9 citations · 19 across the 6 of their papers we have counts for
5 papers
Sparse-Push: Communication- & Energy-Efficient Decentralized Distributed Learning over Directed & Time-Varying Graphs with non-IID Datasets
Sai Aparna Aketi, Amandeep Singh, Jan Rabaey
Current deep learning (DL) systems rely on a centralized computing paradigm which limits the amount of available training data, increases system latency, and adds privacy and secur…
Relevant-features based Auxiliary Cells for Energy Efficient Detection of Natural Errors
Sai Aparna Aketi, Priyadarshini Panda, Kaushik Roy
Deep neural networks have demonstrated state-of-the-art performance on many classification tasks. However, they have no inherent capability to recognize when their predictions are…
Gradual Channel Pruning while Training using Feature Relevance Scores for Convolutional Neural Networks
Sai Aparna Aketi, Sourjya Roy, Anand Raghunathan +1
The enormous inference cost of deep neural networks can be scaled down by network compression. Pruning is one of the predominant approaches used for deep network compression. Howev…
SERAD: Soft Error Resilient Asynchronous Design using a Bundled Data Protocol
Sai Aparna Aketi, Smriti Gupta, Huimei Cheng +2
The risk of soft errors due to radiation continues to be a significant challenge for engineers trying to build systems that can handle harsh environments. Building systems that are…
Towards Scalable, Efficient and Accurate Deep Spiking Neural Networks with Backward Residual Connections, Stochastic Softmax and Hybridization
Priyadarshini Panda, Aparna Aketi, Kaushik Roy
Spiking Neural Networks (SNNs) may offer an energy-efficient alternative for implementing deep learning applications. In recent years, there have been several proposals focused on…