Sai Aparna Aketi | DeepAI

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∙ 05/08/2023

Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data

Decentralized learning enables the training of deep learning models over...

0 Sai Aparna Aketi, et al. ∙

∙ 04/09/2023

Homogenizing Non-IID datasets via In-Distribution Knowledge Distillation for Decentralized Learning

Decentralized learning enables serverless training of deep neural networ...

0 Deepak Ravikumar, et al. ∙

∙ 03/27/2023

CoDeC: Communication-Efficient Decentralized Continual Learning

Training at the edge utilizes continuously evolving data generated at di...

0 Sakshi Choudhary, et al. ∙

∙ 09/28/2022

Neighborhood Gradient Clustering: An Efficient Decentralized Learning Method for Non-IID Data Distributions

Decentralized learning over distributed datasets can have significantly ...

0 Sai Aparna Aketi, et al. ∙

∙ 11/17/2021

Low Precision Decentralized Distributed Training over IID and non-IID Data

Decentralized distributed learning is the key to enabling large-scale ma...

0 Sai Aparna Aketi, et al. ∙

∙ 02/10/2021

Sparse-Push: Communication- Energy-Efficient Decentralized Distributed Learning over Directed Time-Varying Graphs with non-IID Datasets

Current deep learning (DL) systems rely on a centralized computing parad...

0 Sai Aparna Aketi, et al. ∙

∙ 02/25/2020

Relevant-features based Auxiliary Cells for Energy Efficient Detection of Natural Errors

Deep neural networks have demonstrated state-of-the-art performance on m...

6 Sai Aparna Aketi, et al. ∙

∙ 02/23/2020

Gradual Channel Pruning while Training using Feature Relevance Scores for Convolutional Neural Networks

The enormous inference cost of deep neural networks can be scaled down b...

0 Sai Aparna Aketi, et al. ∙

∙ 01/13/2020

SERAD: Soft Error Resilient Asynchronous Design using a Bundled Data Protocol

The risk of soft errors due to radiation continues to be a significant c...

0 Sai Aparna Aketi, et al. ∙

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