164 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- J. Darmont2 profiles17 · h 23
- Julien Velcin2 profiles9 · h 13
- Cécile Favre2 profiles5 · h 14
- Sabine Loudcher2 profiles5 · h 14
- Pegdwendé N. Sawadogo2 profiles4 · h 4
- Adrien Guille3 · h 10
- F. Ravat3 · h 20
- Gael Poux-Medard3 · h 6
- Guillaume Metzler2 profiles3 · h 2
- Irina Proskurina3 · h 4
- J. Jacques3 · h 19
- O. Teste3 · h 25
- Université Lumière Lyon 2FR21 papers
- Seattle Epidemiologic Information and Research CenterUS12 papers
- Lyon 1 UniversitéFR10 papers
- Centre National de la Recherche ScientifiqueFR5 papers
- Université de LyonFR4 papers
- Université Toulouse III - Paul SabatierFR4 papers
- Institut de Recherche en Informatique de ToulouseFR3 papers
- Institut Polytechnique de BordeauxFR3 papers
- Laboratoire d'Informatique en Images et Systèmes d'InformationFR3 papers
- Université Fédérale de Toulouse Midi-PyrénéesFR3 papers
- Université Pierre Mendès FranceFR3 papers
- Université Toulouse-I-CapitoleFR3 papers
42 papers
PAC-Bayesian Bounds on Constrained f-Entropic Risk Measures
Hind Atbir, Farah Cherfaoui, Guillaume Metzler +2
PAC generalization bounds on the risk, when expressed in terms of the expected loss, are often insufficient to capture imbalances between subgroups in the data. To overcome this li…
PAC-Bayesian Reinforcement Learning Trains Generalizable Policies
Abdelkrim Zitouni, Mehdi Hennequin, Juba Agoun +3
We derive a novel PAC-Bayesian generalization bound for reinforcement learning that explicitly accounts for Markov dependencies in the data, through the chain's mixing time. This c…
MMM: Clustering Multivariate Longitudinal Mixed-type Data
Francesco Amato, Julien Jacques
Multivariate longitudinal data of mixed-type are increasingly collected in many science domains. However, algorithms to cluster this kind of data remain scarce, due to the challeng…
Pr{é}diction optimale pour un mod{è}le ordinal {à} covariables fonctionnelles
Simón Weinberger, Jairo Cugliari, Aurélie Le Cain
We present a prediction framework for ordinal models: we introduce optimal predictions using loss functions and give the explicit form of the Least-Absolute-Deviation prediction fo…
Natural Language Querying System Through Entity Enrichment
Joshua Amavi, Mirian Halfeld Ferrari, Nicolas Hiot
This paper focuses on a domain expert querying system over databases. It presents a solution designed for a French enterprise interested in offering a natural language interface fo…
When Quantization Affects Confidence of Large Language Models?
Irina Proskurina, Luc Brun, Guillaume Metzler +1
Recent studies introduced effective compression techniques for Large Language Models (LLMs) via post-training quantization or low-bit weight representation. Although quantized weig…
Time topological analysis of EEG using signature theory
Stéphane Chrétien, Ben Gao, Astrid Thebault-Guiochon +1
Anomaly detection in multivariate signals is a task of paramount importance in many disciplines (epidemiology, finance, cognitive sciences and neurosciences, oncology, etc.). In th…
Dataversifying Natural Sciences: Pioneering a Data Lake Architecture for Curated Data-Centric Experiments in Life \& Earth Sciences
Genoveva Vargas-Solar, Jérôme Darmont, Alejandro Adorjan +6
This vision paper introduces a pioneering data lake architecture designed to meet Life \& Earth sciences' burgeoning data management needs. As the data landscape evolves, the imper…
Collaborative business intelligence virtual assistant
Olga Cherednichenko, Fahad Muhammad
The present-day business landscape necessitates novel methodologies that integrate intelligent technologies and tools capable of swiftly providing precise and dependable informatio…
Mini Minds: Exploring Bebeshka and Zlata Baby Models
Irina Proskurina, Guillaume Metzler, Julien Velcin
In this paper, we describe the University of Lyon 2 submission to the Strict-Small track of the BabyLM competition. The shared task is created with an emphasis on small-scale langu…
A Reference Model for Collaborative Business Intelligence Virtual Assistants
Olga Cherednichenko, Fahad Muhammad, Jérôme Darmont +1
