Liva Ralaivola
Liva Ralaivola
Criteo AI Lab
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Gene networks inference using dynamic Bayesian networks
BE Perrin, L Ralaivola, A Mazurie, S Bottani, J Mallet, F d’Alche–Buc
Bioinformatics 19 (suppl_2), ii138-ii148, 2003
Graph kernels for chemical informatics
L Ralaivola, SJ Swamidass, H Saigo, P Baldi
Neural networks 18 (8), 1093-1110, 2005
Kernels for small molecules and the prediction of mutagenicity, toxicity and anti-cancer activity
SJ Swamidass, J Chen, J Bruand, P Phung, L Ralaivola, P Baldi
Bioinformatics 21 (suppl_1), i359-i368, 2005
Incremental support vector machine learning: A local approach
L Ralaivola, F d’Alché-Buc
International conference on artificial neural networks, 322-330, 2001
The pharmacophore kernel for virtual screening with support vector machines
P Mahé, L Ralaivola, V Stoven, JP Vert
Journal of Chemical Information and Modeling 46 (5), 2003-2014, 2006
Learning SVMs from sloppily labeled data
G Stempfel, L Ralaivola
International conference on artificial neural networks, 884-893, 2009
Dynamic screening: Accelerating first-order algorithms for the lasso and group-lasso
A Bonnefoy, V Emiya, L Ralaivola, R Gribonval
IEEE Transactions on Signal Processing 63 (19), 5121-5132, 2015
One-to four-dimensional kernels for virtual screening and the prediction of physical, chemical, and biological properties
CA Azencott, A Ksikes, SJ Swamidass, JH Chen, L Ralaivola, P Baldi
Journal of chemical information and modeling 47 (3), 965-974, 2007
Dynamical modeling with kernels for nonlinear time series prediction
L Ralaivola, F d'Alché-Buc
Advances in neural information processing systems 16, 2003
Grammatical inference as a principal component analysis problem
R Bailly, F Denis, L Ralaivola
Proceedings of the 26th Annual International Conference on Machine Learning …, 2009
Time series filtering, smoothing and learning using the kernel Kalman filter
L Ralaivola, F d'Alché-Buc
Proceedings. 2005 IEEE International Joint Conference on Neural Networks …, 2005
Chromatic PAC-Bayes bounds for non-iid data: Applications to ranking and stationary β-mixing processes
L Ralaivola, M Szafranski, G Stempfel
The Journal of Machine Learning Research 11, 1927-1956, 2010
A dynamic screening principle for the lasso
A Bonnefoy, V Emiya, L Ralaivola, R Gribonval
2014 22nd European Signal Processing Conference (EUSIPCO), 6-10, 2014
Multiple indefinite kernel learning with mixed norm regularization
M Kowalski, M Szafranski, L Ralaivola
Proceedings of the 26th Annual International Conference on Machine Learning …, 2009
Empirical Bernstein inequalities for u-statistics
T Peel, S Anthoine, L Ralaivola
Advances in Neural Information Processing Systems 23, 2010
Graph-based inter-subject pattern analysis of fMRI data
S Takerkart, G Auzias, B Thirion, L Ralaivola
PloS one 9 (8), e104586, 2014
PAC-Bayesian generalization bound on confusion matrix for multi-class classification
E Morvant, S Koço, L Ralaivola
arXiv preprint arXiv:1202.6228, 2012
SVM and pattern-enriched common fate graphs for the game of go.
L Ralaivola, L Wu, P Baldi
ESANN 2005, 27-29, 2005
Incremental learning algorithms for classification and regression: Local strategies
F d’Alché‐Buc, L Ralaivola
AIP Conference Proceedings 627 (1), 320-329, 2002
Learning kernel perceptrons on noisy data using random projections
G Stempfel, L Ralaivola
International Conference on Algorithmic Learning Theory, 328-342, 2007
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