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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 1051–1100 of 1277 papers

TitleStatusHype
Learning Heuristics over Large Graphs via Deep Reinforcement LearningCode0
Attack Graph ObfuscationCode0
Fast Parallel Algorithms for Statistical Subset Selection ProblemsCode0
A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics NetworkCode1
End-to-End Efficient Representation Learning via Cascading Combinatorial Optimization—0
Optimal and Fast Real-time Resources Slicing with Deep Dueling Neural Networks—0
First-Order Bayesian Regret Analysis of Thompson Sampling—0
Constrained optimization under uncertainty for decision-making problems: Application to Real-Time Strategy gamesCode0
Exploiting Problem Structure in Combinatorial Landscapes: A Case Study on Pure Mathematics Application—0
Algorithms Inspired by Nature: A Survey—0
Mixed Uncertainty Sets for Robust Combinatorial Optimization—0
Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizon—0
Scalable Robust Kidney ExchangeCode0
Dynamic Assortment Optimization with Changing Contextual Information—0
Differentiable Greedy Networks—0
Combinatorial Optimization with Graph Convolutional Networks and Guided Tree SearchCode1
MS-BACO: A new Model Selection algorithm using Binary Ant Colony Optimization for neural complexity and error reduction—0
Fast Graph-Cut Based Optimization for Practical Dense Deformable Registration of Volume ImagesCode0
Learning to Perform Local Rewriting for Combinatorial OptimizationCode0
Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization—0
Learning-based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set MatchingCode0
Improving Optimization Bounds using Machine Learning: Decision Diagrams meet Deep Reinforcement LearningCode0
MRF Optimization with Separable Convex Prior on Partially Ordered Labels—0
Algoritmos Genéticos Aplicado ao Problema de Roteamento de Veículos—0
Parallelization does not Accelerate Convex Optimization: Adaptivity Lower Bounds for Non-smooth Convex Minimization—0
An Iterative Path-Breaking Approach with Mutation and Restart Strategies for the MAX-SAT Problem—0
Towards fully automated protein structure elucidation with NMR spectroscopy—0
An Approximation Algorithm for Risk-averse Submodular Optimization—0
Boosting Combinatorial Problem Modeling with Machine Learning—0
Memory Augmented Policy Optimization for Program Synthesis and Semantic ParsingCode0
Ranked Reward: Enabling Self-Play Reinforcement Learning for Combinatorial OptimizationCode0
Automatic Rank Selection for High-Speed Convolutional Neural Network—0
Quit When You Can: Efficient Evaluation of Ensembles with Ordering Optimization—0
Deep Learning of Graph Matching—0
INGEOTEC at SemEval-2018 Task 1: EvoMSA and μTC for Sentiment Analysis—0
Generic CP-Supported CMSA for Binary Integer Linear Programs—0
A novel channel pruning method for deep neural network compression—0
Safe Element Screening for Submodular Function Minimization—0
Solving the Rubik's Cube Without Human KnowledgeCode0
Evolutionary RL for Container Loading—0
Recent Progress on Graph Partitioning Problems Using Evolutionary Computation—0
A Multi-task Selected Learning Approach for Solving 3D Flexible Bin Packing Problem—0
Regularized Greedy Column Subset Selection—0
Composing photomosaic images using clustering based evolutionary programming—0
Attention, Learn to Solve Routing Problems!Code1
Accelerating E-Commerce Search Engine Ranking by Contextual Factor Selection—0
Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization AlgorithmsCode1
Smoothed analysis for low-rank solutions to semidefinite programs in quadratic penalty form—0
Cakewalk Sampling—0
Memcomputing: Leveraging memory and physics to compute efficiently—0
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