Fabrice Popineau

Laboratoire Interdisciplinaire des Sciences du Numérique

Self-supervision is often used for pre-training to foster performance on a downstream task by constructing meaningful representations of samples. Self-supervised learning (SSL) generally involves generating different views of the same sample and thus requires data augmentations that are challenging to construct for tabular data. This constitutes on...

This study explores the application of anomaly detection (AD) methods in imbalanced learning tasks, focusing on fraud detection using real online credit card payment data. We assess the performance of several recent AD methods and compare their effectiveness against standard supervised learning methods. Offering evidence of distribution shift withi...

This book series, “Chronicle of Computing,” aims to facilitate increased opportunities for cross-fertilization across the disciplines and topics in Computing. Book proposals are solicited for consideration in all disciplines of Computing and including, but not limited to, Computer Engineering, Computer Science, Information Systems, Information Tech...

Deep Reinforcement Learning approaches to Online Portfolio Selection have grown in popularity in recent years. The sensitive nature of training Reinforcement Learning agents implies a need for extensive efforts in market representation, behavior objectives, and training processes, which have often been lacking in previous works. We propose a traini...

Anomaly detection is crucial in various domains, such as finance, healthcare, and cybersecurity. In this paper, we propose a novel deep anomaly detection method for tabular data that leverages Non-Parametric Transformers (NPTs), a model initially proposed for supervised tasks, to capture both feature-feature and sample-sample dependencies. In a rec...

As with many other tasks, neural networks prove very effective for anomaly detection purposes. However, very few deep-learning models are suited for detecting anomalies on tabular datasets. This paper proposes a novel methodology to flag anomalies based on TracIn, an influence measure initially introduced for explicability purposes. The proposed me...

The goal of the Semantic Textual Similarity task is to automatically quantify the semantic similarity of two text snippets. Since 2012, the task has been organized on a yearly basis as a part of the SemEval evaluation campaign. This paper presents a method that aims to combine different sentence-based vector representations in order to improve the...

Today Online Learning Environments (OLE) like MOOCs and LMS are very commonly used and a huge number of students with very different profiles and backgrounds follow the same online courses. Still, personalized experience for attendees is not widely spread on the platforms hosting these courses. At the same time, there is a growing number of open ed...

Spaced repetition is among the most studied learning strategies in the cognitive science literature. It consists in temporally distributing exposure to an information so as to improve long-term memorization. Providing students with an adaptive and personalized distributed practice schedule would benefit more than just a generic scheduler. However,...

Les MOOC accueillent des apprenants de compétences très diverses. Afin de connaître leurs multiples besoins, il est possible de leur faire passer un test d'élicitation de connaissances, en profitant du fait que l'évaluation se fasse en ligne pour choisir la question suivante en fonction des réponses précédentes. Le test est alors dit adaptatif, il...

In large-scale assessments such as the ones encountered in MOOCs, a lot of usage data is available because of the number of learners involved. Newcomers, that just arrive on a MOOC, have various backgrounds in terms of knowledge, but the platform hardly knows anything about them. Therefore, it is crucial to elicit their knowledge fast, in order to...

In formative assessments, one wants to provide a useful feedback to the examinee at the end of the test. In order to reduce the number of questions asked in an assessment, adaptive testing models have been developed for cognitive diagnosis, such as the ones encountered in knowledge space theory. However, when the number of skills assessed is very h...

News media platforms publish articles about daily events letting their users comment on them, and forming interesting discussions in almost real-time. To keep users always active and interested, media platforms need an effective recommender system to bring up new articles that match user interests. In this article, we show that we can improve the q...

Computerized assessments are an increasingly popular way to evaluate students. They need to be optimized so that students can receive an accurate evaluation in as little time as possible. Such optimization is possible through learning analytics and computerized adaptive tests (CATs): the next question is then chosen according to the previous respon...

In online learning platforms such as MOOCs, computerized assessment needs to be optimized in order to prevent boredom and dropout of learners. Indeed, they should spend as little time as possible in tests and still receive valuable feedback. It is actually possible to reduce the number of questions for the same accuracy with computerized adaptive t...

Personalized applications like recommendation systems or open adaptive hypermedia require to facilitate reuse and interoperability of educational resources. Thus we have to solve the problem of discovering educational datasets and the problem of the fragmented landscape of competing metadata schemas. In this paper, we compare a subset of metadata s...

Nowadays, more and more people are using online news platforms as their main source of information about daily life events. Users of such platforms discuss around topics providing new insights and sometimes revealing hidden aspects about topics. The valuable information provided by users needs to be exploited to improve the accuracy of news recomme...

