354 citations · 600 across the 29 of their papers we have counts for
9 papers · 1 filter
CoDream: Exchanging dreams instead of models for federated aggregation with heterogeneous models
Abhishek Singh, Gauri Gupta, Ritvik Kapila +5
Federated Learning (FL) enables collaborative optimization of machine learning models across decentralized data by aggregating model parameters. Our approach extends this concept b…
Scalable Collaborative Learning via Representation Sharing
Frédéric Berdoz, Abhishek Singh, Martin Jaggi +1
Privacy-preserving machine learning has become a key conundrum for multi-party artificial intelligence. Federated learning (FL) and Split Learning (SL) are two frameworks that enab…
AdaSplit: Adaptive Trade-offs for Resource-constrained Distributed Deep Learning
Ayush Chopra, Surya Kant Sahu, Abhishek Singh +4
Distributed deep learning frameworks like federated learning (FL) and its variants are enabling personalized experiences across a wide range of web clients and mobile/IoT devices.…
Can Self Reported Symptoms Predict Daily COVID-19 Cases?
Parth Patwa, Viswanatha Reddy, Rohan Sukumaran +6
The COVID-19 pandemic has impacted lives and economies across the globe, leading to many deaths. While vaccination is an important intervention, its roll-out is slow and unequal ac…
COVID-19 Outbreak Prediction and Analysis using Self Reported Symptoms
Rohan Sukumaran, Parth Patwa, T V Sethuraman +9
It is crucial for policymakers to understand the community prevalence of COVID-19 so combative resources can be effectively allocated and prioritized during the COVID-19 pandemic.…
NoPeek: Information leakage reduction to share activations in distributed deep learning
Praneeth Vepakomma, Abhishek Singh, Otkrist Gupta +1
For distributed machine learning with sensitive data, we demonstrate how minimizing distance correlation between raw data and intermediary representations reduces leakage of sensit…
SplitNN-driven Vertical Partitioning
Iker Ceballos, Vivek Sharma, Eduardo Mugica +4
In this work, we introduce SplitNN-driven Vertical Partitioning, a configuration of a distributed deep learning method called SplitNN to facilitate learning from vertically distrib…
FedML: A Research Library and Benchmark for Federated Machine Learning
Chaoyang He, Songze Li, Jinhyun So +17
Federated learning (FL) is a rapidly growing research field in machine learning. However, existing FL libraries cannot adequately support diverse algorithmic development; inconsist…
Privacy in Deep Learning: A Survey
Fatemehsadat Mireshghallah, Mohammadkazem Taram, Praneeth Vepakomma +3
The ever-growing advances of deep learning in many areas including vision, recommendation systems, natural language processing, etc., have led to the adoption of Deep Neural Networ…