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CORR
2010
Springer
167views Education» more  CORR 2010»
13 years 8 months ago
Network Flow Algorithms for Structured Sparsity
We consider a class of learning problems that involve a structured sparsityinducing norm defined as the sum of -norms over groups of variables. Whereas a lot of effort has been pu...
Julien Mairal, Rodolphe Jenatton, Guillaume Obozin...
ICCAD
2001
IEEE
124views Hardware» more  ICCAD 2001»
14 years 5 months ago
Highly Accurate Fast Methods for Extraction and Sparsification of Substrate Coupling Based on Low-Rank Approximation
More aggressive design practices have created renewed interest in techniques for analyzing substrate coupling problems. Most previous work has focused primarily on faster techniqu...
Joe Kanapka, Jacob White
SIGMOD
2010
ACM
186views Database» more  SIGMOD 2010»
14 years 1 months ago
Fast approximate correlation for massive time-series data
We consider the problem of computing all-pair correlations in a warehouse containing a large number (e.g., tens of thousands) of time-series (or, signals). The problem arises in a...
Abdullah Mueen, Suman Nath, Jie Liu
WADS
2009
Springer
243views Algorithms» more  WADS 2009»
14 years 3 months ago
Approximation Algorithms for Buy-at-Bulk Geometric Network Design
Abstract. The buy-at-bulk network design problem has been extensively studied in the general graph model. In this paper we consider the geometric version of the problem, where all ...
Artur Czumaj, Jurek Czyzowicz, Leszek Gasieniec, J...
STOC
2006
ACM
244views Algorithms» more  STOC 2006»
14 years 9 months ago
Approximate nearest neighbors and the fast Johnson-Lindenstrauss transform
We introduce a new low-distortion embedding of d 2 into O(log n) p (p = 1, 2), called the Fast-Johnson-LindenstraussTransform. The FJLT is faster than standard random projections ...
Nir Ailon, Bernard Chazelle