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09/08/2023
Viewing the process of generating counterfactuals as a source of knowledge – Application to the Naive Bayes classifier
There are now many comprehension algorithms for understanding the decisi...
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08/29/2023
Biquality Learning: a Framework to Design Algorithms Dealing with Closed-Set Distribution Shifts
Training machine learning models from data with weak supervision and dat...
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08/18/2023
biquality-learn: a Python library for Biquality Learning
The democratization of Data Mining has been widely successful thanks in ...
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08/02/2023
Automatic Feature Engineering for Time Series Classification: Evaluation and Discussion
Time Series Classification (TSC) has received much attention in the past...
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07/31/2023
An Efficient Shapley Value Computation for the Naive Bayes Classifier
Variable selection or importance measurement of input variables to a mac...
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06/22/2023
An Interactive Interface for Novel Class Discovery in Tabular Data
Novel Class Discovery (NCD) is the problem of trying to discover novel c...
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03/10/2023
Efficient simulation of individual-based population models: the R Package IBMPopSim
The R Package IBMPopSim (https://daphnegiorgi.github.io/IBMPopSim/) aims...
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02/22/2023
Novel Class Discovery: an Introduction and Key Concepts
Novel Class Discovery (NCD) is a growing field where we are given during...
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11/28/2022
Découvrir de nouvelles classes dans des données tabulaires
In Novel Class Discovery (NCD), the goal is to find new classes in an un...
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09/02/2022
A Method for Discovering Novel Classes in Tabular Data
In Novel Class Discovery (NCD), the goal is to find new classes in an un...
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04/27/2022
Open challenges for Machine Learning based Early Decision-Making research
More and more applications require early decisions, i.e. taken as soon a...
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04/01/2022
ECOTS: Early Classification in Open Time Series
Learning to predict ahead of time events in open time series is challeng...
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09/21/2021
Early and Revocable Time Series Classification
Many approaches have been proposed for early classification of time seri...
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08/20/2021
Contrastive Representations for Label Noise Require Fine-Tuning
In this paper we show that the combination of a Contrastive representati...
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04/27/2021
Early Classification of Time Series is Meaningful
Many approaches have been proposed for early classification of time seri...
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03/15/2021
Interpretable Feature Construction for Time Series Extrinsic Regression
Supervised learning of time series data has been extensively studied for...
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12/16/2020
Predictive K-means with local models
Supervised classification can be effective for prediction but sometimes ...
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12/16/2020
Learning active learning at the crossroads? evaluation and discussion
Active learning aims to reduce annotation cost by predicting which sampl...
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12/16/2020
From Weakly Supervised Learning to Biquality Learning, a brief introduction
The field of Weakly Supervised Learning (WSL) has recently seen a surge ...
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10/19/2020
Importance Reweighting for Biquality Learning
The field of Weakly Supervised Learning (WSL) has recently seen a surge ...
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03/08/2019
Should we Reload Time Series Classification Performance Evaluation ? (a position paper)
Since the introduction and the public availability of the ucr time serie...
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11/06/2018
Day-ahead time series forecasting: application to capacity planning
In the context of capacity planning, forecasting the evolution of inform...
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06/10/2015
