Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization
Bounds

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Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds

29 October 2018

Barbara Rakitsch

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Papers citing "Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds"

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Title
Deep Actor-Critics with Tight Risk Certificates Bahareh Tasdighi Manuel Haussmann Yi-Shan Wu A. Masegosa M. Kandemir UQCV 78 0 0 26 May 2025
Multi-View Majority Vote Learning Algorithms: Direct Minimization of PAC-Bayesian Bounds Mehdi Hennequin Abdelkrim Zitouni K. Benabdeslem H. Elghazel Yacine Gaci 92 0 0 09 Nov 2024
PAC-Bayesian Soft Actor-Critic Learning Bahareh Tasdighi Abdullah Akgul Manuel Haussmann Kenny Kazimirzak Brink M. Kandemir 91 4 0 30 Jan 2023
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review Florian Tambon Gabriel Laberge Le An Amin Nikanjam Paulina Stevia Nouwou Mindom Y. Pequignot Foutse Khomh G. Antoniol E. Merlo François Laviolette 104 69 0 26 Jul 2021
Personalized Federated Learning with Gaussian Processes Idan Achituve Aviv Shamsian Aviv Navon Gal Chechik Ethan Fetaya FedML 87 103 0 29 Jun 2021
Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote Yi-Shan Wu A. Masegosa S. Lorenzen Christian Igel Yevgeny Seldin 47 8 0 25 Jun 2021
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound Valentina Zantedeschi Paul Viallard Emilie Morvant Rémi Emonet Amaury Habrard Pascal Germain Benjamin Guedj FedML BDL 93 17 0 23 Jun 2021
Self-Bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound Paul Viallard Pascal Germain Amaury Habrard Emilie Morvant 46 6 0 28 Apr 2021
Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes Manuel Haussmann S. Gerwinn Andreas Look Barbara Rakitsch M. Kandemir 86 16 0 17 Jun 2020
Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties J. Lindinger David Reeb C. Lippert Barbara Rakitsch BDL UQCV 71 8 0 22 May 2020
Consistent Online Gaussian Process Regression Without the Sample Complexity Bottleneck Alec Koppel Hrusikesha Pradhan K. Rajawat 34 32 0 23 Apr 2020
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees Jonas Rothfuss Vincent Fortuin Martin Josifoski Andreas Krause UQCV 93 127 0 13 Feb 2020
Stochastic Neural Network with Kronecker Flow Chin-Wei Huang Ahmed Touati Pascal Vincent Gintare Karolina Dziugaite Alexandre Lacoste Aaron Courville BDL 67 8 0 10 Jun 2019
Posterior Variance Analysis of Gaussian Processes with Application to Average Learning Curves Armin Lederer Jonas Umlauft Sandra Hirche 62 25 0 04 Jun 2019