François Laviolette

Affiliations:
  • Université Laval


According to our database1, François Laviolette authored at least 109 papers between 1994 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of two.

Timeline

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Bibliography

2023
A cop-winning strategy on strongly cop-win graphs.
Discret. Math., August, 2023

MOT: A Multi-Omics Transformer for Multiclass Classification Tumour Types Predictions.
Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies, 2023

PAC-Bayesian Learning of Aggregated Binary Activated Neural Networks with Probabilities over Representations.
Proceedings of the 36th Canadian Conference on Artificial Intelligence, 2023

2022
Toolbox for Multimodal Learn (scikit-multimodallearn).
J. Mach. Learn. Res., 2022

How to certify machine learning based safety-critical systems? A systematic literature review.
Autom. Softw. Eng., 2022

2021
General Cops and Robbers games with randomness.
Theor. Comput. Sci., 2021

Exploring polypharmacy with artificial intelligence: data analysis protocol.
BMC Medical Informatics Decis. Mak., 2021

Multinational Address Parsing: A Zero-Shot Evaluation.
CoRR, 2021

Learning Aggregations of Binary Activated Neural Networks with Probabilities over Representations.
CoRR, 2021

On the robustness of generalization of drug-drug interaction models.
BMC Bioinform., 2021

Leveraging Subword Embeddings for Multinational Address Parsing.
Proceedings of the 6th IEEE Congress on Information Science and Technology, 2021

Applying PySCMGroup to Breast Cancer Biomarkers Discovery.
Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, 2021

2020
Fast greedy <i>C</i>-bound minimization with guarantees.
Mach. Learn., 2020

PAC-Bayes and domain adaptation.
Neurocomputing, 2020

Implicit Variational Inference: the Parameter and the Predictor Space.
CoRR, 2020

The Indian Chefs Process.
CoRR, 2020

Unsupervised Domain Adversarial Self-Calibration for Electromyography-Based Gesture Recognition.
IEEE Access, 2020

The Indian Chefs Process.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Phylogenetic Manifold Regularization: A semi-supervised approach to predict transcription factor binding sites.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

2019

A Low-Cost, Wireless, 3-D-Printed Custom Armband for sEMG Hand Gesture Recognition.
Sensors, 2019

Unsupervised Domain Adversarial Self-Calibration for Electromyographic-based Gesture Recognition.
CoRR, 2019

Virtual Reality to Study the Gap Between Offline and Real-Time EMG-based Gesture Recognition.
CoRR, 2019

Interpreting Deep Learning Features for Myoelectric Control: A Comparison with Handcrafted Features.
CoRR, 2019

Adaptive Deep Kernel Learning.
CoRR, 2019

Finite Approximation of LMPs for Exact Verification of Reachability Properties.
Proceedings of the Quantitative Evaluation of Systems, 16th International Conference, 2019

Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Deep Learning for Electromyographic Hand Gesture Signal Classification by Leveraging Transfer Learning.
CoRR, 2018

Importance of Self-Attention for Sentiment Analysis.
Proceedings of the Workshop: Analyzing and Interpreting Neural Networks for NLP, 2018

2017
Domain-Adversarial Training of Neural Networks.
Proceedings of the Domain Adaptation in Computer Vision Applications., 2017

Risk upper bounds for general ensemble methods with an application to multiclass classification.
Neurocomputing, 2017

Transfer learning for sEMG hand gestures recognition using convolutional neural networks.
Proceedings of the 2017 IEEE International Conference on Systems, Man, and Cybernetics, 2017

Towards the use of consumer-grade electromyographic armbands for interactive, artistic robotics performances.
Proceedings of the 26th IEEE International Symposium on Robot and Human Interactive Communication, 2017

Maximum Margin Interval Trees.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Time Adaptive Dual Particle Swarm Optimization.
Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

2016
Domain-Adversarial Training of Neural Networks.
J. Mach. Learn. Res., 2016

Large scale modeling of antimicrobial resistance with interpretable classifiers.
CoRR, 2016

A convolutional neural network for robotic arm guidance using sEMG based frequency-features.
Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

A New PAC-Bayesian Perspective on Domain Adaptation.
Proceedings of the 33nd International Conference on Machine Learning, 2016

A Column Generation Bound Minimization Approach with PAC-Bayesian Generalization Guarantees.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

PAC-Bayesian Bounds based on the Rényi Divergence.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
Machine Learning Assisted Design of Highly Active Peptides for Drug Discovery.
PLoS Comput. Biol., 2015

Risk bounds for the majority vote: from a PAC-Bayesian analysis to a learning algorithm.
J. Mach. Learn. Res., 2015

On Generalizing the C-Bound to the Multiclass and Multi-label Settings.
CoRR, 2015

PAC-Bayesian Theorems for Domain Adaptation with Specialization to Linear Classifiers.
CoRR, 2015

An Improvement to the Domain Adaptation Bound in a PAC-Bayesian context.
CoRR, 2015

Efficient Learning of Ensembles with QuadBoost.
CoRR, 2015

Greedy Biomarker Discovery in the Genome with Applications to Antimicrobial Resistance.
CoRR, 2015

Machine learning-based metamodels for sawing simulation.
Proceedings of the 2015 Winter Simulation Conference, 2015

Algorithms for the Hard Pre-Image Problem of String Kernels and the General Problem of String Prediction.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Optimizing Question-Answering Systems Using Genetic Algorithms.
Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference, 2015

Bounding an Optimal Search Path with a Game of Cop and Robber on Graphs.
Proceedings of the Principles and Practice of Constraint Programming, 2015

