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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.
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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
Bessiere, C., Hebrard, E., Hnich, B., Kiziltan, Z., Quimper, C.-G., & Walsh, T. (2008, July). The parameterized complexity of global constraints [Paper]. 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI 08/IAAI 08. External link
Côté, M.-C., Gendron, B., Quimper, C.-G., & Rousseau, L.-M. (2011). Formal languages for integer programming modeling of shift scheduling problems. Constraints, 16(1), 54-76. External link
Côté, M.-C., Gendron, B., Quimper, C.-G., & Rousseau, L.-M. (2007). Formal languages for integer programming modeling of shift scheduling problems. (Working Paper n° CIRRELT-2007-64). External link
Hà, M. H., Quimper, C.-G., & Rousseau, L.-M. (2015, August). General Bounding Mechanism for Constraint Programs [Paper]. 21st International Conference on Principles and Practice of Constraint Programming (CP 2015), Cork, Ireland. External link
Maher, M., Narodytska, N., Quimper, C.-G., & Walsh, T. (2008, September). Flow-based propagators for the SEQUENCE and related global constraints [Paper]. 14th International Conference on Principles and Practice of Constraint Programming, CP 2008, Sydney, NSW, Australia. External link
Pesant, G., Quimper, C.-G., & Verhaeghe, H. (2022, June). Practically uniform solution sampling in constraint programming [Paper]. 19th International Conference on Integration of Constraint Programming, Artificial Intelligence and Operations Research (CPAIOR 2022), Los Angeles, CA, USA. External link
Pesant, G., Quimper, C.-G., & Zanarini, A. (2012). Counting-Based Search: Branching Heuristics for Constraint Satisfaction Problems. Journal of Artificial Intelligence Research, 43, 173-210. External link
Pesant, G., Quimper, C.-G., Rousseau, L.-M., & Sellmann, M. (2009, May). The polytope of context-free grammar constraints [Paper]. 6th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, Pittsburgh, PA, USA. External link
Pesant, G., & Quimper, C.-G. (2008, May). Counting solutions of knapsack constraints [Paper]. 5th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (CPAIOR 2008), Paris, France. External link
Quimper, C.-G., & Rousseau, L.-M. (2010). A large neighbourhood search approach to the multi-activity shift scheduling problem. Journal of Heuristics, 16(3), 373-392. External link
Quimper, C.-G., & Walsh, T. (2008, July). Decompositions of grammar constraints [Paper]. 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI-08/IAAI-08, Chicago, IL, United states. Unavailable
Quimper, C.-G., & Rousseau, L.-M. (2007). A large neighbourhood search approach to the multi-activity shift scheduling problem. (Technical Report n° CIRRELT-2007-56). External link
Verhaeghe, H., Cappart, Q., Pesant, G., & Quimper, C.-G. (2024, September). Learning Precedences for Scheduling Problems with Graph Neural Networks [Paper]. 30th International Conference on Principles and Practice of Constraint Programming (CP 2024), Girona, Spain (18 pages). External link
Verhaeghe, H. , Nijssen, S., Pesant, G., Quimper, C.-G., & Schaus, P. (2021, June). Learning Optimal Decision Trees using Constraint Programming [Paper]. 16th French-Speaking Conference on Constraint Programming (JFPC 2021). Unavailable
Verhaeghe, H., Nijssen, S., Pesant, G., Quimper, C.-G., & Schaus, P. (2020). Learning optimal decision trees using constraint programming. Constraints, 25(3-4), 226-250. External link
Verhaeghe, H., Nijssen, S., Pesant, G., Quimper, C.-G., & Schaus, P. (2021, January). Learning optimal decision trees using constraint programming (extended abstract) [Paper]. 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), Yokohama, Japan. External link
