Farhad Pourkamali-Anaraki
Farhad Pourkamali-Anaraki
Verified email at uml.edu - Homepage
Title
Cited by
Cited by
Year
Preconditioned Data Sparsification for Big Data with Applications to PCA and K-means
F Pourkamali-Anaraki, S Becker
IEEE Transactions on Information Theory, 2017
582017
Memory and computation efficient PCA via very sparse random projections
FP Anaraki, S Hughes
International Conference on Machine Learning, 1341-1349, 2014
382014
Support vector machine based reliability analysis of concrete dams
MA Hariri-Ardebili, F Pourkamali-Anaraki
Soil Dynamics and Earthquake Engineering 104, 276-295, 2018
352018
Compressive k-svd
FP Anaraki, SM Hughes
2013 IEEE International Conference on Acoustics, Speech and Signalá…, 2013
312013
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
202018
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
202018
Estimation of the sample covariance matrix from compressive measurements
F Pourkamali-Anaraki
IET Signal Processing 10 (9), 1089-1095, 2016
202016
Kernel Compressive Sensing
FP Anaraki, SM Hughes
Image Processing (ICIP), 2013 20th IEEE International Conference on, 494-498, 2013
182013
Efficient dictionary learning via very sparse random projections
F Pourkamali-Anaraki, S Becker, SM Hughes
2015 International Conference on Sampling Theory and Applications (SampTAá…, 2015
172015
Improved fixed-rank Nystr÷m approximation via QR decomposition: Practical and theoretical aspects
F Pourkamali-Anaraki, S Becker
Neurocomputing 363, 261-272, 2019
132019
Efficient solvers for sparse subspace clustering
F Pourkamali-Anaraki, J Folberth, S Becker
arXiv preprint arXiv:1804.06291, 2018
132018
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 Internationalá…, 2014
9*2014
A randomized approach to efficient kernel clustering
F Pourkamali-Anaraki, S Becker
Signal and Information Processing (GlobalSIP), 2016 IEEE Global Conferenceá…, 2016
82016
Large-scale sparse subspace clustering using landmarks
F Pourkamali-Anaraki
2019 IEEE 29th International Workshop on Machine Learning for Signalá…, 2019
52019
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
42019
Instrumented Health Monitoring of an Earth Dam
SM Seyed-Kolbadi, MA Hariri-Ardebili, M Mirtaheri, F Pourkamali-Anaraki
Infrastructures 5 (3), 26, 2020
22020
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
12020
The Effectiveness of Variational Autoencoders for Active Learning
F Pourkamali-Anaraki, MB Wakin
arXiv preprint arXiv:1911.07716, 2019
12019
Scalable Spectral Clustering With Nystr÷m 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
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Articles 1–20