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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 751–800 of 1277 papers

TitleStatusHype
Surrogate Assisted Monte Carlo Tree Search in Combinatorial Optimization—0
Symmetry Breaking and Equivariant Neural Networks—0
Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization—0
Synthesizing Min-Max Control Barrier Functions For Switched Affine Systems—0
Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls—0
Target Languages (vs. Inductive Biases) for Learning to Act and Plan—0
Classical Simulation of Variational Quantum Classifiers using Tensor Rings—0
Text2Zinc: A Cross-Domain Dataset for Modeling Optimization and Satisfaction Problems in MiniZinc—0
The backtracking survey propagation algorithm for solving random K-SAT problems—0
The Cakewalk Method—0
The Effectiveness of Johnson-Lindenstrauss Transform for High Dimensional Optimization With Adversarial Outliers, and the Recovery—0
The Fellowship of the Dyson Ring: ACT&Friends' Results and Methods for GTOC 11—0
The First Proven Performance Guarantees for the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) on a Combinatorial Optimization Problem—0
The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle—0
The Influence of Local Search over Genetic Algorithms with Balanced Representations—0
The Lovász ϑ function, SVMs and finding large dense subgraphs—0
The Neural-Prediction based Acceleration Algorithm of Column Generation for Graph-Based Set Covering Problems—0
Theoretically Grounded Pruning of Large Ground Sets for Constrained, Discrete Optimization—0
Theory of neuromorphic computing by waves: machine learning by rogue waves, dispersive shocks, and solitons—0
Thinking Out of the Box: Hybrid SAT Solving by Unconstrained Continuous Optimization—0
Thompson Sampling for Combinatorial Network Optimization in Unknown Environments—0
Three-dimensional Cooperative Localization of Commercial-Off-The-Shelf Sensors—0
Threshold-aware Learning to Generate Feasible Solutions for Mixed Integer Programs—0
Tight Bounds for Bandit Combinatorial Optimization—0
Tight Bounds on Low-degree Spectral Concentration of Submodular and XOS functions—0
Time Complexity Analysis of Evolutionary Algorithms for 2-Hop (1,2)-Minimum Spanning Tree Problem—0
Topic-based Multi-document Summarization using Differential Evolution forCombinatorial Optimization of Sentences—0
torchmSAT: A GPU-Accelerated Approximation To The Maximum Satisfiability Problem—0
Totally Corrective Boosting with Cardinality Penalization—0
Accelerating Cutting-Plane Algorithms via Reinforcement Learning Surrogates—0
Towards combinatorial clustering: preliminary research survey—0
Towards Constraint-Based Adaptive Hypergraph Learning for Solving Vehicle Routing: An End-to-End Solution—0
Towards Decision Support Technology Platform for Modular Systems—0
Towards Efficient and Exact MAP-Inference for Large Scale Discrete Computer Vision Problems via Combinatorial Optimization—0
Towards Efficient Modularity in Industrial Drying: A Combinatorial Optimization Viewpoint—0
Towards fully automated protein structure elucidation with NMR spectroscopy—0
Context-aware Diversity Enhancement for Neural Multi-Objective Combinatorial Optimization—0
Towards Geometry-Preserving Reductions Between Constraint Satisfaction Problems (and other problems in NP)—0
Towards Integrated Glance To Restructuring in Combinatorial Optimization—0
Towards Practical Explainability with Cluster Descriptors—0
Towards Principled Task Grouping for Multi-Task Learning—0
Towards the Inferrence of Structural Similarity of Combinatorial Landscapes—0
Trading off Quality for Efficiency of Community Detection: An Inductive Method across Graphs—0
Trading Quality for Efficiency of Graph Partitioning: An Inductive Method across Graphs—0
Training Deep Boltzmann Networks with Sparse Ising Machines—0
Training Hard-Threshold Networks with Combinatorial Search in a Discrete Target Propagation Setting—0
Transfer Learning for Deep-Unfolded Combinatorial Optimization Solver with Quantum Annealer—0
Transformers in Reinforcement Learning: A Survey—0
Transform then Explore: a Simple and Effective Technique for Exploratory Combinatorial Optimization with Reinforcement Learning—0
Tropical Attention: Neural Algorithmic Reasoning for Combinatorial Algorithms—0
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