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Landmark-Based Ensemble Learning with Random Fourier Features and Gradient Boosting.

, , , , , , and . ECML/PKDD (3), volume 12459 of Lecture Notes in Computer Science, page 141-157. Springer, (2020)

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Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound., , , , , , and . NeurIPS, page 455-467. (2021)VideoSense at TRECVID 2011: Semantic Indexing from Light Similarity Functions-based Domain Adaptation with Stacking., , , , , , , , , and . TRECVID, National Institute of Standards and Technology (NIST), (2011)Landmark-Based Ensemble Learning with Random Fourier Features and Gradient Boosting., , , , , , and . ECML/PKDD (3), volume 12459 of Lecture Notes in Computer Science, page 141-157. Springer, (2020)A PAC-Bayes Analysis of Adversarial Robustness., , , and . NeurIPS, page 14421-14433. (2021)Metric Learning from Imbalanced Data., , , and . ICTAI, page 923-930. IEEE, (2019)Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior., , and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 768-776. PMLR, (2019)Self-bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound., , , and . ECML/PKDD (2), volume 12976 of Lecture Notes in Computer Science, page 167-183. Springer, (2021)A general framework for the practical disintegration of PAC-Bayesian bounds., , , and . Mach. Learn., 113 (2): 519-604 (February 2024)Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures., , , , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 3007-3015. PMLR, (2024)