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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 11261150 of 1277 papers

TitleStatusHype
Injecting Combinatorial Optimization into MCTS: Application to the Board Game boopCode0
Supplementing Recurrent Neural Networks with Annealing to Solve Combinatorial Optimization ProblemsCode0
Budget-Aware Sequential Brick Assembly with Efficient Constraint SatisfactionCode0
Improving Optimization Bounds using Machine Learning: Decision Diagrams meet Deep Reinforcement LearningCode0
Offline Reinforcement Learning for Learning to Dispatch for Job Shop SchedulingCode0
A Formal Perspective on Byte-Pair EncodingCode0
Diversity-Driven View Subset Selection for Indoor Novel View SynthesisCode0
DeciLS-PBO: an Effective Local Search Method for Pseudo-Boolean OptimizationCode0
Regret in Online Combinatorial OptimizationCode0
A Benchmark for Maximum Cut: Towards Standardization of the Evaluation of Learned Heuristics for Combinatorial OptimizationCode0
One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint SatisfactionCode0
Learning to Optimize Variational Quantum Circuits to Solve Combinatorial ProblemsCode0
Ecole: A Library for Learning Inside MILP SolversCode0
Understanding Boolean Function Learnability on Deep Neural Networks: PAC Learning Meets Neurosymbolic ModelsCode0
Regularized Langevin Dynamics for Combinatorial OptimizationCode0
Learning to Remove Cuts in Integer Linear ProgrammingCode0
Reheated Gradient-based Discrete Sampling for Combinatorial OptimizationCode0
Differentiable Quadratic Optimization For The Maximum Independent Set ProblemCode0
Chance-Constrained Multiple-Choice Knapsack Problem: Model, Algorithms, and ApplicationsCode0
Automated quantum programming via reinforcement learning for combinatorial optimizationCode0
Reinforcement Learning Assisted Recursive QAOACode0
Reinforcement Learning-based Heuristics to Guide Domain-Independent Dynamic ProgrammingCode0
Attack Graph ObfuscationCode0
Curriculum learning for multilevel budgeted combinatorial problemsCode0
Implementing a GPU-based parallel MAX-MIN Ant SystemCode0
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