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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 601610 of 1277 papers

TitleStatusHype
Directed percolation and numerical stability of simulations of digital memcomputing machines0
Digging Deeper: Operator Analysis for Optimizing Nonlinearity of Boolean Functions0
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Meme Stock Prediction0
An Edge-Aware Graph Autoencoder Trained on Scale-Imbalanced Data for Traveling Salesman Problems0
A Weighted Common Subgraph Matching Algorithm0
Diffusion-Inspired Quantum Noise Mitigation in Parameterized Quantum Circuits0
DIFFRAC: a discriminative and flexible framework for clustering0
Auxiliary-task Based Deep Reinforcement Learning for Participant Selection Problem in Mobile Crowdsourcing0
An Attention-LSTM Hybrid Model for the Coordinated Routing of Multiple Vehicles0
Differentially Private Partial Set Cover with Applications to Facility Location0
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