SOTAVerified

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 11711180 of 1277 papers

TitleStatusHype
Streaming, Distributed Variational Inference for Bayesian Nonparametrics0
Learning-based Compressive Subsampling0
Regularization vs. Relaxation: A conic optimization perspective of statistical variable selection0
Generative Adversarial Networks in Estimation of Distribution Algorithms for Combinatorial OptimizationCode1
Minimum Weight Perfect Matching via Blossom Belief Propagation0
Deep Boltzmann Machines in Estimation of Distribution Algorithms for Combinatorial OptimizationCode1
Hardness of Online Sleeping Combinatorial Optimization Problems0
Concept-based Summarization using Integer Linear Programming: From Concept Pruning to Multiple Optimal Solutions0
Message Passing and Combinatorial Optimization0
The backtracking survey propagation algorithm for solving random K-SAT problems0
Show:102550
← PrevPage 118 of 128Next →

No leaderboard results yet.