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Sharath Nittur Sridhar
Sharath Nittur Sridhar
Research Scientist, Intel Corporation
在 intel.com 的电子邮件经过验证
标题
引用次数
引用次数
年份
Driving in the matrix: Can virtual worlds replace human-generated annotations for real world tasks?
M Johnson-Roberson, C Barto, R Mehta, SN Sridhar, K Rosaen, ...
arXiv preprint arXiv:1610.01983, 2016
7922016
Driving in the matrix: Can virtual worlds replace human-generated annotations for real world tasks? arXiv 2016
M Johnson-Roberson, C Barto, R Mehta, SN Sridhar, K Rosaen, ...
arXiv preprint arXiv:1610.01983, 0
17
Compact scene graphs for layout composition and patch retrieval
S Tripathi, S Nittur Sridhar, S Sundaresan, H Tang
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
162019
Attention-based image upsampling
S Kundu, H Mostafa, SN Sridhar, S Sundaresan
arXiv preprint arXiv:2012.09904, 2020
152020
Undivided attention: Are intermediate layers necessary for BERT?
SN Sridhar, A Sarah
arXiv preprint arXiv:2012.11881, 2020
112020
Sparse mixture once-for-all adversarial training for efficient in-situ trade-off between accuracy and robustness of dnns
S Kundu, S Sundaresan, SN Sridhar, S Lu, H Tang, PA Beerel
ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023
52023
A hardware-aware framework for accelerating neural architecture search across modalities
D Cummings, A Sarah, SN Sridhar, M Szankin, JP Munoz, S Sundaresan
arXiv preprint arXiv:2205.10358, 2022
52022
LLaMA-NAS: Efficient Neural Architecture Search for Large Language Models
A Sarah, SN Sridhar, M Szankin, S Sundaresan
arXiv preprint arXiv:2405.18377, 2024
42024
Instatune: Instantaneous neural architecture search during fine-tuning
SN Sridhar, S Kundu, S Sundaresan, M Szankin, A Sarah
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
32023
Trimbert: Tailoring bert for trade-offs
SN Sridhar, A Sarah, S Sundaresan
arXiv preprint arXiv:2202.12411, 2022
32022
Machine learning model scaling system with energy efficient network data transfer for power aware hardware
DJ Cummings, JP Munoz, S Kundu, SN Sridhar, M Szankin
US Patent App. 17/506,161, 2022
32022
Fast weight long short-term memory
TA Keller, SN Sridhar, X Wang
arXiv preprint arXiv:1804.06511, 2018
32018
On optimizing human-machine task assignments
A Veit, M Wilber, R Vaish, S Belongie, J Davis, V Anand, A Aviral, ...
arXiv preprint arXiv:1509.07543, 2015
32015
A hardware-aware system for accelerating deep neural network optimization
A Sarah, D Cummings, SN Sridhar, S Sundaresan, M Szankin, T Webb, ...
arXiv preprint arXiv:2202.12954, 2022
22022
Hardware-aware machine learning model search mechanisms
SN Sridhar, A Sarah
US Patent App. 17/504,996, 2022
22022
Deep neural network model design enhanced by real-time proxy evaluation feedback
DJ Cummings, SN Sridhar
US Patent App. 17/497,736, 2022
22022
Sensi-Bert: Towards Sensitivity Driven Fine-Tuning for Parameter-Efficient Language Model
S Kundu, SN Sridhar, M Szankin, S Sundaresan
ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024
12024
Sensi-bert: Towards sensitivity driven fine-tuning for parameter-efficient bert
S Kundu, SN Sridhar, M Szankin, S Sundaresan
arXiv preprint arXiv:2307.11764, 2023
12023
Polarized light Monte Carlo modeling for multiparticle distribution of scatterers
R Manjappa, C Devaraj, NS Sharath, SM Shankaranarayana, R Hebbar, ...
International Conference on Fibre Optics and Photonics, S5A. 2, 2014
12014
Methods and apparatus for sensitivity-based fine tuning of a machine learning model
S Kundu, SN Sridhar, S Sundaresan
US Patent App. 18/680,757, 2024
2024
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