French version

Jill-Jênn Vie

Hey! We organize a data challenge about recommender systems with Kyoto University.
Submissions open until October 1.


New! Our article BALSE is on arXiv! (Vie et al. 2017)
It has been accepted to the MANPU 2017 conference in Kyoto.

I'm a postdoctoral researcher in RIKEN AIP @ Tokyo and in Kashima's Machine Learning Lab @ Kyoto University.
My research interests are: matrix factorization, crowdsourcing, and item response theory.

Mail: vie@jill-jenn.net / My résumé

Research Interests

I write free software for the French government: PIX is a certification of digital skills. Presented at Learning at Scale 2017 in Boston: [poster] [article]
I write free software for the French government:
PIX is a certification of digital skills.
Presented at Learning at Scale 2017 in Boston: [poster] [article]
Our publication Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario [arXiv] has been accepted to MANPU 2017 in Kyoto.
Our publication Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario [arXiv] has been accepted to MANPU 2017 in Kyoto.
Slides and benchmark code of my IACAT 2017 presentation in Niigata: Multistage Testing using Determinantal Point Processes
Slides and benchmark code of my IACAT 2017 presentation in Niigata: Multistage Testing using Determinantal Point Processes

Music

Trio ELM

I'm the pianist of Trio ELM: together with two talented singers, we perform anime and video game music in concerts.

Achievements

✅ Cowriter of 2 books including the Python package tryalgo → 128 algorithms for coding contests (also a French book)
✅ Cofounder of a programming summer school for K-12 girlsGirls Can Code!
✅ Core contributor of an open-source anime recommender systemMangaki
✅ Director of a TV show about algorithms that take control of our lives → Blame the Algorithm
✅ Contributor to a government report → open sourcing the French college admission algorithm "APB" (similar to NRMP).

Publications

See my Scholar page

Books

I co-wrote two books about algorithms and data structures: preparing programming contests and coding interviews (Dürr and Vie 2016) and (Belghiti, Mansuy, and Vie 2016).
The book is in French but the code is in Python: all 128 algorithms are on GitHub, in the Python package tryalgo.

Book Chapters

I wrote a chapter about adaptive assessment (Vie, Popineau, Bourda, and Bruillard 2016b) in a learning analytics book. I tend to identify the similarities between cognitive diagnostic models and item response theory.

Conference Proceedings

I used to do cryptography in my master's degree and published an article about leakage resilience (Abdalla and Vie 2012).
Used a General Diagnostic Model for adaptive testing and showed that it outperformed the DINA and Rasch models at predicting examinee performance (Vie, Popineau, Bourda, and Bruillard 2016a).


Abdalla, Michel, and Jill-Jênn Vie. 2012. “Leakage-Resilient Spatial Encryption.” In International Conference on Cryptology and Information Security in Latin America, 78–99. Springer.

Belghiti, Ismael, Roger Mansuy, and Jill-Jênn Vie. 2016. Les Clés Pour L’info : ENS et Agrégation (Option d). Calvage et Mounet.

Dürr, Christoph, and Jill-Jênn Vie. 2016. Programmation efficace. Ellipses.

Vie, Jill-Jênn, Fabrice Popineau, Yolaine Bourda, and Éric Bruillard. 2016a. “A Review of Recent Advances in Adaptive Assessment.” In Learning Analytics: Fundaments, Applications, and Trends: A View of the Current State of the Art, in press. Springer.

Vie, Jill-Jênn, Fabrice Popineau, Yolaine Bourda, and Éric Bruillard. 2016b. “Adaptive Testing Using a General Diagnostic Model.” In European Conference on Technology Enhanced Learning, 331–39. Springer.

Vie, Jill-Jênn, Fabrice Popineau, Éric Bruillard, and Yolaine Bourda. 2016. “Utilisation de tests adaptatifs dans les MOOC dans un cadre de crowdsourcing.” STICEF, in review.

Vie, Jill-Jênn, Fabrice Popineau, Jean-Bastien Grill, Éric Bruillard, and Yolaine Bourda. 2015a. “Predicting Performance over Dichotomous Questions: Comparing Models for Large-Scale Adaptive Testing.” In 8th International Conference on Educational Data Mining (Edm 2015).

Vie, Jill-Jênn, Fabrice Popineau, Jean-Bastien Grill, Éric Bruillard, and Yolaine Bourda. 2015b. “Prédiction de performance sur des questions dichotomiques : comparaison de modèles pour des tests adaptatifs à grande échelle.” In Atelier Évaluation des Apprentissages et Environnements Informatiques, EIAH 2015.

Vie, Jill-Jênn, Fabrice Popineau, Françoise Tort, Benjamin Marteau, and Nathalie Denos. 2017. “A Heuristic Method for Large-Scale Cognitive-Diagnostic Computerized Adaptive Testing.” In Proceedings of the Fourth (2017) Acm Conference on Learning@ Scale, 323–26. ACM.

Vie, Jill-Jênn, Florian Yger, Ryan Lahfa, Basile Clement, Kévin Cocchi, Thomas Chalumeau, and Hisashi Kashima. 2017. “Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario.” ArXiv E-Prints, September. https://arxiv.org/abs/1709.01584.