Nandan Kumar Jha

According to our database, Nandan Kumar Jha authored at least 14 papers between 2019 and 2023.

Collaborative distances:

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

2023

DeepReShape: Redesigning Neural Networks for Efficient Private Inference.

Nandan Kumar Jha, Brandon Reagen

CoRR, 2023

Characterizing and Optimizing End-to-End Systems for Private Inference.

Karthik Garimella, Zahra Ghodsi, Nandan Kumar Jha, Siddharth Garg, Brandon Reagen

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023

2021

Modeling Data Reuse in Deep Neural Networks by Taking Data-Types into Cognizance.

Nandan Kumar Jha, Sparsh Mittal

IEEE Trans. Computers, 2021

CryptoNite: Revealing the Pitfalls of End-to-End Private Inference at Scale.

Karthik Garimella, Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen

CoRR, 2021

Sisyphus: A Cautionary Tale of Using Low-Degree Polynomial Activations in Privacy-Preserving Deep Learning.

Karthik Garimella, Nandan Kumar Jha, Brandon Reagen

CoRR, 2021

Circa: Stochastic ReLUs for Private Deep Learning.

Zahra Ghodsi, Nandan Kumar Jha, Brandon Reagen, Siddharth Garg

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

DeepReDuce: ReLU Reduction for Fast Private Inference.

Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen

Proceedings of the 38th International Conference on Machine Learning, 2021

Digital Storytelling: The Integration of Intangible and Tangible Heritage in the City of Surat, India.

Chika Udeaja, Lukman E. Mansuri, Busisiwe Chikomborero Ncube Makore, Kwasi Gyau Baffour Awuah, Dilip A. Patel, Claudia Trillo, Nandan Kumar Jha

Proceedings of the Culture and Computing. Interactive Cultural Heritage and Arts, 2021

2020

DeepPeep: Exploiting Design Ramifications to Decipher the Architecture of Compact DNNs.

Nandan Kumar Jha, Sparsh Mittal, Binod Kumar, Govardhan Mattela

ACM J. Emerg. Technol. Comput. Syst., 2020

On the Demystification of Knowledge Distillation: A Residual Network Perspective.

Nandan Kumar Jha, Rajat Saini, Sparsh Mittal

CoRR, 2020

ULSAM: Ultra-Lightweight Subspace Attention Module for Compact Convolutional Neural Networks.

Rajat Saini, Nandan Kumar Jha, Bedanta Das, Sparsh Mittal, C. Krishna Mohan

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

E2GC: Energy-efficient Group Convolution in Deep Neural Networks.

Nandan Kumar Jha, Rajat Saini, Subhrajit Nag, Sparsh Mittal

Proceedings of the 33rd International Conference on VLSI Design and 19th International Conference on Embedded Systems, 2020

DRACO: Co-Optimizing Hardware Utilization, and Performance of DNNs on Systolic Accelerator.

Nandan Kumar Jha, Shreyas Ravishankar, Sparsh Mittal, Arvind Kaushik, Dipan Mandal, Mahesh Chandra

Proceedings of the 2020 IEEE Computer Society Annual Symposium on VLSI, 2020

2019

The Ramifications of Making Deep Neural Networks Compact.

Nandan Kumar Jha, Sparsh Mittal, Govardhan Mattela

Proceedings of the 32nd International Conference on VLSI Design and 18th International Conference on Embedded Systems, 2019