Collaborative Business Analysis (CBA) is a methodology that involves bringing together different stakeholders, including business users, analysts, and technical specialists, to col…
Can BERT eat RuCoLA? Topological Data Analysis to Explain
Irina Proskurina, Irina Piontkovskaya, Ekaterina Artemova
This paper investigates how Transformer language models (LMs) fine-tuned for acceptability classification capture linguistic features. Our approach uses the best practices of topol…
Rumor Classification through a Multimodal Fusion Framework and Ensemble Learning
Abderrazek Azri, Cécile Favre, Nouria Harbi +2
The proliferation of rumors on social media has become a major concern due to its ability to create a devastating impact. Manually assessing the veracity of social media messages i…
Dirichlet-Survival Process: Scalable Inference of Topic-Dependent Diffusion Networks
Gaël Poux-Médard, Julien Velcin, Sabine Loudcher
Information spread on networks can be efficiently modeled by considering three features: documents' content, time of publication relative to other publications, and position of the…
Dimensional Data KNN-Based Imputation
Yuzhao Yang, Jérôme Darmont, Franck Ravat +1
Data Warehouses (DWs) are core components of Business Intelligence (BI). Missing data in DWs have a great impact on data analyses. Therefore, missing data need to be completed. Unl…
Properties of Reddit News Topical Interactions
Gaël Poux-Médard, Julien Velcin, Sabine Loudcher
Most models of information diffusion online rely on the assumption that pieces of information spread independently from each other. However, several works pointed out the necessity…
Internal Data Imputation in Data Warehouse Dimensions
Yuzhao Yang, Fatma Abdelhedi, Jérôme Darmont +2
Missing values occur commonly in the multidimensional data warehouses. They may generate problems of usefulness of data since the analysis performed on a multidimensional data ware…
Benchmarking Data Lakes Featuring Structured and Unstructured Data with DLBench
Pegdwendé Sawadogo, Jérôme Darmont
In the last few years, the concept of data lake has become trendy for data storage and analysis. Thus, several design alternatives have been proposed to build data lake systems. Ho…
goldMEDAL : une nouvelle contribution {à} la mod{é}lisation g{é}n{é}rique des m{é}tadonn{é}es des lacs de donn{é}es
Etienne Scholly, Pegdwendé Sawadogo, Pengfei Liu +5
We summarize here a paper published in 2021 in the DOLAP international workshop DOLAP associated with the EDBT and ICDT conferences. We propose goldMEDAL, a generic metadata model…
Simultaneous predictive bands for functional time series using minimum entropy sets
Nicolás Hernández, Jairo Cugliari, Julien Jacques
Functional Time Series are sequences of dependent random elements taking values on some functional space. Most of the research on this domain is focused on producing a predictor ab…
A Note on Data Simulations for Voting by Evaluation
Antoine Rolland, Jean-Baptiste Aubin, Irène Gannaz +1
Voting rules based on evaluation inputs rather than preference orders have been recently proposed, like majority judgement, range voting or approval voting. Traditionally, probabil…
Information Interaction Profile of Choice Adoption
Gaël Poux-Médard, Julien Velcin, Sabine Loudcher
Interactions between pieces of information (entities) play a substantial role in the way an individual acts on them: adoption of a product, the spread of news, strategy choice, etc…
Coining goldMEDAL: A New Contribution to Data Lake Generic Metadata Modeling
Etienne Scholly, Pegdwendé Sawadogo, Pengfei Liu +5
The rise of big data has revolutionized data exploitation practices and led to the emergence of new concepts. Among them, data lakes have emerged as large heterogeneous data reposi…
Feedback from the participants of the ADBIS, TPDL and EDA 2020 joint conferences
Pegdwendé Sawadogo, Jérôme Darmont, Fabien Duchateau
This paper presents the way the joint ADBIS, TPDL and EDA 2020 conferences were organized online and the results of the participant survey conducted thereafter. We present the less…