推荐系统入门教程,在线阅读地址:https://datawhalechina.github.io/fun-rec/
-
Updated
Mar 15, 2024 - Jupyter Notebook
推荐系统入门教程,在线阅读地址:https://datawhalechina.github.io/fun-rec/
KaHyPar (Karlsruhe Hypergraph Partitioning) is a multilevel hypergraph partitioning framework providing direct k-way and recursive bisection based partitioning algorithms that compute solutions of very high quality.
KaHIP -- Karlsruhe HIGH Quality Partitioning.
Mt-KaHyPar (Multi-Threaded Karlsruhe Hypergraph Partitioner) is a shared-memory multilevel graph and hypergraph partitioner equipped with parallel implementations of techniques used in the best sequential partitioning algorithms. Mt-KaHyPar can partition extremely large hypergraphs very fast and with high quality.
Exercises for the Algorithm Engineering (ALE) course at University of Pisa
A list of all publications related to the KaHyPar frameworks.
Experiment execution and result management for empirical evaluations of algorithms in Python.
Collection of our hypergraph partitioning experiments
Secretly a Master's Thesis
Graph Coloring implementation based on XRLF algorithm
Repo for Algorithm Engineering Projects Team: Suffering IRL
Add a description, image, and links to the algorithm-engineering topic page so that developers can more easily learn about it.
To associate your repository with the algorithm-engineering topic, visit your repo's landing page and select "manage topics."