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Yeshwanth Venkatesha
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Neural architecture search for spiking neural networks
Y Kim, Y Li, H Park, Y Venkatesha, P Panda
European Conference on Computer Vision, 36-56, 2022
822022
Rate coding or direct coding: Which one is better for accurate, robust, and energy-efficient spiking neural networks?
Y Kim, H Park, A Moitra, A Bhattacharjee, Y Venkatesha, P Panda
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
482022
Federated learning with spiking neural networks
Y Venkatesha, Y Kim, L Tassiulas, P Panda
IEEE Transactions on Signal Processing 69, 6183-6194, 2021
412021
Exploring lottery ticket hypothesis in spiking neural networks
Y Kim, Y Li, H Park, Y Venkatesha, R Yin, P Panda
European Conference on Computer Vision, 102-120, 2022
332022
Privatesnn: privacy-preserving spiking neural networks
Y Kim, Y Venkatesha, P Panda
Proceedings of the AAAI Conference on Artificial Intelligence 36 (1), 1192-1200, 2022
192022
Activation density based mixed-precision quantization for energy efficient neural networks
K Vasquez, Y Venkatesha, A Bhattacharjee, A Moitra, P Panda
2021 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2021
162021
Exploring temporal information dynamics in spiking neural networks
Y Kim, Y Li, H Park, Y Venkatesha, A Hambitzer, P Panda
Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 8308-8316, 2023
122023
Privatesnn: Fully privacypreserving spiking neural networks
Y Kim, Y Venkatesha, P Panda
arXiv preprint arXiv:2104.03414, 2021
102021
Activation density driven efficient pruning in training
T Foldy-Porto, Y Venkatesha, P Panda
2020 25th International Conference on Pattern Recognition (ICPR), 8929-8936, 2021
8*2021
Lottery ticket hypothesis for spiking neural networks
Y Kim, Y Li, H Park, Y Venkatesha, R Yin, P Panda
arXiv preprint arXiv:2207.01382, 2022
62022
MIME: adapting a single neural network for multi-task inference with memory-efficient dynamic pruning
A Bhattacharjee, Y Venkatesha, A Moitra, P Panda
Proceedings of the 59th ACM/IEEE Design Automation Conference, 499-504, 2022
42022
Addressing client drift in federated continual learning with adaptive optimization
Y Venkatesha, Y Kim, H Park, Y Li, P Panda
Available at SSRN 4188586, 2022
42022
Examining the role and limits of batchnorm optimization to mitigate diverse hardware-noise in in-memory computing
A Bhattacharjee, A Moitra, Y Kim, Y Venkatesha, P Panda
Proceedings of the Great Lakes Symposium on VLSI 2023, 619-624, 2023
22023
Divide-and-conquer the NAS puzzle in resource-constrained federated learning systems
Y Venkatesha, Y Kim, H Park, P Panda
Neural Networks 168, 569-579, 2023
12023
Method and system with deep learning model generation
Y Venkatesha, S Krishnadasan, A Deshwal
US Patent App. 16/549,299, 2020
12020
Multi-objective Based Road-Link Grading for Health-Care Access During Flood Hazard Management
O Chakraborty, V Yeshwanth, P Mitra, SK Ghosh
Computational Science and Its Applications–ICCSA 2018: 18th International …, 2018
12018
Overview of Recent Advancements in Deep Learning and Artificial Intelligence
V Narayanan, Y Cao, P Panda, N Reddy Challapalle, X Du, Y Kim, ...
Advances in Electromagnetics Empowered by Artificial Intelligence and Deep …, 2023
2023
Sparse CNN Architecture Search (Scas)
V Yeshwanth, A Deshwal, S Krishnadasan, S Lee, J Song
2020 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2020
2020
Assortment of Attention Heads: Accelerating Federated Peft with Head Pruning and Strategic Client Selection
Y Venkatesha, S Kundu, P Panda
Available at SSRN 4790569, 0
A. Code Implementation
Y Kim, Y Li, H Park, Y Venkatesha, P Panda
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