21 citations · 58 across the 29 of their papers we have counts for
4 papers · 1 filter
AI Model Disgorgement: Methods and Choices
Alessandro Achille, Michael Kearns, Carson Klingenberg +1
Responsible use of data is an indispensable part of any machine learning (ML) implementation. ML developers must carefully collect and curate their datasets, and document their pro…
À-la-carte Prompt Tuning (APT): Combining Distinct Data Via Composable Prompting
Benjamin Bowman, Alessandro Achille, Luca Zancato +4
We introduce À-la-carte Prompt Tuning (APT), a transformer-based scheme to tune prompts on distinct data so that they can be arbitrarily composed at inference time. The individual…
On the Learnability of Physical Concepts: Can a Neural Network Understand What's Real?
Alessandro Achille, Stefano Soatto
We revisit the classic signal-to-symbol barrier in light of the remarkable ability of deep neural networks to generate realistic synthetic data. DeepFakes and spoofing highlight th…
On Leave-One-Out Conditional Mutual Information For Generalization
Mohamad Rida Rammal, Alessandro Achille, Aditya Golatkar +2
We derive information theoretic generalization bounds for supervised learning algorithms based on a new measure of leave-one-out conditional mutual information (loo-CMI). Contrary…