153 citations · 282 across the 4 of their papers we have counts for
7 papers
Explicit-Duration Markov Switching Models
Silvia Chiappa
Markov switching models (MSMs) are probabilistic models that employ multiple sets of parameters to describe different dynamic regimes that a time series may exhibit at different pe…
Wasserstein Fair Classification
Ray Jiang, Aldo Pacchiano, Tom Stepleton +2
We propose an approach to fair classification that enforces independence between the classifier outputs and sensitive information by minimizing Wasserstein-1 distances. The approac…
Unsupervised Separation of Dynamics from Pixels
Silvia Chiappa, Ulrich Paquet
We present an approach to learn the dynamics of multiple objects from image sequences in an unsupervised way. We introduce a probabilistic model that first generate noisy positions…
A Causal Bayesian Networks Viewpoint on Fairness
Silvia Chiappa, William S. Isaac
We offer a graphical interpretation of unfairness in a dataset as the presence of an unfair causal path in the causal Bayesian network representing the data-generation mechanism. W…
Meta-learning of Sequential Strategies
Pedro A. Ortega, Jane X. Wang, Mark Rowland +21
In this report we review memory-based meta-learning as a tool for building sample-efficient strategies that learn from past experience to adapt to any task within a target class. O…
Degenerate Feedback Loops in Recommender Systems
Ray Jiang, Silvia Chiappa, Tor Lattimore +2
Machine learning is used extensively in recommender systems deployed in products. The decisions made by these systems can influence user beliefs and preferences which in turn affec…