Aurelie C. Lozano 
contact information
Research Staff Member -- Machine LearningThomas J. Watson Research Center, Yorktown Heights, NY USA +1
9149452138
9149452138 links
2020
Regularized Multi-trait Linear Mixed Models for Genome-wide Association Studies and Genomic Selection
Aurelie C. Lozano, Hantian Ding, Alexander E. Lipka, Naoki Abe
Under review, 2020
Aurelie C. Lozano, Hantian Ding, Alexander E. Lipka, Naoki Abe
Under review, 2020
2019
A graph Laplacian prior for Bayesian variable selection and grouping
S Chakraborty, AC Lozano
Computational Statistics and Data Analysis, 2019
S Chakraborty, AC Lozano
Computational Statistics and Data Analysis, 2019
Simultaneous Parameter Learning and Bi-Clustering for Multi-Response Models
Ming Yu, Karthikeyan Natesan Ramamurthy, Addie Thompson, Aurelie Lozano
Frontiers in Big Data, 2019
Ming Yu, Karthikeyan Natesan Ramamurthy, Addie Thompson, Aurelie Lozano
Frontiers in Big Data, 2019
Trimming the L1 Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning
Jihun Yun, Peng Zheng, Eunho Yang, Aurelie Lozano, Aleksandr Aravkin
ICML 2019 -- Full oral, 159/3424=4.64%, pp. 7242-7251
Jihun Yun, Peng Zheng, Eunho Yang, Aurelie Lozano, Aleksandr Aravkin
ICML 2019 -- Full oral, 159/3424=4.64%, pp. 7242-7251
2018
Log-Linear Models, Extensions, and Applications
A. C. Lozano, H. Jiang, X. Deng
Log-Linear Models, Extensions, and Applications, MIT Press , 2018
A. C. Lozano, H. Jiang, X. Deng
Log-Linear Models, Extensions, and Applications, MIT Press , 2018
On Extensions of CLEVER: a Neural Network Robustness Evaluation Algorithm
Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Aurelie Lozano, Cho-Jui Hsieh, Luca Daniel
IEEE GlobalSIP, 2018
Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Aurelie Lozano, Cho-Jui Hsieh, Luca Daniel
IEEE GlobalSIP, 2018
A general family of trimmed estimators for robust high-dimensional data analysis
Yang, E., Lozano, A. and Aravkin, A.
The Electronic Journal of Statistics, Vol. 12, No. 2, 3519-3553, 2018
Yang, E., Lozano, A. and Aravkin, A.
The Electronic Journal of Statistics, Vol. 12, No. 2, 3519-3553, 2018
Stratification of TAD boundaries reveals preferential insulation of super-enhancers by strong boundaries
Yixiao Gong, Charalampos Lazaris, Theodore Sakellaropoulos, Aurelie Lozano, Prabhanjan Kambadur, Panagiotis Ntziachristos, Iannis Aifantis, Aristotelis Tsirigos
Nature Communications, 9(1), p.542., 2018
Yixiao Gong, Charalampos Lazaris, Theodore Sakellaropoulos, Aurelie Lozano, Prabhanjan Kambadur, Panagiotis Ntziachristos, Iannis Aifantis, Aristotelis Tsirigos
Nature Communications, 9(1), p.542., 2018
2017
How to foster innovation: a data-driven approach to measuring economic competitiveness
Caitlin Kuhlman, Karthikenyan Natesan Ramamurthy, Prassana Sattigeri, Aurelie C. Lozano, Lei Cao, Chandra Reddy, Aleksandra Mojsilovic, Kush R. Varshney
IBM Journal of Research and Development, vol. 61, no. 6, pp. 11:1-11:12, Nov.-Dec. 1 2017.
Caitlin Kuhlman, Karthikenyan Natesan Ramamurthy, Prassana Sattigeri, Aurelie C. Lozano, Lei Cao, Chandra Reddy, Aleksandra Mojsilovic, Kush R. Varshney
IBM Journal of Research and Development, vol. 61, no. 6, pp. 11:1-11:12, Nov.-Dec. 1 2017.
