| Preconditioned Data Sparsification for Big Data with Applications to PCA and K-means F Pourkamali-Anaraki, S Becker IEEE Transactions on Information Theory, 2017 | 58 | 2017 |
| Memory and computation efficient PCA via very sparse random projections FP Anaraki, S Hughes International Conference on Machine Learning, 1341-1349, 2014 | 38 | 2014 |
| Support vector machine based reliability analysis of concrete dams MA Hariri-Ardebili, F Pourkamali-Anaraki Soil Dynamics and Earthquake Engineering 104, 276-295, 2018 | 35 | 2018 |
| Compressive k-svd FP Anaraki, SM Hughes 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013 | 31 | 2013 |
| Simplified reliability analysis of multi hazard risk in gravity dams via machine learning techniques MA Hariri-Ardebili, F Pourkamali-Anaraki Archives of Civil and Mechanical Engineering 18, 592-610, 2018 | 20 | 2018 |
| Randomized clustered nystrom for large-scale kernel machines F Pourkamali-Anaraki, S Becker, M Wakin Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 20 | 2018 |
| Estimation of the sample covariance matrix from compressive measurements F Pourkamali-Anaraki IET Signal Processing 10 (9), 1089-1095, 2016 | 20 | 2016 |
| Kernel Compressive Sensing FP Anaraki, SM Hughes Image Processing (ICIP), 2013 20th IEEE International Conference on, 494-498, 2013 | 18 | 2013 |
| Efficient dictionary learning via very sparse random projections F Pourkamali-Anaraki, S Becker, SM Hughes 2015 International Conference on Sampling Theory and Applications (SampTA …, 2015 | 17 | 2015 |
| Improved fixed-rank Nyström approximation via QR decomposition: Practical and theoretical aspects F Pourkamali-Anaraki, S Becker Neurocomputing 363, 261-272, 2019 | 13 | 2019 |
| Efficient solvers for sparse subspace clustering F Pourkamali-Anaraki, J Folberth, S Becker arXiv preprint arXiv:1804.06291, 2018 | 13 | 2018 |
| Efficient Recovery of Principal Components from Compressive Measurements with Application to Gaussian Mixture Model Estimation F Pourkamali Anaraki, SM Hughes Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International …, 2014 | 9* | 2014 |
| A randomized approach to efficient kernel clustering F Pourkamali-Anaraki, S Becker Signal and Information Processing (GlobalSIP), 2016 IEEE Global Conference …, 2016 | 8 | 2016 |
| Large-scale sparse subspace clustering using landmarks F Pourkamali-Anaraki 2019 IEEE 29th International Workshop on Machine Learning for Signal …, 2019 | 5 | 2019 |
| Matrix completion for cost reduction in finite element simulations under hybrid uncertainties MA Hariri-Ardebili, F Pourkamali-Anaraki Applied Mathematical Modelling 69, 164-180, 2019 | 4 | 2019 |
| Instrumented Health Monitoring of an Earth Dam SM Seyed-Kolbadi, MA Hariri-Ardebili, M Mirtaheri, F Pourkamali-Anaraki Infrastructures 5 (3), 26, 2020 | 2 | 2020 |
| A unified nmpc scheme for mavs navigation with 3d collision avoidance under position uncertainty SS Mansouri, C Kanellakis, B Lindqvist, F Pourkamali-Anaraki, ... IEEE Robotics and Automation Letters 5 (4), 5740-5747, 2020 | 1 | 2020 |
| The Effectiveness of Variational Autoencoders for Active Learning F Pourkamali-Anaraki, MB Wakin arXiv preprint arXiv:1911.07716, 2019 | 1 | 2019 |
| Scalable Spectral Clustering With Nyström Approximation: Practical and Theoretical Aspects F Pourkamali-Anaraki IEEE Open Journal of Signal Processing 1, 242-256, 2020 | | 2020 |
| Kernel Ridge Regression Using Importance Sampling with Application to Seismic Response Prediction F Pourkamali-Anaraki, MA Hariri-Ardebili, L Morawiec arXiv preprint arXiv:2009.09136, 2020 | | 2020 |
Stephen BeckerAssistant Professor at University of ColoradoVerified email at colorado.edu
