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Hawkes Processes with Stochastic Excitations.

, , and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 79-88. JMLR.org, (2016)

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An Automated Combination of Kernels for Predicting Protein Subcellular Localization., and . WABI, volume 5251 of Lecture Notes in Computer Science, page 186-197. Springer, (2008)Contextual Gaussian Process Bandit Optimization., and . NIPS, page 2447-2455. (2011)A scaled Bregman theorem with applications., , and . NIPS, page 19-27. (2016)Part & Clamp: Efficient Structured Output Learning., and . AISTATS, volume 22 of JMLR Proceedings, page 877-885. JMLR.org, (2012)Linking losses for density ratio and class-probability estimation., and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 304-313. JMLR.org, (2016)Revisiting revisits in trajectory recommendation., , , and . CitRec@RecSys, page 2:1-2:6. ACM, (2017)Stochastic gradient updates yield deep equilibrium kernels., and . Trans. Mach. Learn. Res., (2023)Cell density in prostate histopathology images as a measure of tumor distribution., , , , , , , and . Medical Imaging: Digital Pathology, volume 9041 of SPIE Proceedings, page 90410S. SPIE, (2014)Multiclass multiple kernel learning., and . ICML, volume 227 of ACM International Conference Proceeding Series, page 1191-1198. ACM, (2007)Inferring structural variant cancer cell fraction, , , , , , , , , and 68 other author(s). Nature Communications, 11 (1): 730-- (2020)