ahmedcs

adaptive-federated-learning

Code for paper "Adaptive Federated Learning in Resource Constrained Edge Computing Systems"

grace

GRACE - GRAdient ComprEssion for distributed deep learning

HyGenICC

Hypervisor-based Generic Congestion Control for Data Centres

Practical_FL_Tutorial

Advancing Federated Learning in Practice: From Theory to Real-World Edge Applications

REFL

Resource Efficient Federated Learning

RWNDQ

RWNDQ is an Equal Share Allocation Switch Design for Data Centre Networks

SICC

SDN-based Incast Congestion Control for Data Centers

SIDCo

SIDCo is An Efficient Statistical-based Gradient Compression Technique for Distributed Training Systems

T-RACKs

Timely ACKs Retransmission for Data Centres

TCP_loss_monitor

TCP socket-level monitoring of socket events (i.e, Open, Close, CWND, Fast Retransmit, Retransmission Timeouts, .. etc)

ahmedcs/deep-gradient-compression

[ICLR 2018] Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training

ahmedcs/grace

GRACE - GRAdient ComprEssion for distributed deep learning

ahmedcs/acme

A library of reinforcement learning components and agents

ahmedcs/ai-research

ahmedcs/artemis-bidirectional-compression

Artemis: fast convergence guarantees for bidirectional compression in Federated Learning

ahmedcs/BatchCrypt

ahmedcs/cgau-client-adaptation

ahmedcs/CollaborativeFairFederatedLearning

Official implementation of our work "Collaborative Fairness in Federated Learning."

ahmedcs/CommEfficient

PyTorch for benchmarking communication-efficient distributed SGD optimization algorithms

ahmedcs/DataPoisoning_FL

Code for Data Poisoning Attacks Against Federated Learning Systems

ahmedcs/ddl-benchmarks

ddl-benchmarks: Benchmarks for Distributed Deep Learning

ahmedcs/deepspeech.pytorch

Speech Recognition using DeepSpeech2.

ahmedcs/DeepSpeed

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

ahmedcs/Dem-AI

Democratized Learning

ahmedcs/edge-consensus-learning

P2P Distributed deep learning framework that runs on PyTorch.

ahmedcs/federated_adaptation

Salvaging Federated Learning by Local Adaptation

ahmedcs/FedMA

Code for Federated Learning with Matched Averaging, ICLR 2020.

ahmedcs/FedProx-1

Federated Optimization in Heterogeneous Networks (MLSys '20)

ahmedcs/FPPDL

code for TPDS paper "Towards Fair and Privacy-Preserving Federated Deep Models"

ahmedcs/GaussianK-SGD

Understanding Top-k Sparsification in Distributed Deep Learning

ahmedcs/HashingDeepLearning

Codebase for "SLIDE : In Defense of Smart Algorithms over Hardware Acceleration for Large-Scale Deep Learning Systems"

ahmedcs/KD_UDA

ahmedcs/leaf

Leaf: A Benchmark for Federated Settings

ahmedcs/LG-FedAvg

Federated Learning with Local and Global Representations

ahmedcs/non_iid_dml

ahmedcs/oneflow

OneFlow is a performance-centered and open-source deep learning framework.

ahmedcs/Split-Learning-and-Federated-Learning

Investigating Split Learning and Federate Learning

ahmedcs/Synaptic-Flow

ahmedcs/toolbox

Curated list of libraries for a faster machine learning workflow

ahmedcs/ZeroShotKnowledgeTransfer

Accompanying code for the paper "Zero-shot Knowledge Transfer via Adversarial Belief Matching"