Emergence of invariance and disentanglement in deep representations, Journal of Machine Learning Research, vol.19, issue.50, pp.1-34, 2018. ,
Sparse single-index model, Journal of Machine Learning Research, vol.14, pp.243-280, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-00556652
Simpler PAC-Bayesian bounds for hostile data, Machine Learning, vol.107, pp.887-902, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01385064
PAC-Bayesian theorems for sparse regression estimation with exponential weights, Electronic Journal of Statistics, vol.5, pp.127-145, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-00607297
On the properties of variational approximations of Gibbs posteriors, The Journal of Machine Learning Research, vol.17, issue.1, pp.8374-8414, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-02403354
Tighter PAC-Bayes bounds, Advances in Neural Information Processing Systems, NIPS, pp.9-16, 2007. ,
Combining PAC-Bayesian and generic chaining bounds, Journal of Machine Learning Research, 2007. ,
PAC-Bayesian theory for transductive learning, AISTATS, 2014. ,
PAC-Bayesian bounds based on the Rényi divergence, AISTATS, 2016. ,
Reconciling modern machine learning and the bias-variance trade-off, 2018. ,
Stability and generalization, Journal of machine learning research, vol.2, pp.499-526, 2002. ,
A PAC-Bayesian approach to adaptive classification, 2003. ,
Statistical Learning Theory and Stochastic Optimization, 2001. ,
URL : https://hal.archives-ouvertes.fr/hal-00104952
PAC-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning, Lecture notes -Monograph Series. Institute of Mathematical Statistics, vol.56, 2007. ,
URL : https://hal.archives-ouvertes.fr/hal-00206119
I-divergence geometry of probability distributions and minimization problems, Annals of Probability, vol.3, pp.146-158, 1975. ,
Explicit learning curves for transduction and application to clustering and compression algorithms, J. Artif. Intell. Res. (JAIR), vol.22, 2004. ,
Asymptotic evaluation of certain Markov process expectations for large time, Communications on Pure and Applied Mathematics, vol.28, 1975. ,
Computing nonvacuous generalization bounds for deep (stochastic) neural networks with many more parameters than training data, Proceedings of Uncertainty in Artificial Intelligence (UAI), 2017. ,
Data-dependent PAC-Bayes priors via differential privacy, NeurIPS, 2018. ,
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors, International Conference on Machine Learning, pp.1376-1385, 2018. ,
PAC-Bayesian model selection for reinforcement learning, Advances in Neural Information Processing Systems (NIPS), 2010. ,
PAC-Bayesian Policy Evaluation for Reinforcement Learning, UAI, Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial Intelligence, pp.195-202, 2011. ,
Prédiction de suites individuelles et cadre statistique classique :étude de quelques liens autour de la régression parcimonieuse et des techniques d'agrégation, 2011. ,
Généralisations de la théorie PAC-bayésienne pour l'apprentissage inductif, l'apprentissage transductif et l'adaptation de domaine, 2015. ,
PAC-Bayesian learning of linear classifiers, Proceedings of the 26th Annual International Conference on Machine Learning, ICML, 2009. ,
From PAC-Bayes bounds to KL regularization, Advances in Neural Information Processing Systems, pp.603-610, 2009. ,
A new PAC-Bayesian perspective on domain adaptation, Proceedings of International Conference on Machine Learning, vol.48, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-01163722
Bayesian reinforcement learning: A survey. Foundations and Trends in Machine Learning, vol.8, pp.359-483, 2015. ,
PAC-Bayesian estimation and prediction in sparse additive models, Electron. J. Statist, vol.7, pp.264-291, 2013. ,
URL : https://hal.archives-ouvertes.fr/hal-00722969
PAC-Bayesian high dimensional bipartite ranking, Journal of Statistical Planning and Inference, vol.196, pp.70-86, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01226472
A PAC-Bayes bound for tailored density estimation, Proceedings of the International Conference on Algorithmic Learning Theory (ALT), 2010. ,
PAC-Bayes bounds for the risk of the majority vote and the variance of the Gibbs classifier, Advances in Neural information processing systems, pp.769-776, 2007. ,
Tutorial on practical prediction theory for classification, Journal of Machine Learning Research, 2005. ,
Bounds for averaging classifiers, 2001. ,
PAC-Bayes & margins, Advances in Neural Information Processing Systems (NIPS), 2002. ,
Distribution-dependent PAC-Bayes priors, International Conference on Algorithmic Learning Theory, pp.119-133, 2010. ,
Tighter PAC-Bayes bounds through distribution-dependent priors, Theoretical Computer Science, vol.473, pp.4-28, 2013. ,
General oracle inequalities for Gibbs posterior with application to ranking, Conference on Learning Theory, pp.512-521, 2013. ,
A quasi-Bayesian perspective to online clustering, Electron. J. Statist, vol.12, issue.2, pp.3071-3113, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01264233
A PAC-Bayesian analysis of randomized learning with application to stochastic gradient descent, Advances in Neural Information Processing Systems, pp.2931-2940, 2017. ,
PAC-Bayesian collective stability, Artificial Intelligence and Statistics, pp.585-594, 2014. ,
A note on the PAC-Bayesian Theorem, 2004. ,
Some PAC-Bayesian theorems, Proceedings of the International Conference on Computational Learning Theory (COLT), 1998. ,
References IV D. McAllester. PAC-Bayesian stochastic model selection, Machine Learning, vol.37, 1999. ,
Simplified PAC-Bayesian margin bounds, COLT, 2003. ,
Exploring generalization in deep learning, Advances in Neural Information Processing Systems, pp.5947-5956, 2017. ,
PAC-Bayes bounds with data dependent priors, Journal of Machine Learning Research, vol.13, pp.3507-3531, 2012. ,
PAC-Bayes bounds for stable algorithms with instance-dependent priors, Advances in Neural Information Processing Systems, pp.9214-9224, 2018. ,
PAC-Bayesian generalization bounds for gaussian processes, Journal of Machine Learning Research, vol.3, pp.233-269, 2002. ,
Bayesian Gaussian Process Models: PAC-Bayesian Generalisation Error Bounds and Sparse Approximations, 2003. ,
PAC-Bayesian analysis of co-clustering and beyond, Journal of Machine Learning Research, vol.11, pp.3595-3646, 2010. ,
PAC-Bayesian analysis of contextual bandits, Advances in Neural Information Processing Systems (NIPS), 2011. ,
PAC-Bayesian inequalities for martingales, IEEE Transactions on Information Theory, vol.58, issue.12, pp.7086-7093, 2012. ,
Pac-bayes analysis of maximum entropy classification, Proceedings on the International Conference on Artificial Intelligence and Statistics (AISTATS), 2009. ,
A PAC analysis of a Bayes estimator, Proceedings of the 10th annual conference on Computational Learning Theory, pp.2-9, 1997. ,
Structural risk minimization over data-dependent hierarchies, IEEE Transactions on Information Theory, vol.44, issue.5, 1998. ,
A Strongly Quasiconvex PAC-Bayesian Bound, International Conference on Algorithmic Learning Theory, ALT, pp.466-492, 2017. ,
The information bottleneck method, Allerton Conference on Communication, Control and Computation, 1999. ,
A theory of the learnable, Communications of the ACM, vol.27, issue.11, pp.1134-1142, 1984. ,