most citedCommunication Optimization in Large Scale Federated Learning using Autoencoder Compressed Weight Updates

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cs.LG20213 cited

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…

cs.LG2021

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…

cs.LG2021

AI based Presentation Creator With Customized Audio Content Delivery

Muvazima Mansoor, Srikanth Chandar, Ramamoorthy Srinath

In this paper, we propose an architecture to solve a novel problem statement that has stemmed more so in recent times with an increase in demand for virtual content delivery due to…

cs.LG2020

Machine Learning Based Network Coverage Guidance System

Srikanth Chandar, Muvazima Mansoor, Mohina Ahmadi +3

With the advent of 4G, there has been a huge consumption of data and the availability of mobile networks has become paramount. Also, with the burst of network traffic based on user…

cs.LG2020

Road Accident Proneness Indicator Based On Time, Weather And Location Specificity Using Graph Neural Networks

Srikanth Chandar, Anish Reddy, Muvazima Mansoor +1

In this paper, we present a novel approach to identify the Spatio-temporal and environmental features that influence the safety of a road and predict its accident proneness based o…

cs.LG2020

Dynamic Systems Simulation and Control Using Consecutive Recurrent Neural Networks

Srikanth Chandar, Harsha Sunder

In this paper, we introduce a novel architecture to connecting adaptive learning and neural networks into an arbitrary machine's control system paradigm. Two consecutive Recurrent…