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» On sampling-based approximate spectral decomposition
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ICML
2009
IEEE
14 years 5 months ago
On sampling-based approximate spectral decomposition
This paper addresses the problem of approximate singular value decomposition of large dense matrices that arises naturally in many machine learning applications. We discuss two re...
Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar
GECCO
2006
Springer
154views Optimization» more  GECCO 2006»
13 years 8 months ago
Spectral techniques for graph bisection in genetic algorithms
Various applications of spectral techniques for enhancing graph bisection in genetic algorithms are investigated. Several enhancements to a genetic algorithm for graph bisection a...
Jacob G. Martin
GD
2006
Springer
13 years 8 months ago
SSDE: Fast Graph Drawing Using Sampled Spectral Distance Embedding
Abstract. We present a fast spectral graph drawing algorithm for drawing undirected connected graphs. Classical Multi-Dimensional Scaling yields a quadratictime spectral algorithm,...
Ali Civril, Malik Magdon-Ismail, Eli Bocek-Rivele
CVPR
2008
IEEE
14 years 7 months ago
Large-scale manifold learning
This paper examines the problem of extracting lowdimensional manifold structure given millions of highdimensional face images. Specifically, we address the computational challenge...
Ameet Talwalkar, Sanjiv Kumar, Henry A. Rowley
ASPDAC
2009
ACM
143views Hardware» more  ASPDAC 2009»
13 years 11 months ago
Statistical modeling and analysis of chip-level leakage power by spectral stochastic method
In this paper, we present a novel statistical full-chip leakage power analysis method. The new method can provide a general framework to derive the full-chip leakage current or po...
Ruijing Shen, Ning Mi, Sheldon X.-D. Tan, Yici Cai...