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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 1151–1200 of 1277 papers

TitleStatusHype
Dynamic Submodular Maximization—0
EALG: Evolutionary Adversarial Generation of Language Model-Guided Generators for Combinatorial Optimization—0
Early years of Biased Random-Key Genetic Algorithms: A systematic review—0
EB-GLS: An Improved Guided Local Search Based on the Big Valley Structure—0
Effective anytime algorithm for multiobjective combinatorial optimization problems—0
Effective Features of Remote Sensing Image Classification Using Interactive Adaptive Thresholding Method—0
Efficient 3D Endfiring TRUS Prostate Segmentation with Globally Optimized Rotational Symmetry—0
Efficient Algorithms for Adversarial Contextual Learning—0
Efficient Combinatorial Optimization for Word-level Adversarial Textual Attack—0
Decomposed Quadratization: Efficient QUBO Formulation for Learning Bayesian Network—0
Efficient correlation-based discretization of continuous variables for annealing machines—0
Efficient LDPC Decoding using Physical Computation—0
Efficient learning by implicit exploration in bandit problems with side observations—0
Efficiently Factorizing Boolean Matrices using Proximal Gradient Descent—0
Efficient Optimization Accelerator Framework for Multistate Ising Problems—0
Efficient Optimization with Higher-Order Ising Machines—0
Efficient Training of Multi-task Combinarotial Neural Solver with Multi-armed Bandits—0
Embed and Project: Discrete Sampling with Universal Hashing—0
End-to-End Efficient Representation Learning via Cascading Combinatorial Optimization—0
End-to-End Pareto Set Prediction with Graph Neural Networks for Multi-objective Facility Location—0
End-to-end Planning of Fixed Millimeter-Wave Networks—0
Energy Minimization in UAV-Aided Networks: Actor-Critic Learning for Constrained Scheduling Optimization—0
Enhancing Column Generation by Reinforcement Learning-Based Hyper-Heuristic for Vehicle Routing and Scheduling Problems—0
Enhancing GNNs Performance on Combinatorial Optimization by Recurrent Feature Update—0
Enhancing In-vehicle Multiple Object Tracking Systems with Embeddable Ising Machines—0
Enhancing Network Resilience through Machine Learning-powered Graph Combinatorial Optimization: Applications in Cyber Defense and Information Diffusion—0
Enhancing Robustness of Neural Networks through Fourier Stabilization—0
Enhancing variational quantum algorithms by balancing training on classical and quantum hardware—0
Entity Summarization: State of the Art and Future Challenges—0
Equivariant neural networks for recovery of Hadamard matrices—0
ERL-MPP: Evolutionary Reinforcement Learning with Multi-head Puzzle Perception for Solving Large-scale Jigsaw Puzzles of Eroded Gaps—0
Estimation of the yield curve for Costa Rica using combinatorial optimization metaheuristics applied to nonlinear regression—0
Estudo comparativo de meta-heurísticas para problemas de colorações de grafos—0
Evaluating Curriculum Learning Strategies in Neural Combinatorial Optimization—0
Evaluation of bioinspired algorithms for the solution of the job scheduling problem—0
Evolutionary Approach for the Containers Bin-Packing Problem—0
Evolutionary Bi-objective Optimization for the Dynamic Chance-Constrained Knapsack Problem Based on Tail Bound Objectives—0
Evolutionary Construction of Perfectly Balanced Boolean Functions—0
Evolutionary Multi-Objective Algorithms for the Knapsack Problems with Stochastic Profits—0
Evolutionary RL for Container Loading—0
Evolution as a Service: A Privacy-Preserving Genetic Algorithm for Combinatorial Optimization—0
Evolving Hard Maximum Cut Instances for Quantum Approximate Optimization Algorithms—0
Exact and Approximate Hierarchical Clustering Using A*—0
Exact and heuristic methods for the discrete parallel machine scheduling location problem—0
Exact Combinatorial Optimization with Temporo-Attentional Graph Neural Networks—0
Exact Spin Elimination in Ising Hamiltonians and Energy-Based Machine Learning—0
Expediting Distributed DNN Training with Device Topology-Aware Graph Deployment—0
Experimental Analysis of Design Elements of Scalarizing Functions-based Multiobjective Evolutionary Algorithms—0
Experiments with graph convolutional networks for solving the vertex p-center problem—0
Exploiting Problem Structure in Combinatorial Landscapes: A Case Study on Pure Mathematics Application—0
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