| Crypten: Secure multi-party computation meets machine learning B Knott, S Venkataraman, A Hannun, S Sengupta, M Ibrahim, ... Advances in Neural Information Processing Systems 34, 4961-4973, 2021 | 416 | 2021 |
| CryptGPU: Fast privacy-preserving machine learning on the GPU S Tan, B Knott, Y Tian, DJ Wu 2021 IEEE Symposium on Security and Privacy (SP), 1021-1038, 2021 | 198 | 2021 |
| Conveying language through haptics: A multi-sensory approach N Dunkelberger, J Sullivan, J Bradley, NP Walling, I Manickam, ... Proceedings of the 2018 ACM International Symposium on Wearable Computers, 25-32, 2018 | 44 | 2018 |
| Characterization of mpc-based private inference for transformer-based models Y Wang, GE Suh, W Xiong, B Lefaudeux, B Knott, M Annavaram, ... 2022 IEEE International Symposium on Performance Analysis of Systems and …, 2022 | 32 | 2022 |
| Secure multiparty computations in floating-point arithmetic C Guo, A Hannun, B Knott, L van der Maaten, M Tygert, R Zhu Information and Inference: A Journal of the IMA 11 (1), 103-135, 2022 | 27 | 2022 |
| Envelope encoding of speech signals for transmission to cutaneous actuators R Turcott, A Israr, BA Knott, F Abnousi US Patent 10,943,503, 2021 | 27 | 2021 |
| Efficient evaluation of coding strategies for transcutaneous language communication R Turcott, J Chen, P Castillo, B Knott, W Setiawan, F Briggs, K Klumb, ... Haptics: Science, Technology, and Applications: 11th International …, 2018 | 22 | 2018 |
| Privacy-preserving multi-party contextual bandits A Hannun, B Knott, S Sengupta, L van der Maaten arXiv preprint arXiv:1910.05299, 2019 | 16 | 2019 |
| Benefits of coding in a noncoherent massive SIMO system B Knott, M Chowdhury, A Manolakos, AJ Goldsmith 2015 IEEE International Conference on Communications (ICC), 2350-2355, 2015 | 15 | 2015 |
| Haptic communication using interference of haptic outputs on skin BA Knott, R Turcott, A Israr US Patent 10,748,448, 2020 | 14 | 2020 |
| Machine translation of consonant-vowel pairs and syllabic units to haptic sequences for transmission via haptic device BA Knott, VP Chakkabala US Patent 10,222,864, 2019 | 11 | 2019 |
| CrypTen: a new research tool for secure machine learning with PyTorch D Gunning, A Hannun, M Ibrahim, B Knott, L van der Maaten, V Reis, ... Blog post available at https://ai. facebook. com/blog/crypten-a-new-research …, 2019 | 10 | 2019 |
| Resolution-defined projections for virtual reality video compression C Dunn, B Knott 2017 IEEE Virtual Reality (VR), 337-338, 2017 | 8 | 2017 |
| Neural network model for generation of compressed haptic actuator signal from audio input BA Knott, VP Chakkabala US Patent 11,355,033, 2022 | 7 | 2022 |
| Machine translation of consonant-vowel pairs and syllabic units to haptic sequences for transmission via haptic device BA Knott, VP Chakkabala US Patent 10,591,996, 2020 | 6 | 2020 |
| Characterizing and Improving MPC-based Private Inference for Transformer-based Models Y Wang, E Suh, W Xiong, B Knott, B Lefaudeux, M Annavaram, HH Lee NeurIPS 2021 Workshop Privacy in Machine Learning, 2021 | 3 | 2021 |
| Identifying Controversial Pairs in Item-to-Item Recommendations J Shen, D VR Oliveira, J Cao, B Knott, G Gu, S Vijaya Raghavan, Y Jin, ... Proceedings of the 17th ACM Conference on Recommender Systems, 671-674, 2023 | | 2023 |
| Neural network model for generation of compressed haptic actuator signal from audio input BA Knott, R Turcott, A Israr US Patent App. 17/734,813, 2022 | | 2022 |
| Supplemental Material for CRYPTEN: Secure Multi-Party Computation Meets Machine Learning B Knott, S Venkataraman, A Hannun, S Sengupta, M Ibrahim, ... | | |