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Fairness with Continuous Optimal Transport
Whilst optimal transport (OT) is increasingly being recognized as a powe...
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Fairness in Machine Learning
Machine learning based systems are reaching society at large and in many...
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Explicit-Duration Markov Switching Models
Markov switching models (MSMs) are probabilistic models that employ mult...
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Wasserstein Fair Classification
We propose an approach to fair classification that enforces independence...
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Unsupervised Separation of Dynamics from Pixels
We present an approach to learn the dynamics of multiple objects from im...
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A Causal Bayesian Networks Viewpoint on Fairness
We offer a graphical interpretation of unfairness in a dataset as the pr...
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Meta-learning of Sequential Strategies
In this report we review memory-based meta-learning as a tool for buildi...
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Degenerate Feedback Loops in Recommender Systems
Machine learning is used extensively in recommender systems deployed in ...
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Causal Reasoning from Meta-reinforcement Learning
Discovering and exploiting the causal structure in the environment is a ...
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Path-Specific Counterfactual Fairness
We consider the problem of learning fair decision systems in complex sce...
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Recurrent Environment Simulators
Models that can simulate how environments change in response to actions ...
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Unified Treatment of Hidden Markov Switching Models
Many real-world problems encountered in several disciplines deal with th...
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