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 581590 of 1277 papers

TitleStatusHype
Highly parallel algorithm for the Ising ground state searching problem0
Improved Approximation Algorithms for Low-Rank Problems Using Semidefinite Optimization0
High-Level Plan for Behavioral Robot Navigation with Natural Language Directions and R-NET0
Improvement/Extension of Modular Systems as Combinatorial Reengineering (Survey)0
Improving Existing Optimization Algorithms with LLMs0
Cross-Problem Parameter Transfer in Quantum Approximate Optimization Algorithm: A Machine Learning Approach0
A Knowledge-Based Approach to Word Sense Disambiguation by distributional selection and semantic features0
Higher-Order Quantum-Inspired Genetic Algorithms0
Inference in Graphical Models via Semidefinite Programming Hierarchies0
Higher-Order Neuromorphic Ising Machines -- Autoencoders and Fowler-Nordheim Annealers are all you need for Scalability0
Show:102550
← PrevPage 59 of 128Next →

No leaderboard results yet.