Aurélie Lozano
- Artificial Intelligence top 5%
- Molecular Biology
- Computational Mechanics top 10%
- Statistics and Probability top 5%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Naoki AbeGrzegorz ŚwirszczYan LiuSaharon RossetEunho YangAleksandr Y. AravkinAlexandru Niculescu-MizilLennart Ljung
- Topics
- Statistical Methods and Inference (18 papers)Sparse and Compressive Sensing Techniques (11 papers)Gene expression and cancer classification (10 papers)
- Partner nations
- United StatesSouth KoreaIsrael
In The Last Decade
Aurélie Lozano
50 papers receiving 820 citations
Peers
Comparison fields: 5 of 113
- Artificial Intelligence 323
- Molecular Biology 202
- Computational Mechanics 126
- Statistics and Probability 122
- Computer Vision and Pattern Recognition 116
Countries citing papers authored by Aurélie Lozano
This map shows the geographic impact of Aurélie Lozano's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Aurélie Lozano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aurélie Lozano more than expected).
Fields of papers citing papers by Aurélie Lozano
This network shows the impact of papers produced by Aurélie Lozano. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Aurélie Lozano. The network helps show where Aurélie Lozano may publish in the future.
Co-authorship network of co-authors of Aurélie Lozano
This figure shows the co-authorship network connecting the top 25 collaborators of Aurélie Lozano. A scholar is included among the top collaborators of Aurélie Lozano based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Aurélie Lozano. Aurélie Lozano is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | Adaptive Proximal Gradient Methods for Structured Neural Networks | 2 |
| 4 | Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning. | 1 |
| 5 | Closed-form estimators for high-dimensional generalized linear models | 2 |
| 6 | 17 | |
| 7 | Elementary Estimators for Graphical Models | 10 |
| 8 | Elementary Estimators for High-Dimensional Linear Regression | 11 |
| 9 | Elementary Estimators for Sparse Covariance Matrices and other Structured Moments | 10 |
| 10 | A Parallel, Block Greedy Method for Sparse Inverse Covariance Estimation for Ultra-high Dimensions | 1 |
| 11 | Scalable Matrix-valued Kernel Learning and High-dimensional Nonlinear Causal Inference | 1 |
| 12 | Multi-level Lasso for Sparse Multi-task Regression | 46 |
| 13 | Group Orthogonal Matching Pursuit for Logistic Regression | 26 |
| 14 | Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels | 10 |
| 15 | Learning Temporal Causal Graphs for Relational Time-Series Analysis | 22 |
| 16 | Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference | 9 |
| 17 | Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction | 62 |
| 18 | Cost-sensitive Boosting with p-norm Loss Functionsand its Applications | 2 |
| 19 | Convergence and Consistency of Regularized Boosting Algorithms with Stationary B-Mixing Observations | 22 |
| 20 | 1 |
About Aurélie Lozano
Aurélie Lozano is a scholar working on Statistics and Probability, Artificial Intelligence and Computational Mechanics, having authored 52 papers that have together received 857 indexed citations. Recurring topics across this work include Statistical Methods and Inference (18 papers), Sparse and Compressive Sensing Techniques (11 papers) and Gene expression and cancer classification (10 papers). The work is most often cited by research in Computational Mathematics (16 citations), Statistics and Probability (122 citations) and Artificial Intelligence (323 citations). Aurélie Lozano has collaborated with scholars based in United States, South Korea and Israel. Frequent co-authors include Naoki Abe, Grzegorz Świrszcz, Yan Liu, Saharon Rosset, Eunho Yang, Aleksandr Y. Aravkin, Alexandru Niculescu-Mizil, Lennart Ljung, James V. Burke and Prabhanjan Kambadur. Their work appears in journals such as Nature Communications, Bioinformatics and PLoS ONE.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.