2014
On the String Kernel Pre-Image Problem with Applications in Drug Discovery.
CoRR, 2014

Learning interpretable models of phenotypes from whole genome sequences with the Set Covering Machine.
CoRR, 2014

Domain-Adversarial Neural Networks.
CoRR, 2014

Sequential Model-Based Ensemble Optimization.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

A Topic Model Scoring Approach for Personalized QA Systems.
Proceedings of the Text, Speech and Dialogue - 17th International Conference, 2014

Agnostic Bayesian Learning of Ensembles.
Proceedings of the 31th International Conference on Machine Learning, 2014

PAC-Bayesian Theory for Transductive Learning.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
Tighter PAC-Bayes bounds through distribution-dependent priors.
Theor. Comput. Sci., 2013

Testing probabilistic equivalence through Reinforcement Learning.
Inf. Comput., 2013

Learning a peptide-protein binding affinity predictor with kernel ridge regression.
BMC Bioinform., 2013

Human Analysts at Superhuman Scales: What Has Friendly Software To Do?
Big Data, 2013

Accelerated Robust Point Cloud Registration in Natural Environments through Positive and Unlabeled Learning.
Proceedings of the IJCAI 2013, 2013

Risk Bounds and Learning Algorithms for the Regression Approach to Structured Output Prediction.
Proceedings of the 30th International Conference on Machine Learning, 2013

A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
PAC-Bayesian Inequalities for Martingales.
IEEE Trans. Inf. Theory, 2012

PAC-Bayes-Bernstein Inequality for Martingales and its Application to Multiarmed Bandits.
Proceedings of the Workshop on On-line Trading of Exploration and Exploitation 2, 2012

Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

PAC-Bayesian Learning and Domain Adaptation
CoRR, 2012

Constraint Programming for Path Planning with Uncertainty - Solving the Optimal Search Path Problem.
Proceedings of the Principles and Practice of Constraint Programming, 2012

A Pseudo-Boolean Set Covering Machine.
Proceedings of the Principles and Practice of Constraint Programming, 2012

2011
A logical duality for underspecified probabilistic systems.
Inf. Comput., 2011

PAC-Bayesian Analysis of the Exploration-Exploitation Trade-off
CoRR, 2011

PAC-Bayesian Analysis of Martingales and Multiarmed Bandits
CoRR, 2011

PAC-Bayesian Analysis of Contextual Bandits.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

From PAC-Bayes Bounds to Quadratic Programs for Majority Votes.
Proceedings of the 28th International Conference on Machine Learning, 2011

A PAC-Bayes Sample-compression Approach to Kernel Methods.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
Learning the set covering machine by bound minimization and margin-sparsity trade-off.
Mach. Learn., 2010

Ray: Simultaneous Assembly of Reads from a Mix of High-Throughput Sequencing Technologies.
J. Comput. Biol., 2010

Learning with Randomized Majority Votes.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Distribution-Dependent PAC-Bayes Priors.
Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010

2009
Learning the Difference between Partially Observable Dynamical Systems.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

From PAC-Bayes Bounds to KL Regularization.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

PAC-Bayesian learning of linear classifiers.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

A Demonic Approach to Information in Probabilistic Systems.
Proceedings of the CONCUR 2009 - Concurrency Theory, 20th International Conference, 2009

2008
Approximate Analysis of Probabilistic Processes: Logic, Simulation and Games.
Proceedings of the Fifth International Conference on the Quantitative Evaluaiton of Systems (QEST 2008), 2008

A Transductive Bound for the Voted Classifier with an Application to Semi-supervised Learning.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

A Stochastic Point-Based Algorithm for POMDPs.
Proceedings of the Advances in Artificial Intelligence , 2008

Selective Sampling for Classification.
Proceedings of the Advances in Artificial Intelligence , 2008

2007
PAC-Bayes Risk Bounds for Stochastic Averages and Majority Votes of Sample-Compressed Classifiers.
J. Mach. Learn. Res., 2007

Revised Loss Bounds for the Set Covering Machine and Sample-Compression Loss Bounds for Imbalanced Data.
J. Mach. Learn. Res., 2007

2006
Bisimulation and cocongruence for probabilistic systems.
Inf. Comput., 2006

PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

A PAC-Bayes Risk Bound for General Loss Functions.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

A Selective Sampling Strategy for Label Ranking.
Proceedings of the Machine Learning: ECML 2006, 2006

Trace Equivalence Characterization Through Reinforcement Learning.
Proceedings of the Advances in Artificial Intelligence, 2006

2005
Decompositions of infinite graphs: Part II circuit decompositions.
J. Comb. Theory B, 2005

Decompositions of infinite graphs: I - bond-faithful decompositions.
J. Comb. Theory B, 2005

A PAC-Bayes approach to the Set Covering Machine.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

PAC-Bayes risk bounds for sample-compressed Gibbs classifiers.
Proceedings of the Machine Learning, 2005

Margin-Sparsity Trade-Off for the Set Covering Machine.
Proceedings of the Machine Learning: ECML 2005, 2005

2003
The Countable Character of Uncountable Graphs.
Proceedings of the Workshop on Domain Theoretic Methods for Probabilistic Processes, 2003

2002
On cop-win graphs.
Discret. Math., 2002

2000
On constructible graphs, infinite bridged graphs and weakly cop-win graphs.
Discret. Math., 2000

1999
Spanning trees of countable graphs omitting sets of dominated ends.
Discret. Math., 1999

1998
On Normal Cayley Graphs and Hom-idempotent Graphs.
Eur. J. Comb., 1998

1997
Edge-Ends in Countable Graphs.
J. Comb. Theory B, 1997

1994
Decomposition of infinite eulerian graphs with a small number of vertices of infinite degree.
Discret. Math., 1994


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