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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.
Bachman, P., Farahmand, A.-M., & Precup, D. (2014, June). Sample-based approximate regularization [Paper]. 31st International Conference on Machine Learning (ICML 2014), Beijing, China (9 pages). External link
Farahmand, A.-M., Precup, D., Barreto, A. M., & Ghavamzadeh, M. (2015). Classification-Based Approximate Policy Iteration. IEEE Transactions on Automatic Control, 60(11), 2989-2993. External link
Fard, M. M., Grinberg, Y., Farahmand, A.-M., Pineau, J., & Precup, D. (2013, December). Bellman error based feature generation using random projections on sparse spaces [Paper]. 27th Conference on Neural Information Processing Systems (NeurIPS 2013), Las Vegas, NV, USA (9 pages). External link
Farahmand, A.-M., Precup, D., Barreto, A. M. S., & Ghavamzadeh, M. (2013, October). CAPI : generalized classification-based approximate policy iteration [Paper]. Multi-Disciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2013), Princeton, NJ, USA. Unavailable
Farahmand, A.-M., & Precup, D. (2012, December). Value pursuit iteration [Paper]. 26th annual Conference on Neural Information Processing Systems (NeurIPS 2012), Lake Tahoe, Nevada, USA (9 pages). External link
Grinberg, Y., Precup, D., & Gendreau, M. (2014, December). Optimizing energy production using policy search and predictive state representations [Paper]. 28th Annual Conference on Neural Information Processing Systems 2014 (NIPS 2014), Montréal, Québec. Unavailable
Jafarpour, N., Izadi, M., Precup, D., & Buckeridge, D. L. (2015). Quantifying the determinants of outbreak detection performance through simulation and machine learning. Journal of Biomedical Informatics, 53, 180-187. External link
Kim, B., Farahmand, A.-M., Pineau, J., & Precup, D. (2013, October). Approximate policy iteration with demonstrated data [Paper]. Multi-Disciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2013), Princeton, NJ, USA. Unavailable
Kim, B., Farahmand, A.-M., Pineau, J., & Precup, D. (2013, December). Learning from limited demonstration [Paper]. 27th Conference on Neural Information Processing Systems (NeurIPS 2013), Las Vegas, NV, USA (9 pages). External link
Weiss, M., Chamorro, S., Girgis, R., Luck, M., Kahou, S. E., Cohen, J. P., Nowrouzezahrai, D., Precup, D., Golemo, F., & Pal, C. J. (2019, October). Navigation agents for the visually impaired:a sidewalk simulator and experiments [Paper]. Conference on Robot Learning (CoRL 2019), Osaka, Japan (14 pages). Published in Proceedings of Machine Learning Research, 100. External link
Weiss, M., Chamorro, S., Girgis, R., Luck, M., Kahou, S., Cohen, J., Nowrouzezahrai, D., Precup, D., Golemo, F., & Pal, C. J. (2019). Sidewalk environment for visual navigation [Dataset]. External link
