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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 226–250 of 1277 papers

TitleStatusHype
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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