16 citations · 27 across the 5 of their papers we have counts for
5 papers
Inference and Interference: The Role of Clipping, Pruning and Loss Landscapes in Differentially Private Stochastic Gradient Descent
Lauren Watson, Eric Gan, Mohan Dantam +2
Differentially private stochastic gradient descent (DP-SGD) is known to have poorer training and test performance on large neural networks, compared to ordinary stochastic gradient…
Accelerated Shapley Value Approximation for Data Evaluation
Lauren Watson, Zeno Kujawa, Rayna Andreeva +3
Data valuation has found various applications in machine learning, such as data filtering, efficient learning and incentives for data sharing. The most popular current approach to…
Towards Understanding the Interplay of Generative Artificial Intelligence and the Internet
Gonzalo Martínez, Lauren Watson, Pedro Reviriego +3
The rapid adoption of generative Artificial Intelligence (AI) tools that can generate realistic images or text, such as DALL-E, MidJourney, or ChatGPT, have put the societal impact…
Metric Space Magnitude and Generalisation in Neural Networks
Rayna Andreeva, Katharina Limbeck, Bastian Rieck +1
Deep learning models have seen significant successes in numerous applications, but their inner workings remain elusive. The purpose of this work is to quantify the learning process…
Combining Generative Artificial Intelligence (AI) and the Internet: Heading towards Evolution or Degradation?
Gonzalo Martínez, Lauren Watson, Pedro Reviriego +3
In the span of a few months, generative Artificial Intelligence (AI) tools that can generate realistic images or text have taken the Internet by storm, making them one of the techn…