← Authors

François Laviolette

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

Achievements

🐝 Cross-Pollinator (7) 🏃 Academic Marathon (16) 🌉 Interdisciplinary Bridge 🌈 Renaissance Researcher (5) 🗺️ Taxonomy Completionist (10) 🌍 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) gibbs classifier (3) generalization bound (3) majority vote (3) domain adaptation (3) classifier ensemble (2) pac-bayesian bound (2) neural network (2) bayesian inference (2) structured output prediction (2) pac-bayesian theory (2) pac-bayesian analysis (2) sample compression (2) margin-based learning (2) transductive learning (2) variational inference (2) text classification (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