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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 951–975 of 1277 papers

TitleStatusHype
A Deep Reinforcement Learning Algorithm Using Dynamic Attention Model for Vehicle Routing ProblemsCode1
Fair Correlation ClusteringCode0
Bayesian Meta-Prior Learning Using Empirical Bayes—0
Accelerating Quantum Approximate Optimization Algorithm using Machine Learning—0
WiSM: Windowing Surrogate Model for Evaluation of Curvature-Constrained Tours with Dubins vehicle—0
A Class of Linear Programs Solvable by Coordinate-Wise Minimization—0
Discrete graphical models -- an optimization perspective—0
On the Performance of Metaheuristics: A Different Perspective—0
Runtime Performances of Randomized Search Heuristics for the Dynamic Weighted Vertex Cover Problem—0
Implementing a GPU-based parallel MAX-MIN Ant SystemCode0
Graph Ordering: Towards the Optimal by Learning—0
Parameterized Complexity Analysis of Randomized Search Heuristics—0
High-Level Plan for Behavioral Robot Navigation with Natural Language Directions and R-NET—0
Clustering Binary Data by Application of Combinatorial Optimization Heuristics—0
Learning fine-grained search space pruning and heuristics for combinatorial optimization—0
A Probability Density Theory for Spin-Glass Systems—0
Targeted sampling of enlarged neighborhood via Monte Carlo tree search for TSPCode1
An adaptive simulated annealing EM algorithm for inference on non-homogeneous hidden Markov modelsCode0
Estudo comparativo de meta-heurísticas para problemas de colorações de grafos—0
Quantum-inspired annealers as Boltzmann generators for machine learning and statistical physics—0
Provable Non-Convex Optimization and Algorithm Validation via Submodularity—0
Theory of neuromorphic computing by waves: machine learning by rogue waves, dispersive shocks, and solitons—0
Learning to Dynamically Coordinate Multi-Robot Teams in Graph Attention Networks—0
Protecting Geolocation Privacy of Photo CollectionsCode0
Improved Regret Bounds for Bandit Combinatorial Optimization—0
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