Aurelie C. Lozano

Publication Activity (10 Years)

Years Active: 2002-2021
Publications (10 Years): 17

Top Topics

Kernel Learning

Covariance Matrices

Nonlinear Regression

Top Venues

Publications

Igor Melnyk, Payel Das, Vijil Chenthamarakshan, Aurelie C. Lozano
Benchmarking deep generative models for diverse antibody sequence design. CoRR (2021)
Jihun Yun, Aurelie C. Lozano, Eunho Yang
A General Family of Stochastic Proximal Gradient Methods for Deep Learning. CoRR (2020)
Jihun Yun, Aurelie C. Lozano, Eunho Yang
Stochastic Gradient Methods with Block Diagonal Matrix Adaptation. CoRR (2019)
Sounak Chakraborty, Aurelie C. Lozano
A graph Laplacian prior for Bayesian variable selection and grouping. Comput. Stat. Data Anal. 136 (2019)
Jihun Yun, Peng Zheng, Eunho Yang, Aurelie C. Lozano, Aleksandr Y. Aravkin
Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning. ICML (2019)
Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Aurelie C. Lozano, Cho-Jui Hsieh, Luca Daniel
On Extensions of Clever: A Neural Network Robustness Evaluation Algorithm. GlobalSIP (2018)
Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Aurelie C. Lozano, Cho-Jui Hsieh, Luca Daniel
On Extensions of CLEVER: A Neural Network Robustness Evaluation Algorithm. CoRR (2018)
Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurelie C. Lozano
Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. IJCAI (2017)
Aleksandr Y. Aravkin, James V. Burke, Lennart Ljung, Aurelie C. Lozano, Gianluigi Pillonetto
Generalized Kalman smoothing: Modeling and algorithms. Autom. 86 (2017)
Caitlin Kuhlman, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Aurelie C. Lozano, Lei Cao, C. Reddy, Aleksandra Mojsilovic, Kush R. Varshney
How to foster innovation: A data-driven approach to measuring economic competitiveness. IBM J. Res. Dev. 61 (6) (2017)
Seunghak Lee, Aurelie C. Lozano, Prabhanjan Kambadur, Eric P. Xing
An Efficient Nonlinear Regression Approach for Genome-wide Detection of Marginal and Interacting Genetic Variations. J. Comput. Biol. 23 (5) (2016)
Jialei Wang, Peder A. Olsen, Andrew R. Conn, Aurelie C. Lozano
Removing Clouds and Recovering Ground Observations in Satellite Image Sequences via Temporally Contiguous Robust Matrix Completion. CVPR (2016)
Aurelie C. Lozano, Prasanna Sattigeri, Aleksandra Mojsilovic, Kush R. Varshney
Stable estimation of Granger-causal factors of country-level innovation. GlobalSIP (2016)
Jialei Wang, Peder A. Olsen, Andrew R. Conn, Aurelie C. Lozano
Removing Clouds and Recovering Ground Observations in Satellite Image Sequences via Temporally Contiguous Robust Matrix Completion. CoRR (2016)
Eunho Yang, Aurelie C. Lozano
Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso. NIPS (2015)
Seunghak Lee, Aurelie C. Lozano, Prabhanjan Kambadur, Eric P. Xing
An Efficient Nonlinear Regression Approach for Genome-Wide Detection of Marginal and Interacting Genetic Variations. RECOMB (2015)
Eunho Yang, Aurelie C. Lozano, Pradeep Ravikumar
Closed-form Estimators for High-dimensional Generalized Linear Models. NIPS (2015)
Eunho Yang, Aurelie C. Lozano, Pradeep Ravikumar
Elementary Estimators for High-Dimensional Linear Regression. ICML (2014)
Aleksandr Y. Aravkin, Anju Kambadur, Aurelie C. Lozano, Ronny Luss
Sparse Quantile Huber Regression for Efficient and Robust Estimation. CoRR (2014)
Aurelie C. Lozano, Sanjeev R. Kulkarni, Robert E. Schapire
Convergence and Consistency of Regularized Boosting With Weakly Dependent Observations. IEEE Trans. Inf. Theory 60 (1) (2014)
Eunho Yang, Aurelie C. Lozano, Pradeep Ravikumar
Elementary Estimators for Sparse Covariance Matrices and other Structured Moments. ICML (2014)
Eunho Yang, Aurelie C. Lozano, Pradeep Ravikumar
