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» Approximation Algorithms for Data Placement Problems
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TNN
2008
182views more  TNN 2008»
13 years 8 months ago
Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines
Abstract--Large-margin methods, such as support vector machines (SVMs), have been very successful in classification problems. Recently, maximum margin discriminant analysis (MMDA) ...
Ivor Wai-Hung Tsang, András Kocsor, James T...
JSW
2010
83views more  JSW 2010»
13 years 6 months ago
Estimating Model Parameters of Conditioned Soils by using Artificial Network
—The parameter identification of nonlinear constitutive model of soil mass is based on an inverse analysis procedure, which consists of minimizing the objective function represen...
Zichang Shangguan, Shouju Li, Wei Sun, Maotian Lua...
SIAMIS
2010
114views more  SIAMIS 2010»
13 years 6 months ago
Improved Total Variation-Type Regularization Using Higher Order Edge Detectors
We present a novel deconvolution approach to accurately restore piecewise smooth signals from blurred data. The first stage uses Higher Order Total Variation restorations to obtai...
Wolfgang Stefan, Rosemary A. Renaut, Anne Gelb
JMLR
2010
128views more  JMLR 2010»
13 years 3 months ago
Fluid Dynamics Models for Low Rank Discriminant Analysis
We consider the problem of reducing the dimensionality of labeled data for classification. Unfortunately, the optimal approach of finding the low-dimensional projection with minim...
Yung-Kyun Noh, Byoung-Tak Zhang, Daniel D. Lee
SIGMOD
2011
ACM
150views Database» more  SIGMOD 2011»
12 years 11 months ago
WHAM: a high-throughput sequence alignment method
Over the last decade the cost of producing genomic sequences has dropped dramatically due to the current so called “next-gen” sequencing methods. However, these next-gen seque...
Yinan Li, Allison Terrell, Jignesh M. Patel