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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 301–350 of 1277 papers

TitleStatusHype
Efficient Combinatorial Optimization via Heat DiffusionCode0
Deep Reinforcement Learning for Modelling Protein Complexes—0
Ant Colony Sampling with GFlowNets for Combinatorial OptimizationCode2
FALCON: FLOP-Aware Combinatorial Optimization for Neural Network PruningCode0
An Efficient Learning-based Solver Comparable to Metaheuristics for the Capacitated Arc Routing Problem—0
RouteExplainer: An Explanation Framework for Vehicle Routing ProblemCode1
AcceleratedLiNGAM: Learning Causal DAGs at the speed of GPUsCode0
Graph Learning for Parameter Prediction of Quantum Approximate Optimization Algorithm—0
Where the Really Hard Quadratic Assignment Problems Are: the QAP-SAT instancesCode0
Learning to Solve Job Shop Scheduling under UncertaintyCode2
How Multimodal Integration Boost the Performance of LLM for Optimization: Case Study on Capacitated Vehicle Routing Problems—0
MMSR: Symbolic Regression is a Multi-Modal Information Fusion TaskCode1
SequentialAttention++ for Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization—0
Box Facets and Cut Facets of Lifted Multicut Polytopes—0
Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot GeneralizationCode1
Towards Principled Task Grouping for Multi-Task Learning—0
Nonlinear Bayesian optimal experimental design using logarithmic Sobolev inequalities—0
Reasoning Algorithmically in Graph Neural Networks—0
PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization—0
Convergence Acceleration of Markov Chain Monte Carlo-based Gradient Descent by Deep Unfolding—0
RITFIS: Robust input testing framework for LLMs-based intelligent software—0
Large Scale Constrained Clustering With Reinforcement Learning—0
Risk-Sensitive Soft Actor-Critic for Robust Deep Reinforcement Learning under Distribution ShiftsCode0
Low-Rank Extragradient Methods for Scalable Semidefinite Optimization—0
Assortment Planning with Sponsored Products—0
Majority Kernels: An Approach to Leverage Big Model Dynamics for Efficient Small Model Training—0
Moco: A Learnable Meta Optimizer for Combinatorial OptimizationCode1
Effective anytime algorithm for multiobjective combinatorial optimization problems—0
torchmSAT: A GPU-Accelerated Approximation To The Maximum Satisfiability Problem—0
Accelerating Matroid Optimization through Fast Imprecise Oracles—0
Continuous Tensor Relaxation for Finding Diverse Solutions in Combinatorial Optimization Problems—0
ReEvo: Large Language Models as Hyper-Heuristics with Reflective EvolutionCode3
Manipulating Predictions over Discrete Inputs in Machine Teaching—0
Attention-based Reinforcement Learning for Combinatorial Optimization: Application to Job Shop Scheduling Problem—0
Domain-Independent Dynamic ProgrammingCode2
Quantum-Inspired Machine Learning for Molecular Docking—0
Simulation Based Bayesian OptimizationCode0
Decentralizing Coordination in Open Vehicle Fleets for Scalable and Dynamic Task Allocation—0
Power System Fault Diagnosis with Quantum Computing and Efficient Gate Decomposition—0
Graph Q-Learning for Combinatorial Optimization—0
Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language ModelCode3
Quantum-Hybrid Stereo Matching With Nonlinear Regularization and Spatial Pyramids—0
OsmLocator: locating overlapping scatter marks with a non-training generative perspectiveCode0
NN-Steiner: A Mixed Neural-algorithmic Approach for the Rectilinear Steiner Minimum Tree Problem—0
A Unified Pre-training and Adaptation Framework for Combinatorial Optimization on Graphs—0
COMBHelper: A Neural Approach to Reduce Search Space for Graph Combinatorial ProblemsCode0
Symmetry Breaking and Equivariant Neural Networks—0
A Simulated Annealing-Based Multiobjective Optimization Algorithm for Minimum Weight Minimum Connected Dominating Set Problem—0
Machine Learning for the Multi-Dimensional Bin Packing Problem: Literature Review and Empirical Evaluation—0
A Novel Differentiable Loss Function for Unsupervised Graph Neural Networks in Graph Partitioning—0
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