3 citations · 3 across the 3 of their papers we have counts for
3 papers
Communication Optimization in Large Scale Federated Learning using Autoencoder Compressed Weight Updates
Srikanth Chandar, Pravin Chandran, Raghavendra Bhat +1
Federated Learning (FL) solves many of this decade's concerns regarding data privacy and computation challenges. FL ensures no data leaves its source as the model is trained at whe…
Weight Divergence Driven Divide-and-Conquer Approach for Optimal Federated Learning from non-IID Data
Pravin Chandran, Raghavendra Bhat, Avinash Chakravarthi +1
Federated Learning allows training of data stored in distributed devices without the need for centralizing training data, thereby maintaining data privacy. Addressing the ability t…
NTP : A Neural Network Topology Profiler
Raghavendra Bhat, Pravin Chandran, Juby Jose +2
Performance of end-to-end neural networks on a given hardware platform is a function of its compute and memory signature, which in-turn, is governed by a wide range of parameters s…