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Collaboration networkThis graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
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Hold down the "Ctrl" key or the "⌘" key while clicking on the nodes to open the list of this person's publications.
Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Desmarais, M. C., & Xu, P. (2016). Methods to refine the mapping of items to skills. In Sottilare, R., Graesser, A., Hu, X., Olney, A., Nye, B., & Sinatra, A. (eds.), Design recommendations for intelligent tutoring systems (Vol. 4, pp. 39-48). External link
Desmarais, M. C., Beheshti, B., & Xu, P. (2014, July). The refinement of a Q-matrix: Assessing methods to validate tasks to skills mapping [Paper]. 7th Conference on Educational Data Data Mining (EDM 2014), London, England. External link
Lu, Y., & Xu, P. (2018, September). Anomaly detection for skin disease images using variational autoencoder [arXiv] [Paper]. ISIC Skin Image Analysis Workshop and Challenge at MICCAI 2018, Granada, Spain. External link
Xu, P. (2019). Q-matrix Refinement, Design and Derivation [Ph.D. thesis, Polytechnique Montréal]. Available
Xu, P., & Desmarais, M. C. (2018, July). An empirical research on identifiability and Q-matrix design for DINA model [Paper]. 11th International Conference on Educational Data Mining (EDM 2018), Buffalo, NY, United states. External link
Xu, P., & Desmarais, M. C. (2016, June). Boosted decision tree for Q-matrix refinement [Paper]. 9th International Conference on Educational Data Mining (EDM 2016), Raleigh, NC, United states. External link
Zhao, D., Yu, G., Xu, P., & Luo, M. (2019). Equivalence between dropout and data augmentation: A mathematical check. Neural Networks, 115, 82-89. External link
