1 citations · 2 across the 5 of their papers we have counts for
6 papers
Generalization Properties of Decision Trees on Real-valued and Categorical Features
Jean-Samuel Leboeuf, Frédéric LeBlanc, Mario Marchand
We revisit binary decision trees from the perspective of partitions of the data. We introduce the notion of partitioning function, and we relate it to the growth function and to th…
Improving Generalization Bounds for VC Classes Using the Hypergeometric Tail Inversion
Jean-Samuel Leboeuf, Frédéric LeBlanc, Mario Marchand
We significantly improve the generalization bounds for VC classes by using two main ideas. First, we consider the hypergeometric tail inversion to obtain a very tight non-uniform d…
Decision trees as partitioning machines to characterize their generalization properties
Jean-Samuel Leboeuf, Frédéric LeBlanc, Mario Marchand
Decision trees are popular machine learning models that are simple to build and easy to interpret. Even though algorithms to learn decision trees date back to almost 50 years, key…
Attending Form and Context to Generate Specialized Out-of-VocabularyWords Representations
Nicolas Garneau, Jean-Samuel Leboeuf, Yuval Pinter +1
We propose a new contextual-compositional neural network layer that handles out-of-vocabulary (OOV) words in natural language processing (NLP) tagging tasks. This layer consists of…
Predicting and interpreting embeddings for out of vocabulary words in downstream tasks
Nicolas Garneau, Jean-Samuel Leboeuf, Luc Lamontagne
We propose a novel way to handle out of vocabulary (OOV) words in downstream natural language processing (NLP) tasks. We implement a network that predicts useful embeddings for OOV…
A No-Go Theorem for Fully SGUTs with Metastable SUSY Breaking
Jean-François Fortin, Jean-Samuel Leboeuf
We introduce fully SGUTs, SUSY grand unified theories that, upon symmetry breaking through the Higgs mechanism, decompose into a visible sector and an extra sector where the dynami…