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02/02/2023
Uncertainty in Fairness Assessment: Maintaining Stable Conclusions Despite Fluctuations
Several recent works encourage the use of a Bayesian framework when asse...
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11/14/2022
A Survey on Preserving Fairness Guarantees in Changing Environments
Human lives are increasingly being affected by the outcomes of automated...
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11/07/2022
Okapi: Generalising Better by Making Statistical Matches Match
We propose Okapi, a simple, efficient, and general method for robust sem...
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09/27/2022
A Snapshot of the Frontiers of Client Selection in Federated Learning
Federated learning (FL) has been proposed as a privacy-preserving approa...
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08/03/2022
RealPatch: A Statistical Matching Framework for Model Patching with Real Samples
Machine learning classifiers are typically trained to minimise the avera...
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03/24/2022
Addressing Missing Sources with Adversarial Support-Matching
When trained on diverse labeled data, machine learning models have prove...
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08/12/2020
Null-sampling for Interpretable and Fair Representations
We propose to learn invariant representations, in the data domain, to ac...
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04/14/2020
Contrastive Examples for Addressing the Tyranny of the Majority
Computer vision algorithms, e.g. for face recognition, favour groups of ...
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03/12/2020
Causal datasheet: An approximate guide to practically assess Bayesian networks in the real world
In solving real-world problems like changing healthcare-seeking behavior...
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11/22/2019
Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution
Learning models with discrete latent variables using stochastic gradient...
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10/15/2018
Neural Styling for Interpretable Fair Representations
We observe a rapid increase in machine learning models for learning data...
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10/12/2018
Interpretable Fairness via Target Labels in Gaussian Process Models
Addressing fairness in machine learning models has recently attracted a ...
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09/14/2016
Gray-box inference for structured Gaussian process models
We develop an automated variational inference method for Bayesian struct...
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10/01/2014
Learning to Transfer Privileged Information
We introduce a learning framework called learning using privileged infor...
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07/01/2014
Mind the Nuisance: Gaussian Process Classification using Privileged Noise
The learning with privileged information setting has recently attracted ...
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09/26/2013
The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models
We propose a probabilistic model to infer supervised latent variables in...
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07/15/2013
Bayesian Structured Prediction Using Gaussian Processes
We introduce a conceptually novel structured prediction model, GPstruct,...
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06/18/2012
