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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

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Showing 1076–1100 of 1277 papers

TitleStatusHype
Constraint Programming to Discover One-Flip Local Optima of Quadratic Unconstrained Binary Optimization Problems—0
Constraints First: A New MDD-based Model to Generate Sentences Under Constraints—0
Content Provider Dynamics and Coordination in Recommendation Ecosystems—0
Context-Aware Online Adaptation of Mixed Reality Interfaces—0
Continuous Latent Search for Combinatorial Optimization—0
Continuous Tensor Relaxation for Finding Diverse Solutions in Combinatorial Optimization Problems—0
Convergence Acceleration of Markov Chain Monte Carlo-based Gradient Descent by Deep Unfolding—0
Convergence and Running Time of Time-dependent Ant Colony Algorithms—0
Cool-Fusion: Fuse Large Language Models without Training—0
Cooperative coevolutionary hybrid NSGA-II with Linkage Measurement Minimization for Large-scale Multi-objective optimization—0
COPS: Controlled Pruning Before Training Starts—0
Cortical Processing with Thermodynamic-RAM—0
Cost-aware Feature Selection for IoT Device Classification—0
CreDes: Causal Reasoning Enhancement and Dual-End Searching for Solving Long-Range Reasoning Problems using LLMs—0
Cross-Problem Parameter Transfer in Quantum Approximate Optimization Algorithm: A Machine Learning Approach—0
Currency Arbitrage Optimization using Quantum Annealing, QAOA and Constraint Mapping—0
Box Facets and Cut Facets of Lifted Multicut Polytopes—0
DAN: Decentralized Attention-based Neural Network for the MinMax Multiple Traveling Salesman Problem—0
On a class of data-driven mixed-integer programming problems under uncertainty: a distributionally robust approach—0
Data-driven Prediction of Relevant Scenarios for Robust Combinatorial Optimization—0
D-Bees: A Novel Method Inspired by Bee Colony Optimization for Solving Word Sense Disambiguation—0
DCILP: A Distributed Approach for Large-Scale Causal Structure Learning—0
Decentralizing Coordination in Open Vehicle Fleets for Scalable and Dynamic Task Allocation—0
Decision-focused Graph Neural Networks for Combinatorial Optimization—0
Bayesian Meta-Prior Learning Using Empirical Bayes—0
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