International Conferences

• PAC-Bayesian Contrastive Unsupervised Representation Learning
  Kento Nozawa ; Pascal Germain ; Benjamin Guedj
  Conference on Uncertainty in Artificial Intelligence (UAI), 2020
• Improved PAC-Bayesian Bounds for Linear Regression
  Vera Shalaeva ; Alireza Fakhrizadeh Esfahani ; Pascal Germain ; Mihaly Petreczky
  Conference on Artificial Intelligence (AAAI), 2020
• Landmark-based Ensemble Learning with Random Fourier Features and Gradient Boosting
  Léo Gautheron ; Pascal Germain ; Amaury Habrard ; Guillaume Metzler ; Emilie Morvant ; Marc Sebban ; Valentina Zantedeschi
  European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2020
• Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior
  Gaël Letarte ; Emilie Morvant ; Pascal Germain
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2019, Naha, Okinawa, Japan
  [pdf][bibtex][code]
• Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks
  Gaël Letarte ; Pascal Germain ; Benjamin Guedj ; François Laviolette
  Conference on Neural Information Processing Systems (NeurIPS), 2019
  [pdf][bibtex (to appear)]

Journal

• A primer on PAC-Bayesian Learning
  Benjamin Guedj
  Journal of Société Mathématiques de France (SMF), 2019
  [pdf][bibtex (to appear)]

French Conferences

• Théorie PAC-Bayésienne pour l’apprentissage en deux étapes de réseaux de neurones
  Paul Viallard ; Rémi Emonet ; Amaury Habrard ; Emilie Morvant; Pascal Germain
  French Conference on Machine Learning (CAp 2020), 2020
• Apprentissage d’ensemble basé sur des points de repère avec des caractéristiques de Fourier aléatoires et un renforcement du gradient
  Léo Gautheron ; Pascal Germain ; Amaury Habrard ; Guillaume Metzler ; Emilie Morvant ; Marc Sebban ; Valentina Zantedeschi
  French Conference on Machine Learning (CAp 2020), 2020
• Revisite des “random Fourier features” basée sur l’apprentissage PAC-Bayésien via des points d’intérêts
  Léo Gautheron ; Pascal Germain ; Amaury Habrard ; Gaël Letarte ; Emilie Morvant ; Marc Sebban ; Valentina Zantedeschi
  French Conference on Machine Learning (CAp 2019), 2019

Workshops

• Interpreting Neural Networks as Majority Votes through the PAC-Bayesian Theory
  Paul Viallard ; Rémi Emonet ; Pascal Germain ; Amaury Habrard ; Emilie Morvant
  NeurIPS 2019 Workshop on Machine Learning with guarantees
• Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks
  Gaël Letarte ; Pascal Germain ; Benjamin Guedj ; François Laviolette
  NeurIPS 2019 Workshop on Machine Learning with guarantees