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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
Bridging Visualization and Optimization: Multimodal Large Language Models on Graph-Structured Combinatorial Optimization—0
Fast instance-specific algorithm configuration with graph neural network—0
Neural Algorithmic Reasoning for Hypergraphs with Looped Transformers—0
Convergence and Running Time of Time-dependent Ant Colony Algorithms—0
Random-Key Algorithms for Optimizing Integrated Operating Room Scheduling—0
Multiple-gain Estimation for Running Time of Evolutionary Combinatorial Optimization—0
Pareto Optimization with Robust Evaluation for Noisy Subset Selection—0
Annealing Machine-assisted Learning of Graph Neural Network for Combinatorial Optimization—0
Self-Adaptive Ising Machines for Constrained OptimizationCode0
Transfer Learning for Deep-Unfolded Combinatorial Optimization Solver with Quantum Annealer—0
Improved Approximation Algorithms for Low-Rank Problems Using Semidefinite Optimization—0
Relaxation-assisted reverse annealing on nonnegative/binary matrix factorization—0
Adaptive Non-Uniform Timestep Sampling for Accelerating Diffusion Model Training—0
Investigating layer-selective transfer learning of QAOA parameters for Max-Cut problem—0
Scalable Quantum-Inspired Optimization through Dynamic Qubit Compression—0
On Enhancing Network Throughput using Reinforcement Learning in Sliced Testbeds—0
Multi-task Representation Learning for Mixed Integer Linear ProgrammingCode0
LLMs for Cold-Start Cutting Plane Separator ConfigurationCode0
Concept Learning in the Wild: Towards Algorithmic Understanding of Neural Networks—0
Scaling Combinatorial Optimization Neural Improvement Heuristics with Online Search and Adaptation—0
Brain-inspired Chaotic Graph Backpropagation for Large-scale Combinatorial Optimization—0
DistrictNet: Decision-aware learning for geographical districtingCode0
Learnable Evolutionary Multi-Objective Combinatorial Optimization via Sequence-to-Sequence ModelCode0
XKV: Personalized KV Cache Memory Reduction for Long-Context LLM Inference—0
SizeGS: Size-aware Compression of 3D Gaussians with Hierarchical Mixed Precision Quantization—0
LIAR: Leveraging Alignment (Best-of-N) to Jailbreak LLMs in Seconds—0
CaDA: Cross-Problem Routing Solver with Constraint-Aware Dual-Attention—0
Scalable iterative pruning of large language and vision models using block coordinate descent—0
Approximation Algorithms for Combinatorial Optimization with PredictionsCode0
Large Language Models for Combinatorial Optimization of Design Structure Matrix—0
Design And Optimization Of Multi-rendezvous Manoeuvres Based On Reinforcement Learning And Convex Optimization—0
Liner Shipping Network Design with Reinforcement Learning—0
Neuro-Symbolic Rule Lists—0
MBL-CPDP: A Multi-objective Bilevel Method for Cross-Project Defect Prediction via Automated Machine Learning—0
Learn to Solve Vehicle Routing Problems ASAP: A Neural Optimization Approach for Time-Constrained Vehicle Routing Problems with Finite Vehicle Fleet—0
Assessing and Enhancing Graph Neural Networks for Combinatorial Optimization: Novel Approaches and Application in Maximum Independent Set Problems—0
A Random-Key Optimizer for Combinatorial Optimization—0
Neural Networks and (Virtual) Extended Formulations—0
Deep memetic models for combinatorial optimization problems: application to the tool switching problem—0
Towards Geometry-Preserving Reductions Between Constraint Satisfaction Problems (and other problems in NP)—0
Multi-IRS Enhanced Wireless Coverage: Deployment Optimization Based on Large-Scale Channel Knowledge—0
Theoretically Grounded Pruning of Large Ground Sets for Constrained, Discrete Optimization—0
Permutation Picture of Graph Combinatorial Optimization Problems—0
Offline reinforcement learning for job-shop scheduling problems—0
Enhancing In-vehicle Multiple Object Tracking Systems with Embeddable Ising Machines—0
Selection of Filters for Photonic Crystal Spectrometer Using Domain-Aware Evolutionary Algorithms—0
Initialization Method for Factorization Machine Based on Low-Rank Approximation for Constructing a Corrected Approximate Ising Model—0
Unsupervised Training of Diffusion Models for Feasible Solution Generation in Neural Combinatorial Optimization—0
Neural Solver Selection for Combinatorial OptimizationCode0
Combinatorial optimization of the coefficient of determinationCode0
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