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Mathieu Guillame-Bert
Mathieu Guillame-Bert
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Title
Cited by
Cited by
Year
Using supervised machine learning to classify real alerts and artifact in online multisignal vital sign monitoring data
L Chen, A Dubrawski, D Wang, M Fiterau, M Guillame-Bert, E Bose, ...
Critical care medicine 44 (7), e456-e463, 2016
802016
Learning temporal association rules on symbolic time sequences
M Guillame-Bert, JL Crowley
Asian conference on machine learning, 159-174, 2012
412012
Learning temporal rules to forecast instability in continuously monitored patients
M Guillame-Bert, A Dubrawski, D Wang, M Hravnak, G Clermont, ...
Journal of the American Medical Informatics Association 24 (1), 47-53, 2017
302017
Classification of time sequences using graphs of temporal constraints
M Guillame-Bert, A Dubrawski
Journal of Machine Learning Research 18 (121), 1-34, 2017
272017
Data-driven classification of screwdriving operations
RM Aronson, A Bhatia, Z Jia, M Guillame-Bert, D Bourne, A Dubrawski, ...
2016 International Symposium on Experimental Robotics, 244-253, 2017
162017
Predicting home service demands from appliance usage data
K Basu, M Guillame-Bert, H Joumaa, S Ploix, J Crowley
International conference on information and communication technologies and …, 2011
152011
New approach on temporal data mining for symbolic time sequences: Temporal tree associate rules
M Guillame-Bert, JL Crowley
2011 IEEE 23rd International Conference on Tools with Artificial …, 2011
142011
First-order logic learning in artificial neural networks
M Guillame-Bert, K Broda, AA Garcez
The 2010 International Joint Conference on Neural Networks (IJCNN), 1-8, 2010
112010
Increasing cardiovascular data sampling frequency and referencing it to baseline improve hemorrhage detection
A Wertz, AL Holder, M Guillame-Bert, G Clermont, A Dubrawski, ...
Critical Care Explorations 1 (10), e0058, 2019
82019
Exact distributed training: Random forest with billions of examples
M Guillame-Bert, O Teytaud
arXiv preprint arXiv:1804.06755, 2018
82018
Artifact patterns in continuous noninvasive monitoring of patients
M Hravnak, L Chen, E Bose, M Fiterau, M Guillame-Bert, A Dubrawski, ...
Intensive care medicine 39 (Suppl 2), S405, 2013
82013
Generative trees: Adversarial and copycat
R Nock, M Guillame-Bert
arXiv preprint arXiv:2201.11205, 2022
72022
Learning temporal rules to forecast events in multivariate time sequences
M Guillame-Bert, A Dubrawski
2nd Workshop on Machine Learning for Clinical Data Analysis, Healthcare and …, 2014
72014
Introducing TensorFlow decision forests
M Guillame-Bert, S Bruch, J Gordon, J Pfeifer
Online]. URL: https://blog. tensorflow. org/2021/05/introducing-tensorflow …, 2021
52021
Yggdrasil decision forests: A fast and extensible decision forests library
M Guillame-Bert, S Bruch, R Stotz, J Pfeifer
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
42023
Learning representations for axis-aligned decision forests through input perturbation
S Bruch, J Pfeifer, M Guillame-Bert
arXiv preprint arXiv:2007.14761, 2020
42020
Systems and Methods for Distributed Generation of Decision Tree-Based Models
M Guillame-bert, O Teytaud
US Patent App. 16/271,064, 2019
42019
Learning temporal rules to forecast instability in intensive care patients
M Guillame-Bert, A Dubrawski, L Chen, M Hravnak, M Pinsky, G Clermont
Intensive care medicine 39 (Suppl 2), S470, 2013
42013
Utility of empirical models of hemorrhage in detecting and quantifying bleeding
M Guillame-Bert, A Dubrawski, L Chen, A Holder, MR Pinsky, G Clermont
Intensive Care Medicine 40, S287-S287, 2014
32014
Planning with inaccurate temporal rules
M Guillame-Bert, JL Crowley
2012 IEEE 24th International Conference on Tools with Artificial …, 2012
32012
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