102 citations · 176 across the 9 of their papers we have counts for
10 papers
A note on blind contact tracing at scale with applications to the COVID-19 pandemic
Jack K. Fitzsimons, Atul Mantri, Robert Pisarczyk +2
The current COVID-19 pandemic highlights the utility of contact tracing, when combined with case isolation and social distancing, as an important tool for mitigating the spread of…
Implicit Priors for Knowledge Sharing in Bayesian Neural Networks
Jack K Fitzsimons, Sebastian M Schmon, Stephen J Roberts
Bayesian interpretations of neural network have a long history, dating back to early work in the 1990's and have recently regained attention because of their desirable properties l…
Intersectionality: Multiple Group Fairness in Expectation Constraints
Jack Fitzsimons, Michael Osborne, Stephen Roberts
Group fairness is an important concern for machine learning researchers, developers, and regulators. However, the strictness to which models must be constrained to be considered fa…
A General Framework for Fair Regression
Jack Fitzsimons, AbdulRahman Al Ali, Michael Osborne +1
Fairness, through its many forms and definitions, has become an important issue facing the machine learning community. In this work, we consider how to incorporate group fairness c…
Smooth input preparation for quantum and quantum-inspired machine learning
Zhikuan Zhao, Jack K. Fitzsimons, Patrick Rebentrost +2
Machine learning has recently emerged as a fruitful area for finding potential quantum computational advantage. Many of the quantum enhanced machine learning algorithms critically…
Quantum algorithms for training Gaussian Processes
Zhikuan Zhao, Jack K. Fitzsimons, Michael A. Osborne +2
Gaussian processes (GPs) are important models in supervised machine learning. Training in Gaussian processes refers to selecting the covariance functions and the associated paramet…