Aurelie Lozano
Aurelie Lozano
Research Staff Member, IBM Research
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Cited by
Cited by
Grouped graphical Granger modeling for gene expression regulatory networks discovery
AC Lozano, N Abe, Y Liu, S Rosset
Bioinformatics 25 (12), i110-i118, 2009
Spatial-temporal causal modeling for climate change attribution
AC Lozano, H Li, A Niculescu-Mizil, Y Liu, C Perlich, J Hosking, N Abe
Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009
Grouped orthogonal matching pursuit for variable selection and prediction
G Swirszcz, N Abe, AC Lozano
Advances in Neural Information Processing Systems 22, 1150-1158, 2009
Multi-level lasso for sparse multi-task regression
AC Lozano, G Swirszcz
Proceedings of the 29th International Coference on International Conference …, 2012
Proximity-based anomaly detection using sparse structure learning
T Idé, AC Lozano, N Abe, Y Liu
Proceedings of the 2009 SIAM international conference on data mining, 97-108, 2009
Stratification of TAD boundaries reveals preferential insulation of super-enhancers by strong boundaries
Y Gong, C Lazaris, T Sakellaropoulos, A Lozano, P Kambadur, ...
Nature communications 9 (1), 1-12, 2018
Generalized Kalman smoothing: Modeling and algorithms
A Aravkin, JV Burke, L Ljung, A Lozano, G Pillonetto
Automatica 86, 63-86, 2017
Learning temporal causal graphs for relational time-series analysis
Y Liu, A Niculescu-Mizil, AC Lozano, Y Lu
ICML, 2010
Group orthogonal matching pursuit for logistic regression
A Lozano, G Swirszcz, N Abe
Proceedings of the fourteenth international conference on artificial …, 2011
Multi-class cost-sensitive boosting with p-norm loss functions
AC Lozano, N Abe
Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008
Convergence and consistency of regularized boosting algorithms with stationary beta-mixing observations
A Lozano, S Kulkarni, R Schapire
Advances in neural information processing systems 18, 819, 2006
Scalable matrix-valued kernel learning for high-dimensional nonlinear multivariate regression and granger causality
V Sindhwani, MH Quang, AC Lozano
arXiv preprint arXiv:1210.4792, 2012
Grouped graphical Granger modeling methods for temporal causal modeling
AC Lozano, N Abe, Y Liu, S Rosset
Proceedings of the 15th ACM SIGKDD international conference on knowledge …, 2009
Methods and systems for variable group selection and temporal causal modeling
N Abe, Y Liu, AC Lozano, S Rosset, G Swirszcz
US Patent 8,255,346, 2012
Elementary estimators for high-dimensional linear regression
E Yang, A Lozano, P Ravikumar
International Conference on Machine Learning, 388-396, 2014
Casual modeling of multi-dimensional hierarchical metric cubes
N Abe, J Fu, MG Gemmell, S Kapoor, FS Kelly, DM Loehr, AC Lozano, ...
US Patent 10,360,527, 2019
Elementary estimators for graphical models
E Yang, AC Lozano, PK Ravikumar
Advances in neural information processing systems, 2159-2167, 2014
Bayesian regularization via graph Laplacian
F Liu, S Chakraborty, F Li, Y Liu, AC Lozano
Bayesian Analysis 9 (2), 449-474, 2014
Robust gaussian graphical modeling with the trimmed graphical lasso
E Yang, AC Lozano
Advances in Neural Information Processing Systems, 2602-2610, 2015
A general family of trimmed estimators for robust high-dimensional data analysis
E Yang, AC Lozano, A Aravkin
Electronic Journal of Statistics 12 (2), 3519-3553, 2018
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