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ICML
2007
IEEE
15 years 10 months ago
Large-scale RLSC learning without agony
The advances in kernel-based learning necessitate the study on solving a large-scale non-sparse positive definite linear system. To provide a deterministic approach, recent resear...
Wenye Li, Kin-Hong Lee, Kwong-Sak Leung
IPPS
1998
IEEE
15 years 1 months ago
High Performance Linear Algebra Package LAPACK90
Abstract. LAPACK90 is a set of LAPACK90 subroutines which interfaces FORTRAN90 with LAPACK. All LAPACK driver subroutines including expert drivers and some LAPACK computationals ha...
Jack Dongarra, Jerzy Wasniewski
JAIR
2002
163views more  JAIR 2002»
14 years 9 months ago
Efficient Reinforcement Learning Using Recursive Least-Squares Methods
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...
Xin Xu, Hangen He, Dewen Hu
CORR
2011
Springer
167views Education» more  CORR 2011»
14 years 4 months ago
Fast global convergence of gradient methods for high-dimensional statistical recovery
Many statistical M-estimators are based on convex optimization problems formed by the weighted sum of a loss function with a norm-based regularizer. We analyze the convergence rat...
Alekh Agarwal, Sahand Negahban, Martin J. Wainwrig...
TSP
2010
14 years 4 months ago
Single antenna power measurements based direction finding
Abstract--In this paper, the problem of estimating direction-ofarrival (DOA) of multiple uncorrelated sources from single antenna power measurements is addressed. Utilizing the fac...
Joni Polili Lie, Thierry Blu, Chong Meng Samson Se...