Scientific talk by Louis Ohl (MAASAI team)
Generalised mutual information (GEMINI) –
A constellation of discriminative clustering models
Abstract: Clustering is a fundamental learning task which consists in separating data samples into several groups, each called a cluster. The last decade witnessed increasing successes in the field of deep clustering that tries to tackle clustering with neural networks. Often belonging to the family of discriminative models, these methods used mutual information (MI) as an unsupervised objective with increasing regularisations. In this presentation, we focus on the discriminative modelling and question the relevance of MI as a clustering objective. To adress these limitations, we developed a novel objective function: the generalised mutual information (GEMINI). We then show how this objective can be combined with various architectures from deep neural networks to decision trees, even with sparsity constraints for feature selection.
When: Monday, Feb 05 at 2pm
Where: Euler Violet