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Spatial forecasting of residential urban fires: A Bayesian approach.

, , and . Comput. Environ. Urban Syst., 34 (1): 58-69 (2010)

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A Scalable Probabilistic Model for Reward Optimizing Slate Recommendation., , , , , and . CoRR, (2022)Development and Application of Statistical and Machine Learning Techniques in Probabilistic Astronomical Catalogue-Matching Problems. University of Queensland, Australia, (2007)BLOB: A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals., , , and . KDD, page 783-793. ACM, (2020)Visual Data Mining Methods for Kernel Smoothed Estimates of Cox Processes., , , and . PAKDD Workshops, volume 7867 of Lecture Notes in Computer Science, page 83-94. Springer, (2013)Reward Optimizing Recommendation using Deep Learning and Fast Maximum Inner Product Search., , , , , , , , , and . KDD, page 4772-4773. ACM, (2022)Exponential Smoothing for Off-Policy Learning., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 984-1017. PMLR, (2023)A Gentle Introduction to Recommendation as Counterfactual Policy Learning., , , and . UMAP, page 392-393. ACM, (2020)MCMC methods for univariate exponential family models with intractable normalization constants., and . SSP, page 356-359. IEEE, (2014)Machine Learning for Matching Astronomy Catalogues., , , , and . IDEAL, volume 3177 of Lecture Notes in Computer Science, page 702-707. Springer, (2004)Three Methods for Training on Bandit Feedback., , and . CoRR, (2019)