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» Randomness and the linear degrees of computability
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NIPS
2008
15 years 1 months ago
Sparse Signal Recovery Using Markov Random Fields
Compressive Sensing (CS) combines sampling and compression into a single subNyquist linear measurement process for sparse and compressible signals. In this paper, we extend the th...
Volkan Cevher, Marco F. Duarte, Chinmay Hegde, Ric...
ICML
2006
IEEE
16 years 17 days ago
Quadratic programming relaxations for metric labeling and Markov random field MAP estimation
Quadratic program relaxations are proposed as an alternative to linear program relaxations and tree reweighted belief propagation for the metric labeling or MAP estimation problem...
Pradeep D. Ravikumar, John D. Lafferty
CORR
2008
Springer
227views Education» more  CORR 2008»
14 years 12 months ago
An experimental analysis of Lemke-Howson algorithm
We present an experimental investigation of the performance of the Lemke-Howson algorithm, which is the most widely used algorithm for the computation of a Nash equilibrium for bi...
Bruno Codenotti, Stefano De Rossi, Marino Pagan
FOCS
2007
IEEE
15 years 6 months ago
Linear Equations Modulo 2 and the L1 Diameter of Convex Bodies
We design a randomized polynomial time algorithm which, given a 3-tensor of real numbers A = {aijk}n i,j,k=1 such that for all i, j, k ∈ {1, . . . , n} we have ai jk = aik j = a...
Subhash Khot, Assaf Naor
ICPR
2010
IEEE
15 years 6 months ago
A Bound on the Performance of LDA in Randomly Projected Data Spaces
We consider the problem of classification in nonadaptive dimensionality reduction. Specifically, we bound the increase in classification error of Fisher’s Linear Discriminant...
Robert John Durrant, Ata Kaban