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» Greedy in Approximation Algorithms
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93
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NIPS
2004
15 years 4 months ago
PAC-Bayes Learning of Conjunctions and Classification of Gene-Expression Data
We propose a "soft greedy" learning algorithm for building small conjunctions of simple threshold functions, called rays, defined on single real-valued attributes. We al...
Mario Marchand, Mohak Shah
105
Voted
CORR
2008
Springer
110views Education» more  CORR 2008»
15 years 2 months ago
Finding Dense Subgraphs in G(n,1/2)
Finding the largest clique in random graphs is a well known hard problem. It is known that a random graph G(n, 1/2) almost surely has a clique of size about 2 log n. A simple greed...
Atish Das Sarma, Amit Deshpande, Ravi Kannan
94
Voted
MOBIHOC
2009
ACM
16 years 3 months ago
Improved bounds on the throughput efficiency of greedy maximal scheduling in wireless networks
Due to its low complexity, Greedy Maximal Scheduling (GMS), also known as Longest Queue First (LQF), has been studied extensively for wireless networks. However, GMS can result in...
Mathieu Leconte, Jian Ni, Rayadurgam Srikant
141
Voted
JCO
1998
136views more  JCO 1998»
15 years 2 months ago
A Greedy Randomized Adaptive Search Procedure for the Feedback Vertex Set Problem
Abstract. A Greedy Randomized Adaptive Search Procedure (GRASP) is a randomized heuristic that has produced high quality solutions for a wide range of combinatorial optimization pr...
Panos M. Pardalos, Tianbing Qian, Mauricio G. C. R...
106
Voted
CEC
2007
IEEE
15 years 9 months ago
Incrementally maximising hypervolume for selection in multi-objective evolutionary algorithms
— Several multi-objective evolutionary algorithms compare the hypervolumes of different sets of points during their operation, usually for selection or archiving purposes. The ba...
Lucas Bradstreet, R. Lyndon While, Luigi Barone