2 citations · 2 across the 7 of their papers we have counts for
7 papers
Are We Lost in the Woods? Detecting Silent Semantic Faults for Random Forest Classifiers with Data-informed Static Analysis
Willem Meijer, Louis Ohl, Kristian Sandahl +1
While machine learning (ML) software necessitates effective quality assurance, ML engineers still encounter silent semantic faults, such as imbalanced datasets, that degrade predic…
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…
Discriminative Ordering Through Ensemble Consensus
Louis Ohl, Fredrik Lindsten
Evaluating the performance of clustering models is a challenging task where the outcome depends on the definition of what constitutes a cluster. Due to this design, current existin…
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…
Sparse and geometry-aware generalisation of the mutual information for joint discriminative clustering and feature selection
Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron +3
Feature selection in clustering is a hard task which involves simultaneously the discovery of relevant clusters as well as relevant variables with respect to these clusters. While…
Generalised Mutual Information 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…