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Submodular function maximization in parallel via the multilinear relaxation
Chandra Chekuri
, Kent Quanrud
Siebel School of Computing and Data Science
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Dive into the research topics of 'Submodular function maximization in parallel via the multilinear relaxation'. Together they form a unique fingerprint.
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Keyphrases
Adaptation
25%
Adaptivity
75%
Cardinality
25%
Cardinality Constraint
50%
Continuous Greedy
25%
Coverage Functions
25%
Fractional Solutions
25%
General Constraints
25%
Greedy Algorithm
25%
Knapsack Constraint
25%
Matroid Matching
25%
Monotone Submodular Functions
50%
Multilinear Extension
25%
Multilinear Relaxation
100%
Near-optimal
50%
Or-parallelism
25%
Oracle
25%
Packing Constraint
75%
Parallel Algorithm
50%
Randomized Algorithms
25%
Randomized Rounding
25%
Rounding Scheme
25%
Set Systems
25%
Singer
50%
Submodular Function
25%
Submodular Function Maximization
100%
Computer Science
Approximation (Algorithm)
66%
Cardinality
100%
Greedy Algorithm
33%
Knapsack
33%
Parallel Algorithm
66%
Parallelism
33%
Randomized Algorithm
33%
Mathematics
Cardinality
100%
Greedy Algorithm
33%
Multilinear Extension
33%
Randomized Rounding
33%
Rubinstein
33%