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ORCIDNikita Dhawan
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2020 – today
- 2024
[j1]Nikita Dhawan, Nicole Mitchell, Zachary Charles, Zachary Garrett, Gintare Karolina Dziugaite:
Leveraging Function Space Aggregation for Federated Learning at Scale. Trans. Mach. Learn. Res. 2024 (2024)- [i6]Nikita Dhawan, Leonardo Cotta, Karen Ullrich, Rahul G. Krishnan, Chris J. Maddison:
End-To-End Causal Effect Estimation from Unstructured Natural Language Data. CoRR abs/2407.07018 (2024) - 2023
- [c5]Nikita Dhawan, Sicong Huang, Juhan Bae, Roger Baker Grosse:
Efficient Parametric Approximations of Neural Network Function Space Distance. ICML 2023: 7795-7812 - [i5]Nikita Dhawan, Sicong Huang, Juhan Bae, Roger B. Grosse:
Efficient Parametric Approximations of Neural Network Function Space Distance. CoRR abs/2302.03519 (2023) - [i4]Nikita Dhawan, Nicole Mitchell, Zachary Charles, Zachary Garrett, Gintare Karolina Dziugaite:
Leveraging Function Space Aggregation for Federated Learning at Scale. CoRR abs/2311.10291 (2023) - 2022
- [c4]Adam Dziedzic, Nikita Dhawan, Muhammad Ahmad Kaleem, Jonas Guan, Nicolas Papernot:
On the Difficulty of Defending Self-Supervised Learning against Model Extraction. ICML 2022: 5757-5776 - [c3]Adam Dziedzic, Haonan Duan, Muhammad Ahmad Kaleem, Nikita Dhawan, Jonas Guan, Yannis Cattan, Franziska Boenisch, Nicolas Papernot:
Dataset Inference for Self-Supervised Models. NeurIPS 2022 - [i3]Adam Dziedzic, Nikita Dhawan, Muhammad Ahmad Kaleem, Jonas Guan, Nicolas Papernot:
On the Difficulty of Defending Self-Supervised Learning against Model Extraction. CoRR abs/2205.07890 (2022) - [i2]Adam Dziedzic, Haonan Duan, Muhammad Ahmad Kaleem, Nikita Dhawan, Jonas Guan, Yannis Cattan, Franziska Boenisch, Nicolas Papernot:
Dataset Inference for Self-Supervised Models. CoRR abs/2209.09024 (2022) - 2021
- [c2]Marvin Zhang, Henrik Marklund, Nikita Dhawan, Abhishek Gupta, Sergey Levine, Chelsea Finn:
Adaptive Risk Minimization: Learning to Adapt to Domain Shift. NeurIPS 2021: 23664-23678 - 2020
- [c1]Laura M. Smith, Nikita Dhawan, Marvin Zhang, Pieter Abbeel, Sergey Levine:
AVID: Learning Multi-Stage Tasks via Pixel-Level Translation of Human Videos. Robotics: Science and Systems 2020
2010 – 2019
- 2019
- [i1]Laura M. Smith, Nikita Dhawan, Marvin Zhang, Pieter Abbeel, Sergey Levine:
AVID: Learning Multi-Stage Tasks via Pixel-Level Translation of Human Videos. CoRR abs/1912.04443 (2019)
Coauthor Index
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last updated on 2024-08-17 23:37 CEST by the dblp team
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