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ICASSP
2010
IEEE
13 years 8 months ago
A convex relaxation for approximate maximum-likelihood 2D source localization from range measurements
This paper addresses the problem of locating a single source from noisy range measurements in wireless sensor networks. An approximate solution to the maximum likelihood location ...
Pinar Oguz-Ekim, João Pedro Gomes, Jo&atild...
TSP
2010
13 years 2 months ago
Code design for radar STAP via optimization theory
Abstract--In this paper, we deal with the problem of constrained code optimization for radar space-time adaptive processing (STAP) in the presence of colored Gaussian disturbance. ...
Antonio De Maio, Silvio De Nicola, Yongwei Huang, ...
SIAMJO
2010
127views more  SIAMJO 2010»
13 years 2 months ago
Trace Norm Regularization: Reformulations, Algorithms, and Multi-Task Learning
We consider a recently proposed optimization formulation of multi-task learning based on trace norm regularized least squares. While this problem may be formulated as a semidefini...
Ting Kei Pong, Paul Tseng, Shuiwang Ji, Jieping Ye
JMLR
2008
169views more  JMLR 2008»
13 years 7 months ago
Multi-class Discriminant Kernel Learning via Convex Programming
Regularized kernel discriminant analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. Its performance depends on the selection of kernel...
Jieping Ye, Shuiwang Ji, Jianhui Chen
CORR
2011
Springer
172views Education» more  CORR 2011»
13 years 2 months ago
Improving Strategies via SMT Solving
We consider the problem of computing numerical invariants of programs by abstract interpretation. Our method eschews two traditional sources of imprecision: (i) the use of widenin...
Thomas Martin Gawlitza, David Monniaux