Zobrazeno 1 - 10
of 1 180
pro vyhledávání: '"P. Vie"'
Autor:
Vassoyan, Jean, Schütt, Anan, Vie, Jill-Jênn, Lekshmi-Narayanan, Arun-Balajiee, André, Elisabeth, Vayatis, Nicolas
Massive Open Online Courses (MOOCs) have greatly contributed to making education more accessible. However, many MOOCs maintain a rigid, one-size-fits-all structure that fails to address the diverse needs and backgrounds of individual learners. Learni
Externí odkaz:
http://arxiv.org/abs/2411.11520
Autor:
Yan, Su, Vié, Clotilde, Lerendegui, Marcelo, Verinaz-Jadan, Herman, Yan, Jipeng, Tashkova, Martina, Burn, James, Wang, Bingxue, Frost, Gary, Murphy, Kevin G., Tang, Meng-Xing
Super-resolution ultrasound imaging through microbubble (MB) localisation and tracking, also known as ultrasound localisation microscopy, allows non-invasive sub-diffraction resolution imaging of microvasculature in animals and humans. The number of
Externí odkaz:
http://arxiv.org/abs/2407.06373
Accurate estimation of question difficulty and prediction of student performance play key roles in optimizing educational instruction and enhancing learning outcomes within digital learning platforms. The Elo rating system is widely recognized for it
Externí odkaz:
http://arxiv.org/abs/2403.07908
Autor:
Garg, Alka B., Vie, David, Rodriguez-Hernandez, Placida, Munoz, Alfonso, Segura, Alfredo, Errandonea, Daniel
Publikováno v:
J. Phys. Chem. Lett. 2023, 14, 1762-1768
In this work, we report diffuse reflectivity measurements in InNbO4, ScNbO4, YNbO4, and eight different rare-earth niobates. From a comparison with the established values of the band gap of InNbO4 and ScNbO4, we have found that the broadly used Tauc
Externí odkaz:
http://arxiv.org/abs/2401.13477
Autor:
Vie, Jill-Jênn, Kashima, Hisashi
Publikováno v:
ICCE 2023 - The 31st International Conference on Computers in Education, Asia-Pacific Society for Computers in Education, Dec 2023, Matsue, Shimane, Japan
Knowledge tracing consists in predicting the performance of some students on new questions given their performance on previous questions, and can be a prior step to optimizing assessment and learning. Deep knowledge tracing (DKT) is a competitive mod
Externí odkaz:
http://arxiv.org/abs/2309.12334
Adaptive learning is an area of educational technology that consists in delivering personalized learning experiences to address the unique needs of each learner. An important subfield of adaptive learning is learning path personalization: it aims at
Externí odkaz:
http://arxiv.org/abs/2305.06398
Autor:
Vie, Aymeric, Farmer, J. Doyne
Agent-based models (ABMs) are fit to model heterogeneous, interacting systems like financial markets. We present the latest advances in Evology: a heterogeneous, empirically calibrated market ecology agent-based model of the US stock market. Prices e
Externí odkaz:
http://arxiv.org/abs/2302.01216
Publikováno v:
Psychometrika volume 87, pages 266-288 (2022)
This paper presents a machine learning approach to multidimensional item response theory (MIRT), a class of latent factor models that can be used to model and predict student performance from observed assessment data. Inspired by collaborative filter
Externí odkaz:
http://arxiv.org/abs/2301.00909
Factorization machines (FMs) are a powerful tool for regression and classification in the context of sparse observations, that has been successfully applied to collaborative filtering, especially when side information over users or items is available
Externí odkaz:
http://arxiv.org/abs/2212.09920
Publikováno v:
2022 ACM International Conference on Artificial Intelligence in Finance - Benchmarks in AI workshop
The profitability of various investment styles in investment funds depends on macroeconomic conditions. Market ecology, which views financial markets as ecosystems of diverse, interacting and evolving trading strategies, has shown that endogenous int
Externí odkaz:
http://arxiv.org/abs/2210.11344