A curated list of gradient boosting research papers with implementations.

numpy 实现的 周志华《机器学习》书中的算法及其他一些传统机器学习算法

Python版OpenCVのTracking APIの比較サンプル

A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and loss functions.

Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks [NeurIPS 2019]

A face detection program in python using Viola-Jones algorithm.

The transfer learning code for understanding and teaching : Boosting for transfer learning with single / multiple source(s)

An implementation of "Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation" (ASONAM 2019).

Functional gradient boosting based on residual network perception

We got a stew going!

Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"

An implementation of the paper "A Short Introduction to Boosting"

MILBoost and other boosting algorithms, compatible with scikit-learn

LogitBoost classification algorithm built on top of scikit-learn

Code repository of the paper "BooVAE: Boosting Approach for Continual Learning of VAE" published at NeurIPS 2021. https://arxiv.org/abs/1908.11853

A boosting procedure for multitask learning on graph-structured data

Open source gradient boosting library

Implementation of Modified Online Adaboost-ing algorithm

A simplified implement of Adaptive boosting.