activity
20222024
most citedNovel Class Discovery: an Introduction and Key Concepts

4 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2024

Constructing Variables Using Classifiers as an Aid to Regression: An Empirical Assessment

Colin Troisemaine, Vincent Lemaire

This paper proposes a method for the automatic creation of variables (in the case of regression) that complement the information contained in the initial input vector. The method w…

cs.LG2023★ 1 cited

A Practical Approach to Novel Class Discovery in Tabular Data

Colin Troisemaine, Alexandre Reiffers-Masson, Stéphane Gosselin +2

The problem of Novel Class Discovery (NCD) consists in extracting knowledge from a labeled set of known classes to accurately partition an unlabeled set of novel classes. While NCD…

cs.LG2023★ 1 cited

An Interactive Interface for Novel Class Discovery in Tabular Data

Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin +3

Novel Class Discovery (NCD) is the problem of trying to discover novel classes in an unlabeled set, given a labeled set of different but related classes. The majority of NCD method…

cs.LG2023★ 4 cited

Novel Class Discovery: an Introduction and Key Concepts

Colin Troisemaine, Vincent Lemaire, Stéphane Gosselin +3

Novel Class Discovery (NCD) is a growing field where we are given during training a labeled set of known classes and an unlabeled set of different classes that must be discovered.…

cs.LG2022

A Method for Discovering Novel Classes in Tabular Data

Colin Troisemaine, Joachim Flocon-Cholet, Stéphane Gosselin +3

In Novel Class Discovery (NCD), the goal is to find new classes in an unlabeled set given a labeled set of known but different classes. While NCD has recently gained attention from…