FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs o…

🔨 A toolbox for federated learning, aiming to provide implementations of FedAvg, FedProx, Ditto, etc. in multiple versions, such as Pytorch/Tensorflow, single-machine/distributed, synchronized/asyn…

A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

Methods with examples for Feature Selection during Pre-processing in Machine Learning.

利用基于FPFH（Fast Point Feature Histograms）的特征描述符进行快速粗配准，通过ICP（Iterative Closest Point）算法进行精细调整，以实现高精度的点云对齐。

PyTorch Federated Learning (easy to use and extend)

We expose this user-friendly algorithm library (with an integrated evaluation platform) for beginners who intend to start federated learning (FL) study

A PyTorch implementation of "Communication-Efficient Learning of Deep Networks from Decentralized Data", AISTATS, 2017

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✅ Curated list of resources for college students

Feature Selection using Mutual Information for High Dimensional DataSets

Enhanced machine learning library tailored for data streams, featuring a Python API integrated with MOA backend support. This unique combination empowers users to leverage a wide array of existing…

Python implementation of the data stream clustering algorithm "DenStream"

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Streaming Feature Selection with Causal Fairness (SFCF)

OSFS-Vague

Sparse Streaming Feature Selection

A Python package for feature selection on a simulated data stream

streaming feature selection regularized by l2, 1 norm

Final Project, Implemeting 5 Online Feature Selection algorithms including SAOLA, Alpha Investing, OSFS, Fast OSFS, Fires. Validation process, Experiments and Evaluation process using 4 different O…

A Scoring Scheme for Online Feature Selection: Simulating Model Performance Without Retraining

Python implementation of Point Feature Histogram (PFH) from PCL

Fuctions to register pairs of point clouds (Fast global Registration + Multi-scale Generalized ICP) and Global Refinement using loopclosure optimization.

In this case, implement RANSAC global registration algorithm using python without library

Comparison of SHOT and FPFH descriptors for 3D point clouds registration

Implementation of the Chamfer Distance as a module for PyTorch

A machine learning package for streaming data in Python. The other ancestor of River.

open-source feature selection repository in python

Paralleled Iterative Closest Point (ICP) algorithm with Python and PyCUDA.