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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 351–375 of 1277 papers

TitleStatusHype
Deep Reinforcement Learning for Traveling Purchaser Problems—0
Differentiable Scaffolding Tree for Molecule Optimization—0
Deep Reinforcement Learning for Online Routing of Unmanned Aerial Vehicles with Wireless Power Transfer—0
Differentially Private Partial Set Cover with Applications to Facility Location—0
DIFFRAC: a discriminative and flexible framework for clustering—0
Diffusion-Inspired Quantum Noise Mitigation in Parameterized Quantum Circuits—0
Deep Reinforcement Learning for Modelling Protein Complexes—0
Deep Reinforcement Learning for Exact Combinatorial Optimization: Learning to Branch—0
A Two-stage Framework and Reinforcement Learning-based Optimization Algorithms for Complex Scheduling Problems—0
A Multi-task Selected Learning Approach for Solving 3D Flexible Bin Packing Problem—0
Deep Reinforcement Learning for Combinatorial Optimization: Covering Salesman Problems—0
DISCO: Efficient Diffusion Solver for Large-Scale Combinatorial Optimization Problems—0
Deep reinforced learning heuristic tested on spin-glass ground states: The larger picture—0
A Tutorial on Dual Decomposition and Lagrangian Relaxation for Inference in Natural Language Processing—0
Discrete graphical models -- an optimization perspective—0
An Efficient Algorithm for Cooperative Semi-Bandits—0
Diseño e implementación de una meta-heurística multi-poblacional de optimización combinatoria enfocada a la resolución de problemas de asignación de rutas a vehículos—0
Distributed Combinatorial Optimization of Downlink User Assignment in mmWave Cell-free Massive MIMO Using Graph Neural Networks—0
Distributed Deep Reinforcement Learning for Collaborative Spectrum Sharing—0
Distributed Injection-Locking in Analog Ising Machines to Solve Combinatorial Optimizations—0
Deep Momentum Uncertainty Hashing—0
An Efficient Circuit Compilation Flow for Quantum Approximate Optimization Algorithm—0
Diversity from Human Feedback—0
Divide and Learn: A Divide and Conquer Approach for Predict+Optimize—0
Deep memetic models for combinatorial optimization problems: application to the tool switching problem—0
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