{"id":89,"date":"2019-01-09T16:11:18","date_gmt":"2019-01-09T15:11:18","guid":{"rendered":"https:\/\/project.inria.fr\/apriori\/?page_id=89"},"modified":"2021-03-03T16:16:37","modified_gmt":"2021-03-03T15:16:37","slug":"publications","status":"publish","type":"page","link":"https:\/\/project.inria.fr\/apriori\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"<h1>International Conferences<\/h1>\n<ul>\n<li><span style=\"font-weight: 400;\"><strong>PAC-Bayesian Contrastive Unsupervised Representation Learning<br \/>\n<\/strong><\/span>Kento Nozawa ; Pascal Germain ; Benjamin Guedj<br \/>\n<em>Conference on Uncertainty in Artificial Intelligence (UAI), <strong>2020<\/strong><\/em><\/li>\n<li><span style=\"font-weight: 400;\"><strong>Improved PAC-Bayesian Bounds for Linear Regression<br \/>\n<\/strong>Vera Shalaeva ; Alireza Fakhrizadeh Esfahani ; Pascal Germain ; Mihaly Petreczky<br \/>\n<em>Conference on Artificial Intelligence (AAAI), <strong>2020<\/strong><\/em><\/span><\/li>\n<li><strong>Landmark-based Ensemble Learning with Random Fourier Features and Gradient Boosting<\/strong><br \/>\nL\u00e9o Gautheron ; Pascal Germain ; Amaury Habrard ; Guillaume Metzler ; Emilie Morvant ; Marc Sebban ; Valentina Zantedeschi<br \/>\n<em>European Conference on Machine Learning &amp; Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), <strong>2020<\/strong><\/em><\/li>\n<li><strong>Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior<\/strong><br \/>\nGa\u00ebl Letarte ; Emilie Morvant ; Pascal Germain<br \/>\n<em>International Conference on Artificial Intelligence and Statistics (AISTATS),\u00a0<b>2019<\/b>, Naha, Okinawa, Japan<\/em><br \/>\n[<a href=\"https:\/\/hal.archives-ouvertes.fr\/hal-01908555v2\/document\">pdf<\/a>][<a href=\"https:\/\/hal.archives-ouvertes.fr\/hal-01908555v2\/bibtex\">bibtex<\/a>][<a href=\"https:\/\/github.com\/gletarte\/pbrff\">code<\/a>]<\/li>\n<li><strong>Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks<\/strong><br \/>\nGa\u00ebl Letarte ; Pascal Germain ; Benjamin Guedj ; Fran\u00e7ois Laviolette<br \/>\n<em>Conference on Neural Information Processing Systems (NeurIPS),\u00a0<strong>2019<\/strong><\/em><br \/>\n[<a href=\"https:\/\/arxiv.org\/abs\/1905.10259\">pdf<\/a>][bibtex <em>(to appear)<\/em>]<\/li>\n<\/ul>\n<h1>Journal<\/h1>\n<ul>\n<li><strong>A primer on PAC-Bayesian Learning<br \/>\n<\/strong>Benjamin Guedj<br \/>\n<em>Journal of Soci\u00e9t\u00e9 Math\u00e9matiques de France (<a href=\"https:\/\/smf.emath.fr\/en\/publications\/nos-revues\">SMF<\/a>),\u00a0<strong>2019<\/strong><\/em><br \/>\n[<a href=\"https:\/\/arxiv.org\/abs\/1901.05353\">pdf<\/a>][bibtex<em> (to appear)<\/em>]<\/li>\n<\/ul>\n<h1>French Conferences<\/h1>\n<ul>\n<li><strong>Th\u00e9orie PAC-Bay\u00e9sienne pour l&#8217;apprentissage en deux \u00e9tapes de r\u00e9seaux de neurones<\/strong><br \/>\nPaul Viallard ; R\u00e9mi Emonet ; Amaury Habrard ; Emilie Morvant; Pascal Germain<br \/>\n<em>French Conference on Machine Learning (CAp 2020),\u00a0<b>2020<\/b><\/em><\/li>\n<li><strong>Apprentissage d&#8217;ensemble bas\u00e9 sur des points de rep\u00e8re avec des caract\u00e9ristiques de Fourier al\u00e9atoires et un renforcement du gradient<\/strong><br \/>\nL\u00e9o Gautheron ; Pascal Germain ; Amaury Habrard ; Guillaume Metzler ; Emilie Morvant ; Marc Sebban ; Valentina Zantedeschi<br \/>\n<em>French Conference on Machine Learning (CAp 2020),\u00a0<b>2020<\/b><\/em><\/li>\n<li><strong>Revisite des &#8220;random Fourier features&#8221; bas\u00e9e sur l&#8217;apprentissage PAC-Bay\u00e9sien via des points d&#8217;int\u00e9r\u00eats<\/strong><br \/>\nL\u00e9o Gautheron ; Pascal Germain ; Amaury Habrard ; Ga\u00ebl Letarte ; Emilie Morvant ; Marc Sebban ; Valentina Zantedeschi<br \/>\n<em>French Conference on Machine Learning (CAp 2019),\u00a0<b>2019<\/b><\/em><\/li>\n<\/ul>\n<h1>Workshops<\/h1>\n<ul>\n<li><strong>Interpreting Neural Networks as Majority Votes through the PAC-Bayesian Theory<\/strong><br \/>\nPaul Viallard ; R\u00e9mi Emonet ; Pascal Germain ; Amaury Habrard ; Emilie Morvant<br \/>\n<em>NeurIPS\u00a0<b>2019<\/b>\u00a0Workshop on\u00a0<a href=\"https:\/\/sites.google.com\/view\/mlwithguarantees\" target=\"_blank\" rel=\"noopener\">Machine Learning with guarantees<\/a><\/em><\/li>\n<li><strong>Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks<\/strong><br \/>\nGa\u00ebl Letarte ; Pascal Germain ; Benjamin Guedj ; Fran\u00e7ois Laviolette<br \/>\n<em>NeurIPS\u00a0<b>2019<\/b>\u00a0Workshop on\u00a0<a href=\"https:\/\/sites.google.com\/view\/mlwithguarantees\" target=\"_blank\" rel=\"noopener\">Machine Learning with guarantees<\/a><\/em><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>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\u2026<\/p>\n<p> <a class=\"continue-reading-link\" href=\"https:\/\/project.inria.fr\/apriori\/publications\/\"><span>Continue reading<\/span><i class=\"crycon-right-dir\"><\/i><\/a> <\/p>\n","protected":false},"author":1525,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-89","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/project.inria.fr\/apriori\/wp-json\/wp\/v2\/pages\/89","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/project.inria.fr\/apriori\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/project.inria.fr\/apriori\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/apriori\/wp-json\/wp\/v2\/users\/1525"}],"replies":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/apriori\/wp-json\/wp\/v2\/comments?post=89"}],"version-history":[{"count":14,"href":"https:\/\/project.inria.fr\/apriori\/wp-json\/wp\/v2\/pages\/89\/revisions"}],"predecessor-version":[{"id":219,"href":"https:\/\/project.inria.fr\/apriori\/wp-json\/wp\/v2\/pages\/89\/revisions\/219"}],"wp:attachment":[{"href":"https:\/\/project.inria.fr\/apriori\/wp-json\/wp\/v2\/media?parent=89"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}