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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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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.
Fu, S., Sein, M., & Desmarais, M. C. (2014, July). Towards the efficient recovery of general multi-dimensional bayesian network classifier [Paper]. 10th International Conference on Machine Learning and Data Mining in Pattern Recognition (MLDM 2014), St-Petersburg, Russia. External link
Fu, S. (2010). Efficient Learning of Markov Blanket and Markov Blanket Classifier [Ph.D. thesis, École Polytechnique de Montréal]. Available
Fu, S., & Desmarais, M. C. (2010, June). Feature Selection by Efficient Learning of Markov Blanket [Paper]. World Congress on Engineering 2010 (WCE 2010). External link
Fu, S., & Desmarais, M. C. (2010, June). Markov Blanket Based Feature Selection: a Review of Past Decade [Paper]. World Congress on Engineering 2010 (WCE 2010), London, U.K. External link
Fu, S., Pi, B., Zhou, Y., Desmarais, M. C., Wang, W., Han, S., & Rao, X. (2009, April). Cross-channel query recommendation on commercial mobile search engine: Why, how and empirical evaluation [Paper]. 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2009), Bangkok, Thailand. External link
Fu, S., Pi, B., Desmarais, M. C., Zhou, Y., Wang, W., & Han, S. (2009, October). Query recommendation and its usefulness evaluation on mobile search engine [Paper]. IEEE International Conference on Systems, Man and Cybernetics (SMC 2009), San Antonio, Texas, USA. External link
Fu, S., Desmarais, M. C., Pi, B., Zhou, Y., Wang, W., Zou, G., Han, S., & Rao, X. (2009, April). Simple but effective porn query recognition by k-NN with semantic similarity measure [Paper]. Joint International Conference on Advances in Data and Web Management (APWeb/WAIM 2009), Suzhou, China. External link
Fu, S., & Desmarais, M. C. (2008, May). Fast Markov blanket discovery algorithm via local learning within single pass [Paper]. 21st Conference of the Canadian Society for Computational Studies of Intelligence, Windsor, Canada. External link
Fu, S., Desmarais, M. C., & Li, F. (2008, May). One-pass learning algorithm for fast recovery of bayesian network [Paper]. 21th International Florida Artificial Intelligence Research Society Conference (FLAIRS 2008), Coconut Grove, FL, United States. External link
Fu, S., & Desmarais, M. C. (2008, May). Tradeoff analysis of different Markov blanket local learning approaches [Paper]. 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2008), Osaka, Japan. External link
Fu, S., & Desmarais, M. C. (2006, July). Multidimensional Computerized Adaptive Testing Based on Bayesian Theory [Paper]. 2nd IASTED International Conference on Education and Technology (ICET 2006), Calgary, Alberta. External link
Fu, S. (2005). Computerized adaptive testing based on bayesian decision theory : uni- and multidimensional models [Master's thesis, École Polytechnique de Montréal]. Available
Minn, S., Fu, S., & Desmarais, M. C. (2014, October). Efficient learning of general Bayesian network Classifier by Local and Adaptive Search [Paper]. IEEE International Conference on Data Science and Advanced Analytics (DSAA 2014), Shanghai, Chine. External link
