24 citations · 59 across the 12 of their papers we have counts for
4 papers · 1 filter
Machine Learning for a Low-cost Air Pollution Network
Michael T. Smith, Joel Ssematimba, Mauricio A. Alvarez +1
Data collection in economically constrained countries often necessitates using approximate and biased measurements due to the low-cost of the sensors used. This leads to potentiall…
Differentially Private Regression and Classification with Sparse Gaussian Processes
Michael Thomas Smith, Mauricio A. Alvarez, Neil D. Lawrence
A continuing challenge for machine learning is providing methods to perform computation on data while ensuring the data remains private. In this paper we build on the provable priv…
Adversarial Vulnerability Bounds for Gaussian Process Classification
Michael Thomas Smith, Kathrin Grosse, Michael Backes +1
Machine learning (ML) classification is increasingly used in safety-critical systems. Protecting ML classifiers from adversarial examples is crucial. We propose that the main threa…
Multi-task Learning for Aggregated Data using Gaussian Processes
Fariba Yousefi, Michael Thomas Smith, Mauricio A. Álvarez
Aggregated data is commonplace in areas such as epidemiology and demography. For example, census data for a population is usually given as averages defined over time periods or spa…