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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 501–550 of 1277 papers

TitleStatusHype
Self-averaging of digital memcomputing machinesCode0
Quantum HyperNetworks: Training Binary Neural Networks in Quantum SuperpositionCode1
Efficient correlation-based discretization of continuous variables for annealing machines—0
A Combinatorial Semi-Bandit Approach to Charging Station Selection for Electric Vehicles—0
BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial OptimizationCode1
Unsupervised Learning for Combinatorial Optimization Needs Meta-LearningCode0
Mathematical Models and Reinforcement Learning based Evolutionary Algorithm Framework for Satellite Scheduling Problem—0
PA-GM: Position-Aware Learning of Embedding Networks for Deep Graph Matching—0
A machine learning framework for neighbor generation in metaheuristic search—0
A Local Optima Network View of Real Function Fitness Landscapes—0
Local Branching Relaxation Heuristics for Integer Linear Programs—0
Learning to repeatedly solve routing problems—0
Security Defense of Large Scale Networks Under False Data Injection Attacks: An Attack Detection Scheduling Approach—0
Walkability Optimization: Formulations, Algorithms, and a Case Study of TorontoCode0
Multi-Objective Linear Ensembles for Robust and Sparse Training of Few-Bit Neural NetworksCode0
Efficient Optimization with Higher-Order Ising Machines—0
Reinforcement Learning for Multi-Truck Vehicle Routing Problems—0
Fast Hyperparameter Tuning for Ising Machines—0
Reinforced Genetic Algorithm for Structure-based Drug DesignCode1
Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls—0
Domain-Independent Dynamic Programming: Generic State Space Search for Combinatorial OptimizationCode1
Learning Branching Heuristics from Graph Neural Networks—0
Arbitrarily Large Labelled Random Satisfiability Formulas for Machine Learning Training—0
Optimal Discrete Beamforming of RIS-Aided Wireless Communications: An Inner Product Maximization ApproachCode1
Deep Causal Learning: Representation, Discovery and Inference—0
A Survey on Influence Maximization: From an ML-Based Combinatorial Optimization—0
Feature Selection for Classification with QAOA—0
Balancing Utility and Fairness in Submodular Maximization (Technical Report)Code0
Learning Adaptive Evolutionary Computation for Solving Multi-Objective Optimization Problems—0
Online Control of Adaptive Large Neighborhood Search using Deep Reinforcement LearningCode1
Differentiable Model Selection for Ensemble LearningCode0
Binary sequence set optimization for CDMA applications via mixed-integer quadratic programming—0
Artificial Potential Field-Based Path Planning for Cluttered EnvironmentsCode0
Learning Heuristics for the Maximum Clique Enumeration Problem Using Low Dimensional Representations—0
End-to-End Pareto Set Prediction with Graph Neural Networks for Multi-objective Facility Location—0
Learning Discrete Directed Acyclic Graphs via Backpropagation—0
Revealed Preferences of One-Sided Matching—0
Sub-network Multi-objective Evolutionary Algorithm for Filter Pruning—0
NeuroPrim: An Attention-based Model for Solving NP-hard Spanning Tree ProblemsCode0
SurCo: Learning Linear Surrogates For Combinatorial Nonlinear Optimization Problems—0
Graph Coloring via Neural Networks for Haplotype Assembly and Viral Quasispecies ReconstructionCode0
Application of Decision Tree Classifier in Detection of Specific Denial of Service Attacks with Genetic Algorithm Based Feature Selection on NSL-KDD—0
Towards Practical Explainability with Cluster Descriptors—0
Navigating Memory Construction by Global Pseudo-Task Simulation for Continual LearningCode0
Theory and Approximate Solvers for Branched Optimal Transport with Multiple SourcesCode1
ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement LearningCode1
Travel the Same Path: A Novel TSP Solving StrategyCode0
Finding and Exploring Promising Search Space for the 0-1 Multidimensional Knapsack Problem—0
DIMES: A Differentiable Meta Solver for Combinatorial Optimization ProblemsCode1
Winner Takes It All: Training Performant RL Populations for Combinatorial OptimizationCode1
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