Yeshwanth Venkatesha

According to our database, Yeshwanth Venkatesha authored at least 14 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

HaLo-FL: Hardware-Aware Low-Precision Federated Learning.

Yeshwanth Venkatesha, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024

2023

Divide-and-conquer the NAS puzzle in resource-constrained federated learning systems.

Yeshwanth Venkatesha, Youngeun Kim, Hyoungseob Park, Priyadarshini Panda

Neural Networks, November, 2023

Examining the Role and Limits of Batchnorm Optimization to Mitigate Diverse Hardware-noise in In-memory Computing.

Abhiroop Bhattacharjee, Abhishek Moitra, Youngeun Kim, Yeshwanth Venkatesha, Priyadarshini Panda

Proceedings of the Great Lakes Symposium on VLSI 2023, 2023

Exploring Temporal Information Dynamics in Spiking Neural Networks.

Youngeun Kim, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha, Anna Hambitzer, Priyadarshini Panda

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Addressing Client Drift in Federated Continual Learning with Adaptive Optimization.

Yeshwanth Venkatesha, Youngeun Kim, Hyoungseob Park, Yuhang Li, Priyadarshini Panda

CoRR, 2022

Rate Coding Or Direct Coding: Which One Is Better For Accurate, Robust, And Energy-Efficient Spiking Neural Networks?

Youngeun Kim, Hyoungseob Park, Abhishek Moitra, Abhiroop Bhattacharjee, Yeshwanth Venkatesha, Priyadarshini Panda

Proceedings of the IEEE International Conference on Acoustics, 2022

Exploring Lottery Ticket Hypothesis in Spiking Neural Networks.

Youngeun Kim, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha, Ruokai Yin, Priyadarshini Panda

Proceedings of the Computer Vision - ECCV 2022, 2022

Neural Architecture Search for Spiking Neural Networks.

Youngeun Kim, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha, Priyadarshini Panda

Proceedings of the Computer Vision, 2022

MIME: adapting a single neural network for multi-task inference with memory-efficient dynamic pruning.

Abhiroop Bhattacharjee, Yeshwanth Venkatesha, Abhishek Moitra, Priyadarshini Panda

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

PrivateSNN: Privacy-Preserving Spiking Neural Networks.

Youngeun Kim, Yeshwanth Venkatesha, Priyadarshini Panda

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Federated Learning With Spiking Neural Networks.

Yeshwanth Venkatesha, Youngeun Kim, Leandros Tassiulas, Priyadarshini Panda

IEEE Trans. Signal Process., 2021

PrivateSNN: Fully Privacy-Preserving Spiking Neural Networks.

Youngeun Kim, Yeshwanth Venkatesha, Priyadarshini Panda

CoRR, 2021

Activation Density based Mixed-Precision Quantization for Energy Efficient Neural Networks.

Karina Vasquez, Yeshwanth Venkatesha, Abhiroop Bhattacharjee, Abhishek Moitra, Priyadarshini Panda

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021

2020

Activation Density Driven Efficient Pruning in Training.

Timothy Foldy-Porto, Yeshwanth Venkatesha, Priyadarshini Panda

Proceedings of the 25th International Conference on Pattern Recognition, 2020