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 831840 of 1277 papers

TitleStatusHype
Enhancing Robustness of Neural Networks through Fourier Stabilization0
Experiments with graph convolutional networks for solving the vertex p-center problem0
Policies for the Dynamic Traveling Maintainer Problem with Alerts0
On a class of data-driven mixed-integer programming problems under uncertainty: a distributionally robust approach0
Structural Causal Models Reveal Confounder Bias in Linear Program ModellingCode0
IA-GM: A Deep Bidirectional Learning Method for Graph Matching0
Graph Learning: A Survey0
Reconstruction of Convex Polytope Compositions from 3D Point-clouds0
A Novel Surrogate-assisted Evolutionary Algorithm Applied to Partition-based Ensemble LearningCode0
Exact and Approximate Hierarchical Clustering Using A*0
Show:102550
← PrevPage 84 of 128Next →

No leaderboard results yet.