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MP
2011
15 years 1 months ago
Null space conditions and thresholds for rank minimization
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in machine learning, control theory, and discrete geometry. This c...
Benjamin Recht, Weiyu Xu, Babak Hassibi
OL
2011
332views Neural Networks» more  OL 2011»
15 years 1 months ago
A robust implementation of a sequential quadratic programming algorithm with successive error restoration
We consider sequential quadratic programming (SQP) methods for solving constrained nonlinear programming problems. It is generally believed that SQP methods are sensitive to the a...
Klaus Schittkowski
JMLR
2010
104views more  JMLR 2010»
15 years 1 months ago
Increasing Feature Selection Accuracy for L1 Regularized Linear Models
L1 (also referred to as the 1-norm or Lasso) penalty based formulations have been shown to be effective in problem domains when noisy features are present. However, the L1 penalty...
Abhishek Jaiantilal, Gregory Z. Grudic
ICASSP
2011
IEEE
14 years 10 months ago
Probabilistic SINR constrained robust transmit beamforming: A Bernstein-type inequality based conservative approach
Recently, robust transmit beamforming has drawn considerable attention because it can provide guaranteed receiver performance in the presence of channel state information (CSI) er...
Kun-Yu Wang, Tsung-Hui Chang, Wing-Kin Ma, Anthony...
WIOPT
2011
IEEE
14 years 10 months ago
Network utility maximization over partially observable Markovian channels
Abstract—This paper considers maximizing throughput utility in a multi-user network with partially observable Markov ON/OFF channels. Instantaneous channel states are never known...
Chih-Ping Li, Michael J. Neely