3 citations · 4 across the 4 of their papers we have counts for
3 papers · 1 filter
XLDA: Linear Discriminant Analysis for Scaling Continual Learning to Extreme Classification at the Edge
Karan Shah, Vishruth Veerendranath, Anushka Hebbar +1
Streaming Linear Discriminant Analysis (LDA) while proven in Class-incremental Learning deployments at the edge with limited classes (upto 1000), has not been proven for deployment…
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…