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» On Randomized Lanczos Algorithms
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JMLR
2008
230views more  JMLR 2008»
13 years 7 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
APPROX
2006
Springer
107views Algorithms» more  APPROX 2006»
13 years 11 months ago
A Fast Random Sampling Algorithm for Sparsifying Matrices
We describe a simple random-sampling based procedure for producing sparse matrix approximations. Our procedure and analysis are extremely simple: the analysis uses nothing more th...
Sanjeev Arora, Elad Hazan, Satyen Kale
APPROX
2004
Springer
116views Algorithms» more  APPROX 2004»
14 years 25 days ago
Randomized Approximation Algorithms for Set Multicover Problems with Applications to Reverse Engineering of Protein and Gene Net
In this paper we investigate the computational complexity of a combinatorial problem that arises in the reverse engineering of protein and gene networks. Our contributions are as ...
Piotr Berman, Bhaskar DasGupta, Eduardo D. Sontag
WEA
2004
Springer
85views Algorithms» more  WEA 2004»
14 years 23 days ago
Faster Deterministic and Randomized Algorithms on the Homogeneous Set Sandwich Problem
A homogeneous set is a non-trivial, proper subset of a graph’s vertices such that all its elements present exactly the same outer neighborhood. Given two graphs, G1(V, E1), G2(V,...
Celina M. Herrera de Figueiredo, Guilherme Dias da...