Elementary Estimators for Graphical Models. NIPS (2014)
Vikas Sindhwani, Ha Quang Minh, Aurelie C. Lozano
Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality. CoRR (2014)
Aleksandr Y. Aravkin, Aurelie C. Lozano, Ronny Luss, Prabhanjan Kambadur
Orthogonal Matching Pursuit for Sparse Quantile Regression. ICDM (2014)
Aurelie C. Lozano, Huijing Jiang, Xinwei Deng
Robust sparse estimation of multiresponse regression and inverse covariance matrix via the L2 distance. KDD (2013)
Prabhanjan Kambadur, Aurelie C. Lozano
A Parallel, Block Greedy Method for Sparse Inverse Covariance Estimation for Ultra-high Dimensions. AISTATS (2013)
Vikas Sindhwani, Ha Quang Minh, Aurelie C. Lozano
Scalable Matrix-valued Kernel Learning for High-dimensional Nonlinear Multivariate Regression and Granger Causality. UAI (2013)
Vikas Sindhwani, Aurelie C. Lozano, Ha Quang Minh
Scalable Matrix-valued Kernel Learning and High-dimensional Nonlinear Causal Inference CoRR (2012)
Aurelie C. Lozano, Grzegorz Swirszcz
Multi-level Lasso for Sparse Multi-task Regression. ICML (2012)
Huijing Jiang, Aurelie C. Lozano, Fei Liu
A Bayesian Markov-switching Model for Sparse Dynamic Network Estimation. SDM (2012)
Yan Liu, Alexandru Niculescu-Mizil, Aurelie C. Lozano, Yong Lu
Temporal Graphical Models for Cross-Species Gene Regulatory Network Discovery. J. Bioinform. Comput. Biol. 9 (2) (2011)
Vikas Sindhwani, Aurelie C. Lozano
Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels. NIPS (2011)
Aurelie C. Lozano, Grzegorz Swirszcz, Naoki Abe
Group Orthogonal Matching Pursuit for Logistic Regression. AISTATS (2011)
Aurelie C. Lozano, Vikas Sindhwani
Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference. NIPS (2010)
Yan Liu, Alexandru Niculescu-Mizil, Aurelie C. Lozano, Yong Lu
Learning Temporal Causal Graphs for Relational Time-Series Analysis. ICML (2010)
Aurelie C. Lozano, Hongfei Li, Alexandru Niculescu-Mizil, Yan Liu, Claudia Perlich, Jonathan R. M. Hosking, Naoki Abe
Spatial-temporal causal modeling for climate change attribution. KDD (2009)
Aurelie C. Lozano
A data modeling approach to climate change attribution. KDD Workshop on Knowledge Discovery from Sensor Data (2009)
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Rosset
Grouped graphical Granger modeling methods for temporal causal modeling. KDD (2009)
Tsuyoshi Idé, Aurelie C. Lozano, Naoki Abe, Yan Liu
Proximity-Based Anomaly Detection Using Sparse Structure Learning. SDM (2009)
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Rosset
Grouped graphical Granger modeling for gene expression regulatory networks discovery. Bioinform. 25 (12) (2009)
Aurelie C. Lozano, Grzegorz Swirszcz, Naoki Abe
Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction. NIPS (2009)
Aurelie C. Lozano, Naoki Abe
Multi-class cost-sensitive boosting with p-norm loss functions. KDD (2008)
Aurelie C. Lozano, Sanjeev R. Kulkarni, Pramod Viswanath
Throughput scaling in wireless networks with restricted mobility. IEEE Trans. Wirel. Commun. 6 (2) (2007)
Aurelie C. Lozano, Sanjeev R. Kulkarni
Convergence and Consistency of Recursive Boosting. ISIT (2006)
Aurelie C. Lozano, Sanjeev R. Kulkarni
A wireless network can achieve maximum throughput without each node meeting all others. ISIT (2005)
Aurelie C. Lozano, Sanjeev R. Kulkarni, Robert E. Schapire
Convergence and Consistency of Regularized Boosting Algorithms with Stationary B-Mixing Observations. NIPS (2005)
Aurelie C. Lozano, Sanjeev R. Kulkarni, Pramod Viswanath
Throughput scaling in wireless networks with restricted mobility. ISIT (2004)
Aurelie C. Lozano, Jelena Kovacevic, Mike Andrews
Quantized Frame Expansions In A Wireless Environment. DCC (2002)