Sparsity grouped multitask learning for drug molecular activity prediction
Meghana Kshirsagar, Eunho Yang, Aurelie C. Lozano
ICML Workshop on Computational Biology, 2017
Meghana Kshirsagar, Eunho Yang, Aurelie C. Lozano
ICML Workshop on Computational Biology, 2017
Learning task structure via sparsity grouped multitask learning
Meghana Kshirsagar, Eunho Yang, Aurelie C. Lozano
ECML-PKDD 2017
Meghana Kshirsagar, Eunho Yang, Aurelie C. Lozano
ECML-PKDD 2017
Generalized Kalman Smoothing: Modeling and Algorithms
A.Y. Aravkin, J.V. Burke, L. Ljung, A. Lozano, G. Pillonetto
Automatica, 2017
A.Y. Aravkin, J.V. Burke, L. Ljung, A. Lozano, G. Pillonetto
Automatica, 2017
Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World
Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurelie Lozano
International Joint Conference on Artificial Intelligence (IJCAI-2017). Extended verion arXiv:1701.06106
Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurelie Lozano
International Joint Conference on Artificial Intelligence (IJCAI-2017). Extended verion arXiv:1701.06106
Sparse + Group-Sparse Dirty Models: Statistical Guarantees without Unreasonable Conditions and a Case for Non-Convexity
Eunho Yang and Aurelie C. Lozano
ICML, 2017
Eunho Yang and Aurelie C. Lozano
ICML, 2017
2016
Minimum Distance Lasso for robust high-dimensional regression
Aurelie C Lozano, Nicolai Meinshausen and Eunho Yang
Electronic Journal of Statistics 10(1), 1296--1340, The Institute of Mathematical Statistics and the Bernoulli Society, 2016
Aurelie C Lozano, Nicolai Meinshausen and Eunho Yang
Electronic Journal of Statistics 10(1), 1296--1340, The Institute of Mathematical Statistics and the Bernoulli Society, 2016
Temporal Causal Modeling
P. Kambadur, A.C. Lozano, R. Luss
Financial Signal Processing and Machine Learning, John Wiley & Sons, 2016
P. Kambadur, A.C. Lozano, R. Luss
Financial Signal Processing and Machine Learning, John Wiley & Sons, 2016
Removing Clouds and Recovering Ground Observations in Satellite Image Sequences via Temporally Contiguous Robust Matrix Completion
Wang, Jialei and Olsen, Peder A and Conn, Andrew R and Lozano, Aurelie C
29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
Wang, Jialei and Olsen, Peder A and Conn, Andrew R and Lozano, Aurelie C
29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
An Efficient Nonlinear Regression Approach for Genome-wide Detection of Marginal and Interacting Genetic Variations
S. Lee, A. Lozano, P. Kambadur, and E. P. Xing
Journal of Computational Biology 23 (5), 372-389, 2016
S. Lee, A. Lozano, P. Kambadur, and E. P. Xing
Journal of Computational Biology 23 (5), 372-389, 2016
Understanding Innovation to Drive Sustainable Development
P. Sattigeri, A.C. Lozano, A. Mojsilovic, K.R. Varshney and M. Naghshineh
ICML Workshop #Data4Good: Machine Learning in Social Good Applications, 2016
P. Sattigeri, A.C. Lozano, A. Mojsilovic, K.R. Varshney and M. Naghshineh
ICML Workshop #Data4Good: Machine Learning in Social Good Applications, 2016
2015
Variable-Selection Emerges on Top in Empirical Comparison of Whole-Genome Complex-Trait Prediction Methods
David C. Haws, Irina Rish, Simon Teyssedre, Dan He, Aurelie C. Lozano, Prabhanjan Kambadur, Zivan Karaman, Laxmi Parida
PloS one 10(10), 2015
David C. Haws, Irina Rish, Simon Teyssedre, Dan He, Aurelie C. Lozano, Prabhanjan Kambadur, Zivan Karaman, Laxmi Parida
PloS one 10(10), 2015
Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso
Eunho Yang and Aurelie C. Lozano
NIPS, 2015
Eunho Yang and Aurelie C. Lozano
NIPS, 2015
Closed-form Estimators for High-dimensional Generalized Linear Models
Eunho Yang, Aurelie C. Lozano, Pradeep Ravikumar
NIPS (Selected as Spotlight), 2015
Eunho Yang, Aurelie C. Lozano, Pradeep Ravikumar
NIPS (Selected as Spotlight), 2015
An Efficient Nonlinear Regression Approach for Genome-Wide Detection of Marginal and Interacting Genetic Variations
S. Lee, A. Lozano, P. Kambadur, and E. P. Xing
19th International Conference on Research in Computational Molecular Biology (RECOMB 2015)
S. Lee, A. Lozano, P. Kambadur, and E. P. Xing
19th International Conference on Research in Computational Molecular Biology (RECOMB 2015)
Multi-Relational Learning via Hierarchical Nonparametric Bayesian Collective Matrix Factorization
H. Yang, A.C. Lozano
Journal of Applied Statistics 42(5), 2015
H. Yang, A.C. Lozano
Journal of Applied Statistics 42(5), 2015
2014
Orthogonal Matching Pursuit for Sparse Quantile Regression.
