices for Integration in Systems Analysis
Using the operational matrix of an orthogonal function to perform integration for solving, identifying and optimizing a linear dynamic system has several advantages: (1) the metho...
Jiunn-lin Wu, Chin-hsing Chen, Chih-fan Chen
CORR
2007
Springer
164views Education» more  CORR 2007»
13 years 7 months ago
Consistency of the group Lasso and multiple kernel learning
We consider the least-square regression problem with regularization by a block 1-norm, that is, a sum of Euclidean norms over spaces of dimensions larger than one. This problem, r...
Francis Bach
ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
14 years 2 months ago
Sparse Least-Squares Methods in the Parallel Machine Learning (PML) Framework
—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...
Ramesh Natarajan, Vikas Sindhwani, Shirish Tatikon...
JMLR
2012
11 years 10 months ago
Generic Methods for Optimization-Based Modeling
“Energy” models for continuous domains can be applied to many problems, but often suffer from high computational expense in training, due to the need to repeatedly minimize t...
Justin Domke
NIPS
2003
13 years 9 months ago
Learning with Local and Global Consistency
We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to sem...
Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal,...