668 citations · 1.1k across the 20 of their papers we have counts for
7 papers · 1 filter
DeepFT: Fault-Tolerant Edge Computing using a Self-Supervised Deep Surrogate Model
Shreshth Tuli, Giuliano Casale, Ludmila Cherkasova +1
The emergence of latency-critical AI applications has been supported by the evolution of the edge computing paradigm. However, edge solutions are typically resource-constrained, po…
FlexiBERT: Are Current Transformer Architectures too Homogeneous and Rigid?
Shikhar Tuli, Bhishma Dedhia, Shreshth Tuli +1
The existence of a plethora of language models makes the problem of selecting the best one for a custom task challenging. Most state-of-the-art methods leverage transformer-based m…
MetaNet: Automated Dynamic Selection of Scheduling Policies in Cloud Environments
Shreshth Tuli, Giuliano Casale, Nicholas R. Jennings
Task scheduling is a well-studied problem in the context of optimizing the Quality of Service (QoS) of cloud computing environments. In order to sustain the rapid growth of computa…
Learning to Dynamically Select Cost Optimal Schedulers in Cloud Computing Environments
Shreshth Tuli, Giuliano Casale, Nicholas R. Jennings
The operational cost of a cloud computing platform is one of the most significant Quality of Service (QoS) criteria for schedulers, crucial to keep up with the growing computationa…
SplitPlace: AI Augmented Splitting and Placement of Large-Scale Neural Networks in Mobile Edge Environments
Shreshth Tuli, Giuliano Casale, Nicholas R. Jennings
In recent years, deep learning models have become ubiquitous in industry and academia alike. Deep neural networks can solve some of the most complex pattern-recognition problems to…
GoalNet: Inferring Conjunctive Goal Predicates from Human Plan Demonstrations for Robot Instruction Following
Shreya Sharma, Jigyasa Gupta, Shreshth Tuli +2
Our goal is to enable a robot to learn how to sequence its actions to perform tasks specified as natural language instructions, given successful demonstrations from a human partner…