A.Y. Aravkin, A. Kambadur, A.C. Lozano, and R. Luss
To appear in IEEE International Conference on Data Mining (ICDM), 2014
A.Y. Aravkin, A. Kambadur, A.C. Lozano, and R. Luss
To appear in IEEE International Conference on Data Mining (ICDM), 2014
Elementary Estimators for Sparse Covariance Matrices and other Structured Moments
E. Yang, A.C. Lozano, P. Ravikumar
International Conference on Machine Learning (ICML), 2014
E. Yang, A.C. Lozano, P. Ravikumar
International Conference on Machine Learning (ICML), 2014
Elementary Estimators for High-Dimensional Linear Regression
E. Yang, A.C. Lozano, P. Ravikumar
International Conference on Machine Learning (ICML), 2014
E. Yang, A.C. Lozano, P. Ravikumar
International Conference on Machine Learning (ICML), 2014
Elementary Estimators for Graphical Models
E. Yang, A.C. Lozano, P. Ravikumar
Neural Information Processing Systems Conference (NIPS), 2014
E. Yang, A.C. Lozano, P. Ravikumar
Neural Information Processing Systems Conference (NIPS), 2014
Practical Applications of Sparse Modeling
A book edited by I. Rish, G. Cecchi, A.C. Lozano, A. Niculecu-Mizil
MIT Press, 2014
A book edited by I. Rish, G. Cecchi, A.C. Lozano, A. Niculecu-Mizil
MIT Press, 2014
Bayesian Regularization via Graph Laplacian
F. Liu, S. Chakraborty, F. Li, Y. Liu and A. Lozano
Bayesian Analysis , 2014
F. Liu, S. Chakraborty, F. Li, Y. Liu and A. Lozano
Bayesian Analysis , 2014
Convergence and Consistency of Regularized Boosting with Weakly Dependent Observations
Aurelie C. Lozano, Sanjeev R. Kulkarni and Robert E. Schapire
IEEE Transactions on Information Theory , 2014
Aurelie C. Lozano, Sanjeev R. Kulkarni and Robert E. Schapire
IEEE Transactions on Information Theory , 2014
2013
Robust Sparse Estimation of Multiresponse Regression and Inverse Covariance Matrix via the L2 distance
Aurelie Lozano, Huijing Jiang, Xinwei Deng
KDD 2013
Aurelie Lozano, Huijing Jiang, Xinwei Deng
KDD 2013
A Parallel Block Greedy Method for Sparse Inverse Covariance Estimation in Ultra-high Dimensions
P. Kambadur and A.C. Lozano
AISTATS 2013
P. Kambadur and A.C. Lozano
AISTATS 2013
Scalable Matrix-valued Kernel Learning and High-dimensional Nonlinear Causal Inference.
Vikas Sindhwani, Aurelie C. Lozano, Ha Quang Minh
Uncertainty in Artifical Intelligence (UAI) 2013. UAI Best Paper award. IBM Pat Goldberg Memorial Best Paper Award 2013.
Vikas Sindhwani, Aurelie C. Lozano, Ha Quang Minh
Uncertainty in Artifical Intelligence (UAI) 2013. UAI Best Paper award. IBM Pat Goldberg Memorial Best Paper Award 2013.
