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» A New Iterative Method for Solving Initial Value Problems
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JMLR
2006
89views more  JMLR 2006»
13 years 8 months ago
Maximum-Gain Working Set Selection for SVMs
Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
Tobias Glasmachers, Christian Igel
MANSCI
2007
139views more  MANSCI 2007»
13 years 8 months ago
A Market-Based Optimization Algorithm for Distributed Systems
In this paper, a market-based decomposition method for decomposable linear systems is developed. The solution process iterates between a master problem that solves the market-matc...
Zhiling Guo, Gary J. Koehler, Andrew B. Whinston
ICCAD
2002
IEEE
81views Hardware» more  ICCAD 2002»
14 years 5 months ago
Making Fourier-envelope simulation robust
Fourier-envelope algorithms are an important component of the mixed-signal/RF verification toolbox. In this paper, we address the unpredictability and lack of robustness that has...
Jaijeet S. Roychowdhury
MMAS
2011
Springer
12 years 11 months ago
Sweeping Preconditioner for the Helmholtz Equation: Moving Perfectly Matched Layers
This paper introduces a new sweeping preconditioner for the iterative solution of the variable coefficient Helmholtz equation in two and three dimensions. The algorithms follow th...
Björn Engquist, Lexing Ying
ECML
2006
Springer
14 years 15 days ago
An Adaptive Kernel Method for Semi-supervised Clustering
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...
Bojun Yan, Carlotta Domeniconi