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An improved branch-and-bound method for maximum monomial agreement
Jonathan Eckstein
, Noam Goldberg
Rutgers - The State University of New Jersey, New Brunswick
Argonne National Laboratory
Research output
:
Contribution to journal
›
Article
›
peer-review
10
Scopus citations
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Dive into the research topics of 'An improved branch-and-bound method for maximum monomial agreement'. Together they form a unique fingerprint.
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Keyphrases
Monomial
100%
Branch-and-bound Method
100%
Goldberg
66%
Shan
66%
Tight
33%
NP-hard
33%
Problem Instances
33%
Linear Programming
33%
Philadelphia
33%
Heuristic Method
33%
Medium Size
33%
Upper Bounding
33%
Boolean
33%
Large-scale Problems
33%
Programming Solver
33%
Bounded Functions
33%
Agreement Problem
33%
UCI Machine Learning Repository
33%
Binary Vector
33%
Mixed Integer Programming
33%
Weighted Voting Classifier
33%
Linear Programming Relaxation
33%
Branching Factor
33%
Logical Conjunction
33%
Relaxation-based
33%
Weighted Data
33%
Boosting Method
33%
Integer Linear Programming Formulations
33%
Logical Patterns
33%
Computer Science
Linear Programming
100%
Branch-and-Bound Algorithm Design
100%
Problem Instance
50%
Machine Learning
50%
Data Mining
50%
Heuristic Method
50%
Integer-Linear Programming
50%
Mixed Integer Programming
50%
Branching Factor
50%
Bounding Function
50%
Experimental Result
50%
Mathematics
Monomials
100%
Subproblem
66%
Linear Programming
66%
Integer
33%
Linear Programming Relaxation
33%
Data Mining
33%
Heuristic Method
33%
Binary Vector
33%
Integer Programming
33%
Chemical Engineering
Learning System
100%