Name: Milad Khademi Nori
Type: User
Company: Queen's University
Bio: PhD in Deep Learning from Queen's University (2023). Expert in federated and continual learning with publications in top journals. Proficient in Python.
Twitter: khademinori
Location: Canada
Blog: https://t.co/xEIb1aeR3n
Milad Khademi Nori's Projects
enriched e-Prints
Atomo: Communication-efficient Learning via Atomic Sparsification
PyTorch implementation of a VAE-based generative classifier, as well as other class-incremental learning methods that do not store data (DGR, BI-R, EWC, SI, CWR, CWR+, AR1, the "labels trick", SLDA).
PyTorch implementation of various methods for continual learning (XdG, EWC, online EWC, SI, LwF, GR, GR+distill, RtF, ER, A-GEM, iCaRL).
PyTorch implementation of the Deep SLDA method from our CVPRW-2020 paper "Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis"
This is an official Tensorflow-2 implementation of Federated Continual Learning with Inter-Client Weighted Transfer
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Lightweight Python library for simple matrix completion.
Medical Imaging Assingment
Peer-to-peer Chat Application written in Java. This application uses the hybrid model to retrieve a list of available peers.
a simple P2P chat using a STUN server and 2 users.
Annotations for the PI-CAI Challenge: Public Training and Development Dataset
All Algorithms implemented in Python
95.47% on CIFAR10 with PyTorch