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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 151–200 of 1277 papers

TitleStatusHype
DAG Matters! GFlowNets Enhanced Explainer For Graph Neural NetworksCode1
D2Match: Leveraging Deep Learning and Degeneracy for Subgraph MatchingCode1
Maximum Entropy Weighted Independent Set Pooling for Graph Neural NetworksCode1
Memory-Enhanced Neural Solvers for Efficient Adaptation in Combinatorial OptimizationCode1
DeepACO: Neural-enhanced Ant Systems for Combinatorial OptimizationCode1
MIP-GNN: A Data-Driven Framework for Guiding Combinatorial SolversCode1
Deep Boltzmann Machines in Estimation of Distribution Algorithms for Combinatorial OptimizationCode1
Deep Graph Matching via Blackbox Differentiation of Combinatorial SolversCode1
Learning Large Neighborhood Search for Vehicle Routing in Airport Ground HandlingCode1
Combining Reinforcement Learning and Constraint Programming for Combinatorial OptimizationCode1
Attention, Learn to Solve Routing Problems!Code1
Denoising Autoencoders for fast Combinatorial Black Box OptimizationCode1
DHRL-FNMR: An Intelligent Multicast Routing Approach Based on Deep Hierarchical Reinforcement Learning in SDNCode1
RELIEF: Reinforcement Learning Empowered Graph Feature Prompt TuningCode1
Learning a Large Neighborhood Search Algorithm for Mixed Integer ProgramsCode1
A Two-stage Reinforcement Learning-based Approach for Multi-entity Task AllocationCode1
Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization SolversCode1
Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling ProblemsCode1
Learning Primal Heuristics for Mixed Integer ProgramsCode1
Domain-Independent Dynamic Programming: Generic State Space Search for Combinatorial OptimizationCode1
A Deep Instance Generative Framework for MILP Solvers Under Limited Data AvailabilityCode1
Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale GeneralizationCode1
Dynamic Partial Removal: A Neural Network Heuristic for Large Neighborhood SearchCode1
Noisy intermediate-scale quantum algorithm for semidefinite programmingCode1
A Deep Reinforcement Learning Algorithm Using Dynamic Attention Model for Vehicle Routing ProblemsCode1
Automatic Truss Design with Reinforcement LearningCode1
Efficient Joint Optimization of Layer-Adaptive Weight Pruning in Deep Neural NetworksCode1
Parallel AutoRegressive Models for Multi-Agent Combinatorial OptimizationCode1
Learning to Solve Combinatorial Optimization under Positive Linear Constraints via Non-Autoregressive Neural NetworksCode1
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock PredictionCode1
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock PredictionsCode1
POMO: Policy Optimization with Multiple Optima for Reinforcement LearningCode1
Equivariant quantum circuits for learning on weighted graphsCode1
RAMA: A Rapid Multicut Algorithm on GPUCode1
Balans: Multi-Armed Bandits-based Adaptive Large Neighborhood Search for Mixed-Integer Programming ProblemCode1
Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on GraphsCode1
Learning What to Defer for Maximum Independent SetsCode1
Beyond the Heatmap: A Rigorous Evaluation of Component Impact in MCTS-Based TSP SolversCode1
Exact Combinatorial Optimization with Graph Convolutional Neural NetworksCode1
Reinforced Lin-Kernighan-Helsgaun Algorithms for the Traveling Salesman ProblemsCode1
Belief Propagation Neural NetworksCode1
An End-to-End Reinforcement Learning Approach for Job-Shop Scheduling Problems Based on Constraint ProgrammingCode1
Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment ProblemCode0
Joint Graph Decomposition and Node Labeling: Problem, Algorithms, ApplicationsCode0
Lagrange Oscillatory Neural Networks for Constraint Satisfaction and OptimizationCode0
An Unsupervised Learning Framework Combined with Heuristics for the Maximum Minimal Cut ProblemCode0
Ants can orienteer a thief in their robberyCode0
Structural Causal Models Reveal Confounder Bias in Linear Program ModellingCode0
Interferometric Neural NetworksCode0
Large Language Model Assisted Adversarial Robustness Neural Architecture SearchCode0
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