4 papers · 1 filter
Beyond Mixtures and Products for Ensemble Aggregation: A Likelihood Perspective on Generalized Means
Raphaël Razafindralambo, Rémy Sun, Frédéric Precioso +2
Density aggregation is a central problem in machine learning, for instance when combining predictions from a Deep Ensemble. The choice of aggregation remains an open question with…
A Tutorial on Discriminative Clustering and Mutual Information
Louis Ohl, Pierre-Alexandre Mattei, Frédéric Precioso
To cluster data is to separate samples into distinctive groups that should ideally have some cohesive properties. Today, numerous clustering algorithms exist, and their differences…
Kernel KMeans clustering splits for end-to-end unsupervised decision trees
Louis Ohl, Pierre-Alexandre Mattei, Mickaël Leclercq +2
Trees are convenient models for obtaining explainable predictions on relatively small datasets. Although there are many proposals for the end-to-end construction of such trees in s…
Generalised Mutual Information: a Framework for Discriminative Clustering
Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron +4
In the last decade, recent successes in deep clustering majorly involved the Mutual Information (MI) as an unsupervised objective for training neural networks with increasing regul…