12 citations · 21 across the 9 of their papers we have counts for
6 papers · 1 filter
On Accelerating Edge AI: Optimizing Resource-Constrained Environments
Jacob Sander, Achraf Cohen, Venkat R. Dasari +2
Resource-constrained edge deployments demand AI solutions that balance high performance with stringent compute, memory, and energy limitations. In this survey, we present a compreh…
Semantic Edge Computing and Semantic Communications in 6G Networks: A Unifying Survey and Research Challenges
Milin Zhang, Mohammad Abdi, Venkat R. Dasari +1
Semantic Edge Computing (SEC) and Semantic Communications (SemComs) have been proposed as viable approaches to achieve real-time edge-enabled intelligence in sixth-generation (6G)…
Adaptive Stochastic Gradient Descent for Fast and Communication-Efficient Distributed Learning
Serge Kas Hanna, Rawad Bitar, Parimal Parag +2
We consider the setting where a master wants to run a distributed stochastic gradient descent (SGD) algorithm on workers, each having a subset of the data. Distributed SGD may…
Computational complexity reduction of deep neural networks
Mee Seong Im, Venkat R. Dasari
Deep neural networks (DNN) have been widely used and play a major role in the field of computer vision and autonomous navigation. However, these DNNs are computationally complex an…
ECM: Early Exit via Class Means for Efficient Supervised and Unsupervised Learning
Alperen Görmez, Venkat R. Dasari, Erdem Koyuncu
State-of-the-art neural networks with early exit mechanisms often need considerable amount of training and fine tuning to achieve good performance with low computational cost. We p…
Adaptive Distributed Stochastic Gradient Descent for Minimizing Delay in the Presence of Stragglers
Serge Kas Hanna, Rawad Bitar, Parimal Parag +2
We consider the setting where a master wants to run a distributed stochastic gradient descent (SGD) algorithm on workers each having a subset of the data. Distributed SGD may s…