François Laviolette
24 papers · 2006–2022 · 7 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+11 more ↓ Show less ↑
🗺️ Taxonomy Completionist (34) 🏃 Academic Marathon · Full 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
🌱
Topic Pioneer
🌟
Keyword Trendsetter Combo
(6)
🤝
Dynamic Duo
(10)
🔬
Deep Specialist
(15)
🏆
Keyword Champion
(4)
🧭
Keyword Pioneer
🚀
Conference Pioneer
🗃️
Keyword Collector
(99)
🔥
Unstoppable · Silver
💎
Century Club · Bronze
📈
Trend Setter
Top co-authors
Research topics
Machine Learning
(23)
Optimization & Theory
(19)
Core Methods
(9)
Learning Types
(7)
Artificial Intelligence
(6)
Deep Learning
(3)
Application Areas
(3)
Bayesian & Probabilistic · Machine Learning
(3)
Core AI
(3)
Mathematics & Optimization
(2)
Bayesian & Probabilistic · Artificial Intelligence
(2)
Natural Language Processing
(1)
Applications
(1)
Architectures
(1)
Learning Paradigms
(1)
Keywords
ensemble learning
(5)
risk bound
(5)
learning theory
(5)
gibbs classifier
(4)
pac-bayes bound
(4)
pac-bayesian bound
(3)
domain adaptation
(3)
majority vote
(3)
generalization bound
(3)
classifier ensemble
(2)
neural network
(2)
structured output prediction
(2)
bayesian inference
(2)
pac-bayesian theory
(2)
sample compression
(2)
variational inference
(2)
transductive learning
(2)
margin-based learning
(2)
pac-bayesian analysis
(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
NeurIPS 2019
Importance of Self-Attention for Sentiment Analysis
EMNLP 2018
Maximum Margin Interval Trees
NeurIPS 2017
A Column Generation Bound Minimization Approach with PAC-Bayesian Generalization Guarantees
AISTATS 2016
A New PAC-Bayesian Perspective on Domain Adaptation
ICML 2016
Domain-Adversarial Training of Neural Networks
JMLR 2016
PAC-Bayesian Bounds based on the Rényi Divergence
AISTATS 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
Agnostic Bayesian Learning of Ensembles
ICML 2014
PAC-Bayesian Theory for Transductive Learning
AISTATS 2014
Accelerated Robust Point Cloud Registration in Natural Environments through Positive and Unlabeled Learning
IJCAI 2013
A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers
ICML 2013
Risk Bounds and Learning Algorithms for the Regression Approach to Structured Output Prediction
ICML 2013
Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets
AISTATS 2012
PAC-Bayesian Analysis of Contextual Bandits
NeurIPS 2011
From PAC-Bayes Bounds to KL Regularization
NeurIPS 2009
A Transductive Bound for the Voted Classifier with an Application to Semi-supervised Learning
NeurIPS 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
NeurIPS 2006
PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier
NeurIPS 2006