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Michael Lomnitz
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2020 – today
- 2024
- [c6]Jun Hu, Phil Miller, Michael Lomnitz, Saurabh Farkya, Emre Yilmaz, Aswin Raghavan, David C. Zhang, Michael R. Piacentino:
Tools Identification By On-Board Adaptation of Vision-and-Language Models. AAAI 2024: 23799-23801 - 2023
- [c5]Michael Lomnitz, Zachary Daniels, Saurabh Farkya, Michael A. Isnardi, David C. Zhang, Michael R. Piacentino:
Learning with Local Gradients at the Edge. SMC 2023: 3146-3151 - [i6]Zachary A. Daniels, Jun Hu, Michael Lomnitz, Phil Miller, Aswin Raghavan, Joe Zhang, Michael R. Piacentino, David C. Zhang:
Efficient Model Adaptation for Continual Learning at the Edge. CoRR abs/2308.02084 (2023) - 2022
- [c4]Indhumathi Kandaswamy, Saurabh Farkya, Zachary Daniels, Gooitzen van der Wal, Aswin Raghavan, Yuzheng Zhang, Jun Hu, Michael Lomnitz, Michael A. Isnardi, David C. Zhang, Michael R. Piacentino:
Real-time Hyper-Dimensional Reconfiguration at the Edge using Hardware Accelerators. CVPR Workshops 2022: 3609-3617 - [i5]Indhumathi Kandaswamy, Saurabh Farkya, Zachary Daniels, Gooitzen van der Wal, Aswin Raghavan, Yuzheng Zhang, Jun Hu, Michael Lomnitz, Michael A. Isnardi, David C. Zhang, Michael R. Piacentino:
Real-time Hyper-Dimensional Reconfiguration at the Edge using Hardware Accelerators. CoRR abs/2206.05128 (2022) - [i4]Michael Lomnitz, Zachary Daniels, David C. Zhang, Michael R. Piacentino:
Learning with Local Gradients at the Edge. CoRR abs/2208.08503 (2022) - 2020
- [c3]John K. Lewis, Imad Eddine Toubal, Helen Chen, Vishal Sandesera, Michael Lomnitz, Zigfried Hampel-Arias, Prasad Calyam, Kannappan Palaniappan:
Deepfake Video Detection Based on Spatial, Spectral, and Temporal Inconsistencies Using Multimodal Deep Learning. AIPR 2020: 1-9 - [c2]Michael Lomnitz, Zigfried Hampel-Arias, Vishal Sandesara, Simon Hu:
Multimodal Approach for DeepFake Detection. AIPR 2020: 1-9 - [c1]Mahesh Kumar Nandwana, Michael Lomnitz, Colleen Richey, Mitchell McLaren, Diego Castán, Luciana Ferrer, Aaron Lawson:
The VOiCES from a Distance Challenge 2019: Analysis of Speaker Verification Results and Remaining Challenges. Odyssey 2020: 165-170 - [i3]Michael Lomnitz, Zigfried Hampel-Arias, Nina Lopatina, Felipe A. Mejia:
A general approach to bridge the reality-gap. CoRR abs/2009.01865 (2020)
2010 – 2019
- 2019
- [i2]Felipe A. Mejia, Paul Gamble, Zigfried Hampel-Arias, Michael Lomnitz, Nina Lopatina, Lucas Tindall, Maria Alejandra Barrios:
Robust or Private? Adversarial Training Makes Models More Vulnerable to Privacy Attacks. CoRR abs/1906.06449 (2019) - [i1]Michael Lomnitz, Nina Lopatina, Paul Gamble, Zigfried Hampel-Arias, Lucas Tindall, Felipe A. Mejia, Maria Alejandra Barrios:
Reducing audio membership inference attack accuracy to chance: 4 defenses. CoRR abs/1911.01888 (2019)
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last updated on 2024-07-31 20:48 CEST by the dblp team
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