SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 126–150 of 1277 papers

TitleStatusHype
Decision-Focused Learning: Through the Lens of Learning to RankCode1
BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial OptimizationCode1
A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics NetworkCode1
CLIPPER: A Graph-Theoretic Framework for Robust Data AssociationCode1
Combinatorial Optimization enriched Machine Learning to solve the Dynamic Vehicle Routing Problem with Time WindowsCode1
Balans: Multi-Armed Bandits-based Adaptive Large Neighborhood Search for Mixed-Integer Programming ProblemCode1
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock PredictionsCode1
CO-Bench: Benchmarking Language Model Agents in Algorithm Search for Combinatorial OptimizationCode1
Belief Propagation Neural NetworksCode1
Combinatorial Optimization Perspective based Framework for Multi-behavior RecommendationCode1
Automatic Truss Design with Reinforcement LearningCode1
Combinatorial Optimization with Physics-Inspired Graph Neural NetworksCode1
Combinatorial Optimization with Policy Adaptation using Latent Space SearchCode1
Are Graph Neural Networks Optimal Approximation Algorithms?Code1
A Reinforcement Learning Approach to the Orienteering Problem with Time WindowsCode1
A Reinforcement Learning Environment For Job-Shop SchedulingCode1
Contingency-Aware Influence Maximization: A Reinforcement Learning ApproachCode1
RELIEF: Reinforcement Learning Empowered Graph Feature Prompt TuningCode1
Deep Boltzmann Machines in Estimation of Distribution Algorithms for Combinatorial OptimizationCode1
A Learning-based Iterative Method for Solving Vehicle Routing ProblemsCode1
ASP: Learn a Universal Neural Solver!Code1
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock PredictionCode1
DHRL-FNMR: An Intelligent Multicast Routing Approach Based on Deep Hierarchical Reinforcement Learning in SDNCode1
BILP-Q: Quantum Coalition Structure GenerationCode1
Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable ApproachCode1
Show:102550
← PrevPage 6 of 52Next →

No leaderboard results yet.