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This 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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A 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.
Babaki, B., Omrani, B., & Pesant, G. (2020, September). Combinatorial Search in CP-Based Iterated Belief Propagation [Paper]. 26th International Conference on Principles and Practice of Constraint Programming, Louvain-la-Neuve, Belgium. External link
Babaki, B., & Pesant, G. (2020, November). Parallel Planning using a Lazy Clause Generation Solver [Paper]. 32nd IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2020). External link
Babaki, B., Pesant, G., & Quimper, C.-G. (2020, May). Solving Classical AI Planning Problems Using Planning-Independent CP Modeling and Search [Paper]. 13th International Symposium on Combinatorial Search (SOCS 2020), Vienna, Austria. Published in Proceedings of the International Symposium on Combinatorial Search, 11(1). External link
Choi, Y. J., Farnadi, G., Babaki, B., & Van Den Broeck, G. (2020, February). Learning fair naive bayes classifiers by discovering and eliminating discrimination patterns [Paper]. 34th AAAI Conference on Artificial Intelligence (AAAI 2020), New York, NY, USA. External link
Farnadi, G., St-Arnaud, W., Babaki, B., & Carvalho, M. (2021, February). Individual Fairness in Kidney Exchange Programs [Paper]. 35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence. External link
Farnadi, G., Babaki, B., & Gendreau, M. (2020, April). A unifying framework for fairness-aware influence maximization [Paper]. WWW '20: The Web Conference 2020, Taipei, Taiwan. Available
Farnadi, G., Babaki, B., & Getoor, L. (2018, February). Fairness in Relational Domains [Paper]. 1st AAAI/ACM Conference on AI, Ethics, and Society (AIES 2018), New Orleans, LA. External link
Khorasany, M., Mishra, Y., Babaki, B., & Ledwich, G. (2019). Enhancing scalability of peer-to-peer energy markets using adaptive segmentation method. Journal of Modern Power Systems and Clean Energy, 7(4), 791-801. Available
Latour, A. L. D., Babaki, B., Fokkinga, D., Anastacio, M. H., Hoos, H. H., & Nijssen, S. (2022). Exact stochastic constraint optimisation with applications in network analysis. Artificial Intelligence, 304, 103650 (38 pages). External link
Latour, A. L. D., Babaki, B., & Nijssen, S. (2019, August). Stochastic constraint propagation for mining probabilistic networks [Paper]. 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), Macao, China. External link
Srinivasan, S., Babaki, B., Farnadi, G., & Getoor, L. (2019, January). Lifted hinge-loss Markov random fields [Paper]. 33rd AAAI Conference on Artificial Intelligence (AAAI 2019), 31st Annual Conference on Innovative Applications of Artificial Intelligence (IAAI 2019) and the 9th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI 2019), Honolulu, HI. Published in Proceedings of the ... AAAI Conference on Artificial Intelligence, 33(1). External link
Tran, D. H., Babaki, B., Van Daele, D., Leyman, P., & De Causmaecker, P. (2021). Local search for constrained graph clustering in biological networks. Computers & Operations Research, 132, 12 pages. External link