21 citations · 122 across the 18 of their papers we have counts for
5 papers · 1 filter
Addressing Missing Sources with Adversarial Support-Matching
Thomas Kehrenberg, Myles Bartlett, Viktoriia Sharmanska +1
When trained on diverse labeled data, machine learning models have proven themselves to be a powerful tool in all facets of society. However, due to budget limitations, deliberate…
Tuning Fairness by Balancing Target Labels
Thomas Kehrenberg, Zexun Chen, Novi Quadrianto
The issue of fairness in machine learning models has recently attracted a lot of attention as ensuring it will ensure continued confidence of the general public in the deployment o…
Gray-box inference for structured Gaussian process models
Pietro Galliani, Amir Dezfouli, Edwin V. Bonilla +1
We develop an automated variational inference method for Bayesian structured prediction problems with Gaussian process (GP) priors and linear-chain likelihoods. Our approach does n…
Mind the Nuisance: Gaussian Process Classification using Privileged Noise
Daniel Hernández-Lobato, Viktoriia Sharmanska, Kristian Kersting +2
The learning with privileged information setting has recently attracted a lot of attention within the machine learning community, as it allows the integration of additional knowled…
Bayesian Structured Prediction Using Gaussian Processes
Sebastien Bratieres, Novi Quadrianto, Zoubin Ghahramani
We introduce a conceptually novel structured prediction model, GPstruct, which is kernelized, non-parametric and Bayesian, by design. We motivate the model with respect to existing…