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NIPS
1998
14 years 11 months ago
Coding Time-Varying Signals Using Sparse, Shift-Invariant Representations
A common way to represent a time series is to divide it into shortduration blocks, each of which is then represented by a set of basis functions. A limitation of this approach, ho...
Michael S. Lewicki, Terrence J. Sejnowski
ICASSP
2010
IEEE
14 years 10 months ago
Fast signal analysis and decomposition on graphs using the Sparse Matrix Transform
Recently, the Sparse Matrix Transform (SMT) has been proposed as a tool for estimating the eigen-decomposition of high dimensional data vectors [1]. The SMT approach has two major...
Leonardo R. Bachega, Guangzhi Cao, Charles A. Boum...
ECCC
2008
122views more  ECCC 2008»
14 years 10 months ago
Every Minor-Closed Property of Sparse Graphs is Testable
Testing a property P of graphs in the bounded degree model is the following computational problem: given a graph G of bounded degree d we should distinguish (with probability 0.9,...
Itai Benjamini, Oded Schramm, Asaf Shapira
CORR
2010
Springer
178views Education» more  CORR 2010»
14 years 7 months ago
Is Light-Tree Structure Optimal for Multicast Routing in Sparse Light Splitting WDM Networks?
To minimize the number of wavelengths required by a multicast session in sparse light splitting Wavelength Division Multiplexing (WDM) networks, a light-hierarchy structure, which ...
Fen Zhou, Miklós Molnár, Bernard Cou...
CORR
2010
Springer
136views Education» more  CORR 2010»
14 years 7 months ago
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
Many problems in machine learning and statistics can be formulated as (generalized) eigenproblems. In terms of the associated optimization problem, computing linear eigenvectors a...
Matthias Hein, Thomas Bühler