| Randomized LU decomposition G Shabat, Y Shmueli, Y Aizenbud, A Averbuch Applied and Computational Harmonic Analysis 44 (2), 246-272, 2018 | 49 | 2018 |
| Impact of healthcare worker shift scheduling on workforce preservation during the COVID-19 pandemic DM Kluger, Y Aizenbud, A Jaffe, F Parisi, L Aizenbud, E Minsky-Fenick, ... Infection Control & Hospital Epidemiology 41 (12), 1443-1445, 2020 | 47 | 2020 |
| Approximation of functions over manifolds: A moving least-squares approach B Sober, Y Aizenbud, D Levin Journal of Computational and Applied Mathematics, 2020 | 25 | 2020 |
| PCA-based out-of-sample extension for dimensionality reduction Y Aizenbud, A Bermanis, A Averbuch arXiv preprint arXiv:1511.00831, 2015 | 21 | 2015 |
| Matrix decompositions using sub-Gaussian random matrices Y Aizenbud, A Averbuch Information and Inference: A Journal of the IMA 8 (3), 445-469, 2019 | 18 | 2019 |
| Randomized LU decomposition using sparse projections Y Aizenbud, G Shabat, A Averbuch Computers & Mathematics with Applications 72 (9), 2525-2534, 2016 | 17 | 2016 |
| Multi-view kernel consensus for data analysis M Salhov, O Lindenbaum, Y Aizenbud, A Silberschatz, Y Shkolnisky, ... Applied and Computational Harmonic Analysis, 2019 | 16* | 2019 |
| Non-parametric estimation of manifolds from noisy data Y Aizenbud, B Sober arXiv preprint arXiv:2105.04754, 2021 | 13 | 2021 |
| A max-cut approach to heterogeneity in cryo-electron microscopy Y Aizenbud, Y Shkolnisky Journal of Mathematical Analysis and Applications 479 (1), 1004-1029, 2019 | 10 | 2019 |
| Rank-one multi-reference factor analysis Y Aizenbud, B Landa, Y Shkolnisky Statistics and Computing 31, 1-31, 2021 | 9 | 2021 |
| Spectral Neighbor Joining for Reconstruction of Latent Tree Models A Jaffe, N Amsel, Y Aizenbud, B Nadler, JT Chang, Y Kluger SIAM Journal on Mathematics of Data Science 3 (1), 113-141, 2021 | 5 | 2021 |
| Approximating the span of principal components via iterative least-squares Y Aizenbud, B Sober arXiv preprint arXiv:1907.12159, 2019 | 4 | 2019 |
| Diffusion-Based Methods for Estimating Curvature in Data D Bhaskar, K MacDonald, D Thomas, S Zhao, K You, J Paige, Y Aizenbud, ... ICLR 2022 Workshop on Geometrical and Topological Representation Learning, 2022 | 2 | 2022 |
| Probabilistic Robust Autoencoders for Anomaly Detection Y Aizenbud, O Lindenbaum, Y Kluger arXiv e-prints, arXiv: 2110.00494, 2021 | 2 | 2021 |
| Germline genetic variants are associated with development of insulin-dependent diabetes in cancer patients treated with immune checkpoint inhibitors JI Caulfield, L Aizenbud, AL Perdigoto, E Meffre, L Jilaveanu, ... Journal for Immunotherapy of Cancer 11 (3), 2023 | 1 | 2023 |
| Convergence rates of vector-valued local polynomial regression Y Aizenbud, B Sober arXiv preprint arXiv:2107.05852, 2021 | 1 | 2021 |
| Approximating the span of principal components via iterative least-squares Y Aizenbud, B Sober Applied and Computational Harmonic Analysis 63, 84-92, 2023 | | 2023 |
| Probabilistic Robust Autoencoders for Outlier Detection O Lindenbaum, Y Aizenbud, Y Kluger arXiv preprint arXiv:2110.00494, 2021 | | 2021 |
| Differentiable Unsupervised Feature Selection Y Aizenbud, O Lindenbaum, Y Kluger arXiv preprint arXiv:2110.00494, 2021 | | 2021 |
| Spectral Top-Down Recovery of Latent Tree Models Y Aizenbud, A Jaffe, M Wang, A Hu, N Amsel, B Nadler, JT Chang, ... arXiv preprint arXiv:2102.13276, 2021 | | 2021 |
Amir AverbuchProfessor of Computer Science, Tel-Aviv UniversityVerified email at math.tau.ac.il
