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 821830 of 1277 papers

TitleStatusHype
Three-dimensional Cooperative Localization of Commercial-Off-The-Shelf Sensors0
Threshold-aware Learning to Generate Feasible Solutions for Mixed Integer Programs0
Tight Bounds for Bandit Combinatorial Optimization0
Tight Bounds on Low-degree Spectral Concentration of Submodular and XOS functions0
Time Complexity Analysis of Evolutionary Algorithms for 2-Hop (1,2)-Minimum Spanning Tree Problem0
Topic-based Multi-document Summarization using Differential Evolution forCombinatorial Optimization of Sentences0
torchmSAT: A GPU-Accelerated Approximation To The Maximum Satisfiability Problem0
Totally Corrective Boosting with Cardinality Penalization0
Accelerating Cutting-Plane Algorithms via Reinforcement Learning Surrogates0
Towards combinatorial clustering: preliminary research survey0
Show:102550
← PrevPage 83 of 128Next →

No leaderboard results yet.