1.9k citations · 3.7k across the 35 of their papers we have counts for
5 papers · 1 filter
EIFFeL: Ensuring Integrity for Federated Learning
Amrita Roy Chowdhury, Chuan Guo, Somesh Jha +1
Federated learning (FL) enables clients to collaborate with a server to train a machine learning model. To ensure privacy, the server performs secure aggregation of updates from th…
Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems
Ruihan Wu, Chuan Guo, Awni Hannun +1
Machine-learning systems such as self-driving cars or virtual assistants are composed of a large number of machine-learning models that recognize image content, transcribe speech,…
Making Paper Reviewing Robust to Bid Manipulation Attacks
Ruihan Wu, Chuan Guo, Felix Wu +3
Most computer science conferences rely on paper bidding to assign reviewers to papers. Although paper bidding enables high-quality assignments in days of unprecedented submission n…
Measuring Data Leakage in Machine-Learning Models with Fisher Information
Awni Hannun, Chuan Guo, Laurens van der Maaten
Machine-learning models contain information about the data they were trained on. This information leaks either through the model itself or through predictions made by the model. Co…
Physical Reasoning Using Dynamics-Aware Models
Eltayeb Ahmed, Anton Bakhtin, Laurens van der Maaten +1
A common approach to solving physical reasoning tasks is to train a value learner on example tasks. A limitation of such an approach is that it requires learning about object dynam…