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Combinatorial Optimization

Combinatorial Optimization is a category of problems which requires optimizing a function over a combination of discrete objects and the solutions are constrained. Examples include finding shortest paths in a graph, maximizing value in the Knapsack problem and finding boolean settings that satisfy a set of constraints. Many of these problems are NP-Hard, which means that no polynomial time solution can be developed for them. Instead, we can only produce approximations in polynomial time that are guaranteed to be some factor worse than the true optimal solution.

Source: Recent Advances in Neural Program Synthesis

Papers

Showing 271280 of 1277 papers

TitleStatusHype
An adaptive simulated annealing EM algorithm for inference on non-homogeneous hidden Markov modelsCode0
Futureproof Static Memory PlanningCode0
Graph Adversarial Immunization for Certifiable RobustnessCode0
FIS-ONE: Floor Identification System with One Label for Crowdsourced RF SignalsCode0
Flex-Net: A Graph Neural Network Approach to Resource Management in Flexible Duplex NetworksCode0
Fast Parallel Algorithms for Statistical Subset Selection ProblemsCode0
FastCover: An Unsupervised Learning Framework for Multi-Hop Influence Maximization in Social NetworksCode0
Differentiating Through Integer Linear Programs with Quadratic Regularization and Davis-Yin SplittingCode0
Attack Graph ObfuscationCode0
Fast Graph-Cut Based Optimization for Practical Dense Deformable Registration of Volume ImagesCode0
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