dimensionality-driven-learning

Learning algorithm

An implementation of dimensionality-driven learning with noisy labels using deep neural networks and various optimization techniques.

Code for paper "Dimensionality-Driven Learning with Noisy Labels" - ICML 2018

GitHub

58 stars
4 watching
15 forks
Language: Python
last commit: 5 months ago

Related projects:

Repository Description Stars
kyunghyuncho/deepmat An implementation of various deep learning architectures and algorithms 188
sungwon-han/fedx An unsupervised federated learning algorithm that uses cross knowledge distillation to learn meaningful data representations from local and global levels. 68
gorkemalgan/deep_learning_with_noisy_labels_literature A collection of papers and repos on deep learning with noisy labels. 235
xjtushujun/meta-weight-net An implementation of a meta-learning algorithm to improve sample weighting in classification tasks with noisy labels. 281
daizhongxiang/federated-neural-bandits An implementation of a decentralized algorithm for online decision-making in multiple agents 3
pouyamghari/pof-mkl An implementation of an online federated learning algorithm with multiple kernels for personalized machine learning 0
shimengjie/machine-learning-andrew-ng An implementation of machine learning algorithms from Andrew Ng's Coursera course in MATLAB 181
pingqingsheng/lrt An algorithm designed to robustly correct noisy labels in training data by iteratively refining the network's confidence and updating the loss function. 21
bhanml/co-teaching This project provides an implementation of Co-teaching, a method for training deep neural networks with extremely noisy labels. 492
yechengxi/lightnet A Matlab-based framework for building and training deep learning models 270
weijiaheng/advances-in-label-noise-learning A curated collection of papers and resources on learning with noisy labels in machine learning 687
dr-darryl-wright/noisy-labels-with-bootstrapping An implementation of training deep neural networks on noisy labels with bootstrapping using Keras 22
zhuangdizhu/fedgen An implementation of algorithms for decentralized machine learning in heterogeneous federated learning settings. 239
yandongliu/learningjs A JavaScript implementation of machine learning algorithms, including logistic regression and decision tree models. 65
felipexw/knn-java-library An implementation of a K-Nearest Neighbor algorithm for supervised learning 7