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» Spectral norm of random matrices
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AAAI
2007
13 years 11 months ago
Compact Spectral Bases for Value Function Approximation Using Kronecker Factorization
A new spectral approach to value function approximation has recently been proposed to automatically construct basis functions from samples. Global basis functions called proto-val...
Jeffrey Johns, Sridhar Mahadevan, Chang Wang
VLSID
2007
IEEE
160views VLSI» more  VLSID 2007»
14 years 9 months ago
Spectral RTL Test Generation for Microprocessors
We introduce a novel method of test generation for microprocessors at the RTL using spectral methods. Test vectors are generated for RTL faults, which are the stuck-at faults on i...
Nitin Yogi, Vishwani D. Agrawal
SDM
2010
SIAM
213views Data Mining» more  SDM 2010»
13 years 10 months ago
Spectral Analysis of Signed Graphs for Clustering, Prediction and Visualization
We study the application of spectral clustering, prediction and visualization methods to graphs with negatively weighted edges. We show that several characteristic matrices of gra...
Jérôme Kunegis, Stephan Schmidt, Andr...
ICDM
2003
IEEE
98views Data Mining» more  ICDM 2003»
14 years 1 months ago
On the Privacy Preserving Properties of Random Data Perturbation Techniques
Privacy is becoming an increasingly important issue in many data mining applications. This has triggered the development of many privacy-preserving data mining techniques. A large...
Hillol Kargupta, Souptik Datta, Qi Wang, Krishnamo...
STOC
2001
ACM
138views Algorithms» more  STOC 2001»
14 years 8 months ago
Fast computation of low rank matrix
Given a matrix A, it is often desirable to find a good approximation to A that has low rank. We introduce a simple technique for accelerating the computation of such approximation...
Dimitris Achlioptas, Frank McSherry