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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
Dynamic Feature Selection for Efficient and Interpretable Human Activity Recognition—0
Barriers for the performance of graph neural networks (GNN) in discrete random structures. A comment on~schuetz2022combinatorial,angelini2023modern,schuetz2023reply—0
An Efficient Circuit Compilation Flow for Quantum Approximate Optimization Algorithm—0
An efficient algorithm for learning with semi-bandit feedback—0
Balancing Pareto Front exploration of Non-dominated Tournament Genetic Algorithm (B-NTGA) in solving multi-objective NP-hard problems with constraints—0
A Differentiable Approach to Combinatorial Optimization using Dataless Neural Networks—0
A Bayesian approach for prompt optimization in pre-trained language models—0
An Efficient Algorithm for Cooperative Semi-Bandits—0
An Edge-Aware Graph Autoencoder Trained on Scale-Imbalanced Data for Traveling Salesman Problems—0
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Meme Stock Prediction—0
Accelerating Exact Combinatorial Optimization via RL-based Initialization -- A Case Study in Scheduling—0
A Weighted Common Subgraph Matching Algorithm—0
Auxiliary-task Based Deep Reinforcement Learning for Participant Selection Problem in Mobile Crowdsourcing—0
An Attention-LSTM Hybrid Model for the Coordinated Routing of Multiple Vehicles—0
Automatic Rank Selection for High-Speed Convolutional Neural Network—0
An Approximation Algorithm for Risk-averse Submodular Optimization—0
Dynamic Feature Selection for Dependency Parsing—0
Dynamic Submodular Maximization—0
Automatic Loss Function Search for Predict-Then-Optimize Problems with Strong Ranking Property—0
Analyzing the behaviour of D'WAVE quantum annealer: fine-tuning parameterization and tests with restrictive Hamiltonian formulations—0
D-Wave's Nonlinear-Program Hybrid Solver: Description and Performance Analysis—0
Doubly Stochastic Matrix Models for Estimation of Distribution Algorithms—0
Domain Switching on the Pareto Front: Multi-Objective Deep Kernel Learning in Automated Piezoresponse Force Microscopy—0
Duality between Feature Selection and Data Clustering—0
Dynamic Algorithms for Matroid Submodular Maximization—0
Automated Graph Genetic Algorithm based Puzzle Validation for Faster Game Design—0
A Unifying Survey of Reinforced, Sensitive and Stigmergic Agent-Based Approaches for E-GTSP—0
Analysis of Quality Diversity Algorithms for the Knapsack Problem—0
Addressing The Knapsack Challenge Through Cultural Algorithm Optimization—0
Reinforcement Learning in Practice: Opportunities and Challenges—0
A Unified Framework for Combinatorial Optimization Based on Graph Neural Networks—0
Accelerating Evolutionary Construction Tree Extraction via Graph Partitioning—0
Dynamic Anisotropic Smoothing for Noisy Derivative-Free Optimization—0
Deep Reinforcement Learning for Traveling Purchaser Problems—0
Deep Reinforcement Learning for Online Routing of Unmanned Aerial Vehicles with Wireless Power Transfer—0
Deep Reinforcement Learning for Modelling Protein Complexes—0
DeepSimplex: Reinforcement Learning of Pivot Rules Improves the Efficiency of Simplex Algorithm in Solving Linear Programming Problems—0
A Unified Pre-training and Adaptation Framework for Combinatorial Optimization on Graphs—0
Deep Reinforcement Learning for Exact Combinatorial Optimization: Learning to Branch—0
A Two-stage Framework and Reinforcement Learning-based Optimization Algorithms for Complex Scheduling Problems—0
Density Maximization in Context-Sense Metric Space for All-words WSD—0
Deploying Graph Neural Networks in Wireless Networks: A Link Stability Viewpoint—0
A Multi-task Selected Learning Approach for Solving 3D Flexible Bin Packing Problem—0
Design And Optimization Of Multi-rendezvous Manoeuvres Based On Reinforcement Learning And Convex Optimization—0
Design Space Exploration as Quantified Satisfaction—0
Accelerating E-Commerce Search Engine Ranking by Contextual Factor Selection—0
Detecting Overlapping Temporal Community Structure in Time-Evolving Networks—0
Devolutionary genetic algorithms with application to the minimum labeling Steiner tree problem—0
Deep Reinforcement Learning for Combinatorial Optimization: Covering Salesman Problems—0
Deep reinforced learning heuristic tested on spin-glass ground states: The larger picture—0
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