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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1051–1075 of 1277 papers

TitleStatusHype
Combinatorial Keyword Recommendations for Sponsored Search with Deep Reinforcement Learning—0
Differentiable Combinatorial Losses through Generalized Gradients of Linear Programs—0
Combinatorial Network Optimization with Unknown Variables: Multi-Armed Bandits with Linear Rewards—0
Combinatorial optimization and reasoning with graph neural networks—0
Combinatorial Optimization for All: Using LLMs to Aid Non-Experts in Improving Optimization Algorithms—0
Combinatorial optimization for low bit-width neural networks—0
Combinatorial optimization solving by coherent Ising machines based on spiking neural networks—0
Combinatorial Optimization via LLM-driven Iterated Fine-tuning—0
Combinatorial Persistency Criteria for Multicut and Max-Cut—0
Combinatorial Pure Exploration with Full-bandit Feedback and Beyond: Solving Combinatorial Optimization under Uncertainty with Limited Observation—0
Combinatorial Reasoning: Selecting Reasons in Generative AI Pipelines via Combinatorial Optimization—0
Combinatorial Topic Models using Small-Variance Asymptotics—0
Combining Learned Representations for Combinatorial Optimization—0
Combining Reinforcement Learning and Configuration Checking for Maximum k-plex Problem—0
Complex Vehicle Routing with Memory Augmented Neural Networks—0
Composing photomosaic images using clustering based evolutionary programming—0
Computational Protein Design Using AND/OR Branch-and-Bound Search—0
Computing with Residue Numbers in High-Dimensional Representation—0
Concentration of Data Encoding in Parameterized Quantum Circuits—0
Concept-based Summarization using Integer Linear Programming: From Concept Pruning to Multiple Optimal Solutions—0
Concept Learning in the Wild: Towards Algorithmic Understanding of Neural Networks—0
Constrained Combinatorial Optimization with Reinforcement Learning—0
Constrained Machine Learning: The Bagel Framework—0
Constrained Multiagent Rollout and Multidimensional Assignment with the Auction Algorithm—0
Constrained Resource Allocation Problems in Communications: An Information-assisted Approach—0
Show:102550
← PrevPage 43 of 52Next →

No leaderboard results yet.