
Improved Learning Bounds for BranchandCut
Branchandcut is the most widely used algorithm for solving integer pro...
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Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond
Cuttingplane methods have enabled remarkable successes in integer progr...
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Generalization in portfoliobased algorithm selection
Portfoliobased algorithm selection has seen tremendous practical succes...
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Private Optimization Without Constraint Violations
We study the problem of differentially private optimization with linear ...
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Refined bounds for algorithm configuration: The knifeedge of dual class approximability
Automating algorithm configuration is growing increasingly necessary as ...
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How much data is sufficient to learn highperforming algorithms?
Algorithms for scientific analysis typically have tunable parameters tha...
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Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees
Algorithms typically come with tunable parameters that have a considerab...
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Learning to Prune: Speeding up Repeated Computations
It is common to encounter situations where one must solve a sequence of ...
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Estimating Approximate Incentive Compatibility
In practice, most mechanisms for selling, buying, matching, voting, and ...
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Learning to Branch
Tree search algorithms, such as branchandbound, are the most widely us...
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LearningTheoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems
Maxcut, clustering, and many other partitioning problems that are of si...
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Ellen Vitercik
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