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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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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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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
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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05/20/2020
Early Classification of Time Series. Cost-based Optimization Criterion and Algorithms
An increasing number of applications require to recognize the class of a...
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12/13/2019
From Shallow to Deep Interactions Between Knowledge Representation, Reasoning and Machine Learning (Kay R. Amel group)
This paper proposes a tentative and original survey of meeting points be...
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07/16/2017