The number of opinions in news media platforms is increasing dramatically with daily news hits, and people spending more and more time to discuss topics and share experiences. Such user generated content represents a promising source for improving the effectiveness of news articles recommendation and retrieval. However, the corpus of opinions is of...

With the tremendous growth of published news articles, a key issue is how to help users find diverse and interesting news stories. To this end, it is crucial to understand and build accurate profiles for both users and news articles. In this paper, we define a user profile based on (1) the set of entities she/he talked about it in her/his comments...

In this paper, we illustrate PAGE – for Parametric AGEnts, a constructive way to design personalized or personified virtual agents starting from a plain rational agent. We chose a scenario about the personification of a virtual agent in a serious game for training communication skills. We start from an agent program that does not take into account...

Nowadays, more and more people are using online news plat-forms as their main source of information about daily life events. Users of such platforms have access to an increasing amount of articles of different topics, stories, and view points. Thus, a news personalization service is needed to filter the flow of available information and satisfy use...

Opinions, in news media platforms, provide a world wide access to what people think about daily life topics. Thus, exploiting such a source of information to identify the trends can be very useful in many scenarios, such as political parties who are interested in monitoring their impact. In this paper, we present an unsupervised technique to classi...

In this paper, we study how to extend the control over the behavioral space of logically specified agents so as they can take into account parameters issuing from constraints and/or preferences that are external to their core reasoning process. Our approach is supported by the proposition of a set of generic transformations to apply to the original...

Personalized systems are a response to the increasing number of resources on the Internet, but can be difficult to create. In order to facilitate the design and creation of such personalized systems, we aim at formalizing them. The situation calculus is a logical framework that has often been proposed to model web applications and even personalized...

Personalized systems are a response to the increasing number of resources on the Internet. In order to facilitate their design and creation, we aim at formalizing them. In this paper, we consider the relationship between a personalized application and its non-personalized counterpart. We argue that a personalized application is a formal extension o...

Nowadays, several efforts are focused on re-using generic platforms to create new systems, in order to make the design process easier and faster. Often, the designer has his own models and resources and would like to reuse the generic system over his resources. That means, he has to integrate his models and resources in the system, and then to dire...

The design of Adaptive Hypermedia is a difficult task which can be made easier if generic systems and AH creators' models are reused. We address this design problem in the setting of the GLAM platform only made up of generic components. In this paper, we assume the GLAM platform is used to create a specific adaptive hypermedia. We present a pattern...

The design of Adaptive Hypermedia is a difficult task which can be made easier if generic systems and AH creators’ models are reused. We address this design problem in the setting of the GLAM platform only made up of generic components. We present a rule-based approach helping an AH creator in reusing its user and domain models to create a specific...

This paper introduces GLAM, a system based on situation calculus and meta-rules, which is able to provide adaptation by means of selection of actions. It is primarily designed to provide adaptive navigation. The different levels of conception, related to different aspects of the available metadata, are split in different layers in GLAM, in order to...

GEAHS is a platform designed to ease the development of Adaptive Educational Hypermedia, using standard formalisms. In this document, we explain the underlying principles of this platform. Genericity is achieved thanks to an adaptation engine based on situation calculus and RDF. This paper describes the main aspects of our system, as well as the us...

even developed, based on AHAM specications. Our goal has been threefold. First, we wanted to create an engine - based on principles close to those of AHAM - using standard or recommended formalisms, in order to make it as reusable as possible. Second, we wanted to provide a model both simple and powerful. We wish that as many people as possible are...

We present an adaptive hypermedia architecture based on Golog and conceptual graphs. We propose a conceptual graph model for the description of the hypermedia structure and the use of Golog, a logic programming language, for the generation of the personalized hypermedia. This approach has been validated by a prototype and two examples based on diff...

The 7th edition of TEX Live under Windows has some new features that are ex- plained in this paper. Especially notable are two experiments to extend Kpathsea beyond its original abilities: • sharing Kpathsea data-structures between several processes for faster pro- cessing, • allow url's in client programs as well as filenames whenever they ask Kpa...

Eitan Gurari est l’auteur de TeX4ht, un outil original permettant la conversion de documents TeX et LaTeX vers HTML et XML. Mon but est de montrer que TeX4ht est simple d’utilisation, puissant et extensible en effectuant un petit tour de ses possibilites.

La distribution logicielle teTeX pour Unix connait un grand succes merite de par son integration de tous les outils necessaires a la chaine de production de documents scientifiques basee sur TeX. La distribution logicielle fpTeX se veut l'equivalent de teTeX mais pour Windows. Nous presentons ici cette nouvelle distribution logicielle de TeX pour W...