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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

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Showing 1126–1150 of 1277 papers

TitleStatusHype
Hierarchical Clustering: Objective Functions and Algorithms—0
Learning Combinatorial Optimization Algorithms over GraphsCode0
A Branch-and-Bound Algorithm for Checkerboard Extraction in Camera-Laser Calibration—0
Experimental Analysis of Design Elements of Scalarizing Functions-based Multiobjective Evolutionary Algorithms—0
Métodos de Otimização Combinatória Aplicados ao Problema de Compressão MultiFrases—0
On Approximation Guarantees for Greedy Low Rank Optimization—0
A Knowledge-Based Approach to Word Sense Disambiguation by distributional selection and semantic features—0
Tight Bounds for Bandit Combinatorial Optimization—0
A Hybrid Evolutionary Algorithm Based on Solution Merging for the Longest Arc-Preserving Common Subsequence Problem—0
Shape Estimation from Defocus Cue for Microscopy Images via Belief Propagation—0
Solving Combinatorial Optimization problems with Quantum inspired Evolutionary Algorithm Tuned using a Novel Heuristic Method—0
Neural Combinatorial Optimization with Reinforcement LearningCode1
Maximizing Non-Monotone DR-Submodular Functions with Cardinality Constraints—0
Joint Graph Decomposition and Node Labeling: Problem, Algorithms, ApplicationsCode0
Recursive Decomposition for Nonconvex Optimization—0
Heuristic with elements of tabu search for Truck and Trailer Routing Problem—0
Duality between Feature Selection and Data Clustering—0
On the Mathematical Relationship between Expected n-call@k and the Relevance vs. Diversity Trade-off—0
A Tutorial about Random Neural Networks in Supervised Learning—0
A Generic Bet-and-run Strategy for Speeding Up Traveling Salesperson and Minimum Vertex Cover—0
A case study of algorithm selection for the traveling thief problem—0
MindX: Denoising Mixed Impulse Poisson-Gaussian Noise Using Proximal Algorithms—0
Parameter Learning for Log-supermodular Distributions—0
How to calculate partition functions using convex programming hierarchies: provable bounds for variational methods—0
Pruning Random Forests for Prediction on a Budget—0
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