François Laviolette

24 papers · 2006–2022 · 7 conferences · across top CS/AI conferences

Achievements

+12 more ↓

🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🗺️ Taxonomy Completionist (10) 🌍 Conference Polyglot (7)

🌍 Conference Polyglot (7) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (4) 🤝 Dynamic Duo (10) 🏆 Keyword Champion 🔬 Deep Specialist (13) 💎 Century Club (24) 📈 Trend Setter 🚀 Conference Pioneer 🗃️ Keyword Collector (91) 🔥 Unstoppable (10)

Conferences

NIPS (7) ICML (5) JMLR (5) AISTATS (4) EMNLP (1) IJCAI (1) UAI (1)

Top co-authors

Mario Marchand (10) Pascal Germain (10) Alexandre Lacasse (4) Jean-Francis Roy (4) Philippe Giguère (3) Alexandre Lacoste (2) Sébastien Giguère (2) Amaury Habrard (2) Nicolas Usunier (2) Hugo Larochelle (2)

Keywords

ensemble learning (5) learning theory (5) risk bound (5) pac-bayes bound (4) majority vote (3) generalization bound (3) domain adaptation (3) gibbs classifier (3) classifier ensemble (2) pac-bayesian bound (2) neural network (2) margin-based learning (2) bayesian inference (2) pac-bayesian theory (2) sample compression (2) variational inference (2) pac-bayesian analysis (2) transductive learning (2) structured output prediction (2) sentiment analysis (1)

Papers

Toolbox for Multimodal Learn (scikit-multimodallearn) JMLR 2022 The Indian Chefs Process UAI 2020 Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks NIPS 2019 Importance of Self-Attention for Sentiment Analysis EMNLP 2018 Maximum Margin Interval Trees NIPS 2017 PAC-Bayesian Bounds based on the Rényi Divergence AISTATS 2016 A Column Generation Bound Minimization Approach with PAC-Bayesian Generalization Guarantees AISTATS 2016 Domain-Adversarial Training of Neural Networks JMLR 2016 A New PAC-Bayesian Perspective on Domain Adaptation ICML 2016 Algorithms for the Hard Pre-Image Problem of String Kernels and the General Problem of String Prediction ICML 2015 Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm JMLR 2015 PAC-Bayesian Theory for Transductive Learning AISTATS 2014 Agnostic Bayesian Learning of Ensembles ICML 2014 Risk Bounds and Learning Algorithms for the Regression Approach to Structured Output Prediction ICML 2013 A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers ICML 2013 Accelerated Robust Point Cloud Registration in Natural Environments through Positive and Unlabeled Learning IJCAI 2013 Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets AISTATS 2012 PAC-Bayesian Analysis of Contextual Bandits NIPS 2011 From PAC-Bayes Bounds to KL Regularization NIPS 2009 A Transductive Bound for the Voted Classifier with an Application to Semi-supervised Learning NIPS 2008 PAC-Bayes Risk Bounds for Stochastic Averages and Majority Votes of Sample-Compressed Classifiers JMLR 2007 Revised Loss Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced Data JMLR 2007 A PAC-Bayes Risk Bound for General Loss Functions NIPS 2006 PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier NIPS 2006