Amherst College Data* Mammoths

Amherst College Data* Mammoths's repositories

datasetgenerator

A porting to modern g++ and C+11 of the IBM Quest dataset generator

Language:CApache-2.02 1 2

Implementations of the parallel and sequential cube sampling algorithms presented in the paper "A Scalable Parallel Algorithm for Balanced Sampling" (Alexander Lee, Stefan Walzer-Goldfeld, Shukry Zablah, Matteo Riondato, AAAI'22 Student Abstract).

Language:PythonApache-2.02 1 1

alice

MCMC algorithms to sample random bipartite graphs with given left and right degree sequences and BJDM.

Language:Jupyter NotebookGPL-3.01 30

SPEck-code

Code for the paper "SPEck: Mining Statistically-significant Sequential Patterns Efficiently with Exact Sampling", by Steedman Jenkins, Stefan Walzer-Goldfeld, and Matteo Riondato, appearing in the Data Mining and Knowledge Discovery Special Issue for ECML PKDD'22.

Language:JavaGPL-3.01 10

.github

Special repo.

Apache-2.0000

accsthesis

Amherst College Computer Science Honors Thesis LaTeX template

Language:TeXApache-2.0000

acdmammoths.github.io

Website for the Amherst College Data* Mammoths Research and Learning Group

Language:SCSSApache-2.0010

Bavarian-code

Code for the paper "Bavarian: Betweenness Centrality Approximation with Variance-Aware Rademacher Averages", by Chloe Wohlgemuth, Cyrus Cousins, and Matteo Riondato, appearing in ACM KDD'21 and ACM TKDD'23

Language:C++Apache-2.0000

Intellij-Hadoop

Run Hadoop program using Intellij

Language:Java010

ROhAN-code

ROhAN: Row-Order Agnostic Null Models for Statistically-sound Knowledge Discovery

Language:JavaGPL-3.0010