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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 376–400 of 1277 papers

TitleStatusHype
Deep Reinforcement Learning for Combinatorial Optimization: Covering Salesman Problems—0
Deep reinforced learning heuristic tested on spin-glass ground states: The larger picture—0
Doubly Stochastic Matrix Models for Estimation of Distribution Algorithms—0
Duality between Feature Selection and Data Clustering—0
D-Wave's Nonlinear-Program Hybrid Solver: Description and Performance Analysis—0
Dynamic Algorithms for Matroid Submodular Maximization—0
Dynamic Anisotropic Smoothing for Noisy Derivative-Free Optimization—0
A Tutorial on Dual Decomposition and Lagrangian Relaxation for Inference in Natural Language Processing—0
Deep Momentum Uncertainty Hashing—0
Deep memetic models for combinatorial optimization problems: application to the tool switching problem—0
Dynamic Feature Selection for Efficient and Interpretable Human Activity Recognition—0
A Tutorial about Random Neural Networks in Supervised Learning—0
Biased Random-Key Genetic Algorithms: A Review—0
Dynamic Submodular Maximization—0
EALG: Evolutionary Adversarial Generation of Language Model-Guided Generators for Combinatorial Optimization—0
Amplitude-Ensemble Quantum-Inspired Tabu Search Algorithm for Solving 0/1 Knapsack Problems—0
A Data-Driven Column Generation Algorithm For Bin Packing Problem in Manufacturing Industry—0
Deep Learning of Graph Matching—0
A Nested Genetic Algorithm for Explaining Classification Data Sets with Decision Rules—0
Effective anytime algorithm for multiobjective combinatorial optimization problems—0
Effective Features of Remote Sensing Image Classification Using Interactive Adaptive Thresholding Method—0
Efficient 3D Endfiring TRUS Prostate Segmentation with Globally Optimized Rotational Symmetry—0
Attention Round for Post-Training Quantization—0
Adaptive Non-Uniform Timestep Sampling for Accelerating Diffusion Model Training—0
Deep Learning based Antenna Selection and CSI Extrapolation in Massive MIMO Systems—0
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