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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 526550 of 1277 papers

TitleStatusHype
A Survey on Influence Maximization: From an ML-Based Combinatorial Optimization0
Feature Selection for Classification with QAOA0
Balancing Utility and Fairness in Submodular Maximization (Technical Report)Code0
Learning Adaptive Evolutionary Computation for Solving Multi-Objective Optimization Problems0
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 programming0
Artificial Potential Field-Based Path Planning for Cluttered EnvironmentsCode0
Learning Heuristics for the Maximum Clique Enumeration Problem Using Low Dimensional Representations0
End-to-End Pareto Set Prediction with Graph Neural Networks for Multi-objective Facility Location0
Learning Discrete Directed Acyclic Graphs via Backpropagation0
Revealed Preferences of One-Sided Matching0
Sub-network Multi-objective Evolutionary Algorithm for Filter Pruning0
NeuroPrim: An Attention-based Model for Solving NP-hard Spanning Tree ProblemsCode0
SurCo: Learning Linear Surrogates For Combinatorial Nonlinear Optimization Problems0
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-KDD0
Towards Practical Explainability with Cluster Descriptors0
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 Problem0
DIMES: A Differentiable Meta Solver for Combinatorial Optimization ProblemsCode1
Winner Takes It All: Training Performant RL Populations for Combinatorial OptimizationCode1
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