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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 11311140 of 1277 papers

TitleStatusHype
Hierarchical Clustering: Objective Functions and Algorithms0
Learning Combinatorial Optimization Algorithms over GraphsCode0
A Branch-and-Bound Algorithm for Checkerboard Extraction in Camera-Laser Calibration0
Experimental Analysis of Design Elements of Scalarizing Functions-based Multiobjective Evolutionary Algorithms0
Métodos de Otimização Combinatória Aplicados ao Problema de Compressão MultiFrases0
On Approximation Guarantees for Greedy Low Rank Optimization0
A Knowledge-Based Approach to Word Sense Disambiguation by distributional selection and semantic features0
Tight Bounds for Bandit Combinatorial Optimization0
A Hybrid Evolutionary Algorithm Based on Solution Merging for the Longest Arc-Preserving Common Subsequence Problem0
Shape Estimation from Defocus Cue for Microscopy Images via Belief Propagation0
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