1 citations · 1 across the 3 of their papers we have counts for
3 papers
Closed-form Filtering for Non-linear Systems
Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj +1
Sequential Bayesian Filtering aims to estimate the current state distribution of a Hidden Markov Model, given the past observations. The problem is well-known to be intractable for…
Measuring dissimilarity with diffeomorphism invariance
Théophile Cantelobre, Carlo Ciliberto, Benjamin Guedj +1
Measures of similarity (or dissimilarity) are a key ingredient to many machine learning algorithms. We introduce DID, a pairwise dissimilarity measure applicable to a wide range of…
A PAC-Bayesian Perspective on Structured Prediction with Implicit Loss Embeddings
Théophile Cantelobre, Benjamin Guedj, María Pérez-Ortiz +1
Many practical machine learning tasks can be framed as Structured prediction problems, where several output variables are predicted and considered interdependent. Recent theoretica…