2012
Multi-level Lasso for Sparse Multi-task Regression
Aurelie C Lozano and Grzegorz Swirszcz
ICML, 2012
Aurelie C Lozano and Grzegorz Swirszcz
ICML, 2012
A Bayesian Markov-switching Model for Sparse Dynamic Network Estimation
H. Jiang, A.Lozano, F. Liu
SDM 2012: Proceedings of 2012 SIAM International Conference on Data Mining
H. Jiang, A.Lozano, F. Liu
SDM 2012: Proceedings of 2012 SIAM International Conference on Data Mining
2011
Temporal Graphical Models for Cross-Species Gene Regulatory Network Discovery
Y. Liu, A. Niculescu-Mizil, A. Lozano, Y. Lu
J Bioinform Comput Biol 8(2), 231-250, 2011
Y. Liu, A. Niculescu-Mizil, A. Lozano, Y. Lu
J Bioinform Comput Biol 8(2), 231-250, 2011
Group Orthogonal Matching Pursuit for Logistic Regression
Aurelie Lozano, Grzegorz Swirszcz, Naoki Abe;
Journal of Machine Learning Research, AISTATS15, 452-460, 2011
Aurelie Lozano, Grzegorz Swirszcz, Naoki Abe;
Journal of Machine Learning Research, AISTATS15, 452-460, 2011
Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels
V Sindhwani, A C Lozano
Proc. of the Neural Information Processing Systems Conference (NIPS), 2011
V Sindhwani, A C Lozano
Proc. of the Neural Information Processing Systems Conference (NIPS), 2011
2010
Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference
A C Lozano, V Sindhwani
Proc. of the Neural Information Processing Systems Conference (NIPS), 2010.
A C Lozano, V Sindhwani
Proc. of the Neural Information Processing Systems Conference (NIPS), 2010.
Learning Temporal Causal Graphs for Relational Time-Series Analysis
Y Liu, A Niculescu-Mizil, A Lozano
International conference on Machine Learning (ICML), 2010
Y Liu, A Niculescu-Mizil, A Lozano
International conference on Machine Learning (ICML), 2010
Temporal Graphical Models for Cross-Species Gene Regulatory Network Discovery
Y Liu, A Niculescu-Mizil, A Lozano, Y Lu
International conference on Computational Systems Bioinformatics (CSB), 2010
Y Liu, A Niculescu-Mizil, A Lozano, Y Lu
International conference on Computational Systems Bioinformatics (CSB), 2010
2009
Grouped graphical Granger modeling methods for temporal causal modeling
Aurelie C Lozano, Naoki Abe, Yan Liu, Saharon Rosset
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 577--586, ACM, 2009
Abstract
Aurelie C Lozano, Naoki Abe, Yan Liu, Saharon Rosset
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 577--586, ACM, 2009
Abstract
Spatial-temporal causal modeling for climate change attribution
Aurelie C Lozano, Hongfei Li, Alexandru Niculescu-Mizil, Yan Liu, Claudia Perlich, Jonathan Hosking, Naoki Abe
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 587--596, ACM, 2009
Abstract
Aurelie C Lozano, Hongfei Li, Alexandru Niculescu-Mizil, Yan Liu, Claudia Perlich, Jonathan Hosking, Naoki Abe
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 587--596, ACM, 2009
Abstract
Proximity-Based Anomaly Detection using Sparse Structure Learning
\bf Tsuyoshi Id\'e, Aurelie C. Lozano, Naoki Abe, Yan Liu
Proceedings of 2009 SIAM International Conference on Data Mining (SDM 09), pp. 97--108
\bf Tsuyoshi Id\'e, Aurelie C. Lozano, Naoki Abe, Yan Liu
Proceedings of 2009 SIAM International Conference on Data Mining (SDM 09), pp. 97--108
Grouped graphical Granger modeling for gene expression regulatory networks discovery
A C Lozano, N Abe, Y Liu, S Rosset
Bioinformatics 25(12), i110, Oxford Univ Press, 2009
A C Lozano, N Abe, Y Liu, S Rosset
Bioinformatics 25(12), i110, Oxford Univ Press, 2009
A data modeling approach to climate change attribution
A Lozano
Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data, pp. 9, 2009
A Lozano
Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data, pp. 9, 2009
Group Orthogonal Matching Pursuit for Variable Selection and Prediction
A C Lozano, G Swirszcz, N Abe
Proc. of the Neural Information Processing Systems Conference (NIPS), 2009.
A C Lozano, G Swirszcz, N Abe
Proc. of the Neural Information Processing Systems Conference (NIPS), 2009.
2008
Introduction to Boosting: Origin, Practice and Recent Developments
N Abe, A C Lozano
Forum Math for Industry, Tokyo, Japan, 2008
N Abe, A C Lozano
Forum Math for Industry, Tokyo, Japan, 2008
Multi-class cost-sensitive boosting with p-norm loss functions
Aurelie C Lozano, Naoki Abe
Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 506--514, ACM, 2008
Abstract
Aurelie C Lozano, Naoki Abe
Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 506--514, ACM, 2008
Abstract