Lauren Watson

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 13

Top Topics

Differentially Private

Top Venues

Proc. Priv. Enhancing Technol.

Publications

Gonzalo Martínez, Lauren Watson, Pedro Reviriego, José Alberto Hernández, Marc Juarez, Rik Sarkar
Towards Understanding the Interplay of Generative Artificial Intelligence and the Internet. Epi UAI (2024)
Lauren Watson, Eric Gan, Mohan Dantam, Baharan Mirzasoleiman, Rik Sarkar
Inference and Interference: The Role of Clipping, Pruning and Loss Landscapes in Differentially Private Stochastic Gradient Descent. CoRR (2023)
Lauren Watson, Zeno Kujawa, Rayna Andreeva, Hao-Tsung Yang, Tariq Elahi, Rik Sarkar
Accelerated Shapley Value Approximation for Data Evaluation. CoRR (2023)
Gonzalo Martínez Ruiz de Arcaute, Lauren Watson, Pedro Reviriego, José Alberto Hernández, Marc Juarez, Rik Sarkar
Combining Generative Artificial Intelligence (AI) and the Internet: Heading towards Evolution or Degradation? CoRR (2023)
Gonzalo Martínez Ruiz de Arcaute, Lauren Watson, Pedro Reviriego, José Alberto Hernández, Marc Juarez, Rik Sarkar
Towards Understanding the Interplay of Generative Artificial Intelligence and the Internet. CoRR (2023)
Benedek Rozemberczki, Lauren Watson, Péter Bayer, Hao-Tsung Yang, Oliver Kiss, Sebastian Nilsson, Rik Sarkar
The Shapley Value in Machine Learning. IJCAI (2022)
Benedek Rozemberczki, Lauren Watson, Péter Bayer, Hao-Tsung Yang, Oliver Kiss, Sebastian Nilsson, Rik Sarkar
The Shapley Value in Machine Learning. CoRR (2022)
Lauren Watson, Rayna Andreeva, Hao-Tsung Yang, Rik Sarkar
Differentially Private Shapley Values for Data Evaluation. CoRR (2022)
Lauren Watson, Abhirup Ghosh, Benedek Rozemberczki, Rik Sarkar
Continual and Sliding Window Release for Private Empirical Risk Minimization. CoRR (2022)
Lauren Watson, Chuan Guo, Graham Cormode, Alexandre Sablayrolles
On the Importance of Difficulty Calibration in Membership Inference Attacks. ICLR (2022)
Lauren Watson, Chuan Guo, Graham Cormode, Alexandre Sablayrolles
On the Importance of Difficulty Calibration in Membership Inference Attacks. CoRR (2021)
Lauren Watson, Benedek Rozemberczki, Rik Sarkar
Stability Enhanced Privacy and Applications in Private Stochastic Gradient Descent. CoRR (2020)
Lauren Watson, Anupam Mediratta, Tariq Elahi, Rik Sarkar
Privacy Preserving Detection of Path Bias Attacks in Tor. Proc. Priv. Enhancing Technol. 2020 (4) (2020)