Krishnakumar Nair

Orcid: 0009-0008-3540-5311

According to our database1, Krishnakumar Nair authored at least 20 papers between 2011 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2023

2022
XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse.
CoRR, 2022

Learning to Collide: Recommendation System Model Compression with Learned Hash Functions.
CoRR, 2022

An In-Silico model for evaluating the directional shock vectors in terminating and modulating rotors.
Comput. Biol. Medicine, 2022

Check-N-Run: a Checkpointing System for Training Deep Learning Recommendation Models.
Proceedings of the 19th USENIX Symposium on Networked Systems Design and Implementation, 2022


Supporting Massive DLRM Inference through Software Defined Memory.
Proceedings of the 42nd IEEE International Conference on Distributed Computing Systems, 2022

2021
Supporting Massive DLRM Inference Through Software Defined Memory.
CoRR, 2021

High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models.
CoRR, 2021

2020
Check-N-Run: A Checkpointing System for Training Recommendation Models.
CoRR, 2020

Deep Learning Training in Facebook Data Centers: Design of Scale-up and Scale-out Systems.
CoRR, 2020

Scalable Distributed Training of Recommendation Models: An ASTRA-SIM + NS3 case-study with TCP/IP transport.
Proceedings of the IEEE Symposium on High-Performance Interconnects, 2020

2019
Empirical mode decomposition based ECG features in classifying and tracking ventricular arrhythmias.
Comput. Biol. Medicine, 2019

2018
Instantaneous Time-Frequency Features in Characterizing Ventricular Arrhythmias Using Empirical Mode Decomposition.
Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

2017
Morphologically constrained signal subspace characterization of electrograms during ventricular fibrillation.
Biomed. Signal Process. Control., 2017

2013
A classification scheme for ventricular arrhythmias using wavelets analysis.
Medical Biol. Eng. Comput., 2013

Automated signal pattern detection in ECG during human ventricular arrhythmias.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

2011
Relating spatial heterogeneities to rotor formation in studying human ventricular fibrillation.
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011

Wavelet-based features for characterizing ventricular arrhythmias in optimizing treatment options.
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011

Predicting refibrillation from pre-shock waveforms in optimizing cardiac resuscitation.
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011


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