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CIARP
2006
Springer
15 years 7 months ago
A New Approach to Multi-class Linear Dimensionality Reduction
Linear dimensionality reduction (LDR) is quite important in pattern recognition due to its efficiency and low computational complexity. In this paper, we extend the two-class Chern...
Luis Rueda, Myriam Herrera
113
Voted
IMA
1995
Springer
97views Cryptology» more  IMA 1995»
15 years 7 months ago
A New Algorithm for Finding Minimum-Weight Words in Large Linear Codes
An algorithm for finding small-weight words in large linear codes is developed and a precise analysis of its complexity is given. It is in particular able to decode random [512,256...
Anne Canteaut
JMLR
2008
133views more  JMLR 2008»
15 years 3 months ago
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
Suhrid Balakrishnan, David Madigan
MP
2008
129views more  MP 2008»
15 years 3 months ago
Corrector-predictor methods for monotone linear complementarity problems in a wide neighborhood of the central path
Abstract. Two corrector-predictor interior point algorithms are proposed for solving monotone linear complementarity problems. The algorithms produce a sequence of iterates in the ...
Florian A. Potra
TSP
2008
100views more  TSP 2008»
15 years 3 months ago
Finite-Sample Performance Analysis of Widely Linear Multiuser Receivers for DS-CDMA Systems
Abstract--This paper tackles the theoretical performance analysis of widely-linear (WL) multiuser receivers for direct-sequence code-division multiple-access (DS-CDMA) systems, as ...
Angela Sara Cacciapuoti, Giacinto Gelli, Luigi Pau...