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» A Better Algorithm for Random k-SAT
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KDD
2010
ACM
274views Data Mining» more  KDD 2010»
13 years 11 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
BMCBI
2008
101views more  BMCBI 2008»
13 years 8 months ago
Prediction of glycosylation sites using random forests
Background: Post translational modifications (PTMs) occur in the vast majority of proteins and are essential for function. Prediction of the sequence location of PTMs enhances the...
Stephen E. Hamby, Jonathan D. Hirst
SAT
2005
Springer
124views Hardware» more  SAT 2005»
14 years 1 months ago
An Improved Upper Bound for SAT
We give a randomized algorithm for testing satisfiability of Boolean formulas in conjunctive normal form with no restriction on clause length. Its running time is at most 2n(1−1...
Evgeny Dantsin, Alexander Wolpert
SAC
2003
ACM
14 years 1 months ago
Greedy Heuristics and an Evolutionary Algorithm for the Bounded-Diameter Minimum Spanning Tree Problem
Given a connected, weighted, undirected graph G and a bound D, the bounded-diameter minimum spanning tree problem seeks a spanning tree on G of lowest weight in which no path betw...
Günther R. Raidl, Bryant A. Julstrom
INFOCOM
2000
IEEE
14 years 6 days ago
An Empirical Evaluation of Client-Side Server Selection Algorithms
—Efficient server selection algorithms reduce retrieval time for objects replicated on different servers and are an important component of Internet cache architectures. This pap...
Sandra G. Dykes, Kay A. Robbins, Clinton L. Jeffer...