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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

Showing 11211130 of 1277 papers

TitleStatusHype
Inference in Graphical Models via Semidefinite Programming Hierarchies0
Solving a New 3D Bin Packing Problem with Deep Reinforcement Learning Method0
INGEOTEC at SemEval 2017 Task 4: A B4MSA Ensemble based on Genetic Programming for Twitter Sentiment Analysis0
Semantic Dependency Parsing via Book Embedding0
Protein design by multiobjective optimization: evolutionary and non-evolutionary approaches0
Joint Graph Decomposition & Node Labeling: Problem, Algorithms, Applications0
Population-specific design of de-immunized protein biotherapeutics0
Recommendations for Marketing Campaigns in Telecommunication Business based on the footprint analysis0
Quadratic Unconstrained Binary Optimization Problem Preprocessing: Theory and Empirical AnalysisCode0
End-to-end Planning of Fixed Millimeter-Wave Networks0
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