134 citations · 179 across the 8 of their papers we have counts for
5 papers · 1 filter
SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems
Edward Chou, Florian Tramèr, Giancarlo Pellegrino
SentiNet is a novel detection framework for localized universal attacks on neural networks. These attacks restrict adversarial noise to contiguous portions of an image and are reus…
Faster CryptoNets: Leveraging Sparsity for Real-World Encrypted Inference
Edward Chou, Josh Beal, Daniel Levy +3
Homomorphic encryption enables arbitrary computation over data while it remains encrypted. This privacy-preserving feature is attractive for machine learning, but requires signific…
A Fully Private Pipeline for Deep Learning on Electronic Health Records
Edward Chou, Thao Nguyen, Josh Beal +2
We introduce an end-to-end private deep learning framework, applied to the task of predicting 30-day readmission from electronic health records. By using differential privacy durin…
Privacy-Preserving Action Recognition for Smart Hospitals using Low-Resolution Depth Images
Edward Chou, Matthew Tan, Cherry Zou +4
Computer-vision hospital systems can greatly assist healthcare workers and improve medical facility treatment, but often face patient resistance due to the perceived intrusiveness…
AI Blue Book: Vehicle Price Prediction using Visual Features
Richard R. Yang, Steven Chen, Edward Chou
In this work, we build a series of machine learning models to predict the price of a product given its image, and visualize the features that result in higher or lower price predic…