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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 201–250 of 1277 papers

TitleStatusHype
An End-to-End Reinforcement Learning Based Approach for Micro-View Order-Dispatching in Ride-Hailing—0
GRLinQ: An Intelligent Spectrum Sharing Mechanism for Device-to-Device Communications with Graph Reinforcement Learning—0
Twin Sorting Dynamic Programming Assisted User Association and Wireless Bandwidth Allocation for Hierarchical Federated Learning—0
An Unsupervised Learning Framework Combined with Heuristics for the Maximum Minimal Cut ProblemCode0
Decision-Focused Learning to Predict Action Costs for PlanningCode0
Robust Estimation of Regression Models with Potentially Endogenous Outliers via a Modern Optimization Lens—0
RELIEF: Reinforcement Learning Empowered Graph Feature Prompt TuningCode1
MARCO: A Memory-Augmented Reinforcement Framework for Combinatorial OptimizationCode0
Cool-Fusion: Fuse Large Language Models without Training—0
Modeling Local Search Metaheuristics Using Markov Decision Processes—0
Take a Step and Reconsider: Sequence Decoding for Self-Improved Neural Combinatorial OptimizationCode1
Generalization Bounds of Surrogate Policies for Combinatorial Optimization Problems—0
Enhancing GNNs Performance on Combinatorial Optimization by Recurrent Feature Update—0
Estimating the stability number of a random graph using convolutional neural networksCode0
Generalizing and Unifying Gray-box Combinatorial Optimization Operators—0
PRANCE: Joint Token-Optimization and Structural Channel-Pruning for Adaptive ViT InferenceCode0
VRSD: Rethinking Similarity and Diversity for Retrieval in Large Language Models—0
UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization ProblemsCode2
A Two-stage Reinforcement Learning-based Approach for Multi-entity Task AllocationCode1
DISCO: Efficient Diffusion Solver for Large-Scale Combinatorial Optimization Problems—0
Differentiable Quadratic Optimization For The Maximum Independent Set ProblemCode0
Learning to Remove Cuts in Integer Linear ProgrammingCode0
Beyond Statistical Estimation: Differentially Private Individual Computation via Shuffling—0
Joint Admission Control and Resource Allocation of Virtual Network Embedding via Hierarchical Deep Reinforcement LearningCode2
Link Prediction with Untrained Message Passing Layers—0
Memory-Enhanced Neural Solvers for Efficient Adaptation in Combinatorial OptimizationCode1
Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial OptimizationCode0
GOAL: A Generalist Combinatorial Optimization Agent LearningCode1
Learning to Retrieve Iteratively for In-Context Learning—0
A Benchmark Study of Deep-RL Methods for Maximum Coverage Problems over GraphsCode0
Graph Neural Networks for Job Shop Scheduling Problems: A Survey—0
Combinatorial Reasoning: Selecting Reasons in Generative AI Pipelines via Combinatorial Optimization—0
A Unified Framework for Combinatorial Optimization Based on Graph Neural Networks—0
Coupled Input-Output Dimension Reduction: Application to Goal-oriented Bayesian Experimental Design and Global Sensitivity AnalysisCode0
Archive-based Single-Objective Evolutionary Algorithms for Submodular Optimization—0
Intertwining CP and NLP: The Generation of Unreasonably Constrained Sentences—0
DCILP: A Distributed Approach for Large-Scale Causal Structure Learning—0
A Benchmark for Maximum Cut: Towards Standardization of the Evaluation of Learned Heuristics for Combinatorial OptimizationCode0
Learning Solution-Aware Transformers for Efficiently Solving Quadratic Assignment ProblemCode1
Deep Symbolic Optimization for Combinatorial Optimization: Accelerating Node Selection by Discovering Potential HeuristicsCode0
Injecting Combinatorial Optimization into MCTS: Application to the Board Game boopCode0
A topological analysis of the space of recipes—0
CHARME: A chain-based reinforcement learning approach for the minor embedding problem—0
Distributional MIPLIB: a Multi-Domain Library for Advancing ML-Guided MILP MethodsCode0
GFPack++: Improving 2D Irregular Packing by Learning Gradient Field with Attention—0
Distributed Combinatorial Optimization of Downlink User Assignment in mmWave Cell-free Massive MIMO Using Graph Neural Networks—0
Large Language Model Assisted Adversarial Robustness Neural Architecture SearchCode0
ON-OFF Neuromorphic ISING Machines using Fowler-Nordheim Annealers—0
Decision-focused Graph Neural Networks for Combinatorial Optimization—0
Combinatorial Optimization with Automated Graph Neural NetworksCode2
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