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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 201225 of 1277 papers

TitleStatusHype
Learning Geometric Combinatorial Optimization Problems using Self-attention and Domain KnowledgeCode0
A Benchmark Study of Deep-RL Methods for Maximum Coverage Problems over GraphsCode0
Learning-Based Heuristic for Combinatorial Optimization of the Minimum Dominating Set Problem using Graph Convolutional NetworksCode0
LAWS: Look Around and Warm-Start Natural Gradient Descent for Quantum Neural NetworksCode0
Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple PartitionsCode0
A Formal Perspective on Byte-Pair EncodingCode0
Learnable Evolutionary Multi-Objective Combinatorial Optimization via Sequence-to-Sequence ModelCode0
Learning-based Online Optimization for Autonomous Mobility-on-Demand Fleet ControlCode0
Lagrange Oscillatory Neural Networks for Constraint Satisfaction and OptimizationCode0
Joint Graph Decomposition and Node Labeling: Problem, Algorithms, ApplicationsCode0
Large Language Model Assisted Adversarial Robustness Neural Architecture SearchCode0
Intelligent Channel Allocation for IEEE 802.11be Multi-Link Operation: When MAB Meets LLMCode0
Structural Causal Models Reveal Confounder Bias in Linear Program ModellingCode0
Instance-Conditioned Adaptation for Large-scale Generalization of Neural Routing SolverCode0
Improving Optimization Bounds using Machine Learning: Decision Diagrams meet Deep Reinforcement LearningCode0
Causal Discovery with Reinforcement LearningCode0
Implementing a GPU-based parallel MAX-MIN Ant SystemCode0
Interferometric Neural NetworksCode0
Implementation of digital MemComputing using standard electronic componentsCode0
How to Evaluate Machine Learning Approaches for Combinatorial Optimization: Application to the Travelling Salesman ProblemCode0
Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment ProblemCode0
LeadCache: Regret-Optimal Caching in NetworksCode0
A Benchmark for Maximum Cut: Towards Standardization of the Evaluation of Learned Heuristics for Combinatorial OptimizationCode0
Injecting Combinatorial Optimization into MCTS: Application to the Board Game boopCode0
Large Neighborhood Prioritized Search for Combinatorial Optimization with Answer Set ProgrammingCode0
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