Publications
Google Scholar Profile: https://scholar.google.com/citations?user=NB2B59cAAAAJ&hl=en
ResearchGate Profile: https://www.researchgate.net/profile/Farhad_Pourkamali-Anaraki
Preprints
The Effectiveness of Variational Autoencoders for Active Learning
F. Pourkamali-Anaraki and M. Wakin
Peer-reviewed Articles
Adaptive Data Compression for Classification Problems
F. Pourkamali-Anaraki and W. Bennette
IEEE Access
Published version (Open Access)
An Empirical Evaluation of the t-SNE Algorithm for Data Visualization in Structural Engineering
P. Hajibabaee, F. Pourkamali-Anaraki, M. Hariri-Ardebili
IEEE International Conference on Machine Learning and Applications (ICMLA)
to appear
Kernel Matrix Approximation on Class-Imbalanced Data With an Application to Scientific Simulation
P. Hajibabaee, F. Pourkamali-Anaraki, M. Hariri-Ardebili
IEEE Access, vol. 9, pp. 83579-83591, 2021
Published version (Open Access)
Towards Robust and Efficient Plane Detection from 3D Point Cloud
S. Sharif Mansouri, C. Kanellakis, F. Pourkamali-Anaraki, G. Nikolakopoulos
International Conference on Unmanned Aircraft Systems (ICUAS), to appear
Neural Networks and Imbalanced Learning for Data-Driven Scientific Computing with Uncertainties
F. Pourkamali-Anaraki and M. Hariri-Ardebili
IEEE Access, vol. 9, pp. 15334-15350, 2021
Published version (Open Access)
Scalable Spectral Clustering with Nystrom Approximation: Practical and Theoretical Aspects
F. Pourkamali-Anaraki
IEEE Open Journal of Signal Processing, vol. 1, pages 242-256, 2020
Published version (Open Access)
Kernel Ridge Regression Using Importance Sampling with Application to Seismic Response Prediction [Best Paper Award]
F. Pourkamali-Anaraki, M. Hariri-Ardebili, L. Morawiec
IEEE International Conference on Machine Learning and Applications (ICMLA), pages 505-512, 2020
A Unified NMPC Scheme for MAVs Navigation with 3D Collision Avoidance under Position Uncertainty
S. Sharif Mansouri, C. Kanellakis, B. Lindqvist, F. Pourkamali-Anaraki, A. Agha-mohammadi, J. Burdick, G. Nikolakopoulos
IEEE Robotics and Automation Letters (RA-L), vol. 5, no. 4, pages 5740-5747, 2020
Unsupervised Learning for Subterranean Junction Recognition Based on 2D Point Cloud
S. Sharif Mansouri, F. Pourkamali-Anaraki, M. Castano, A. Agha-mohammadi, J. Burdick, and G. Nikolakopoulos
28th Mediterranean Conference on Control and Automation (MED), pages 802-807, 2020
Instrumented Health Monitoring of an Earth Dam
S. Kolbadi, M. Hariri-Ardebili, M. Mirtaheri, and F. Pourkamali-Anaraki
Infrastructures, vol. 5, no. 3, page 26, 2020
Efficient Solvers for Sparse Subspace Clustering
F. Pourkamali-Anaraki, J. Folberth, and S. Becker
Signal Processing, vol. 172, page 107548, 2020
Uncertainty Quantification of Structural Systems with Subset of Data
M. Hariri-Ardebili, F. Pourkamali-Anaraki, and S. Sattar
17th World Conference on Earthquake Engineering, 17WCEE, 2020
Improved Fixed-Rank Nystrom Approximation via QR Decomposition: Practical and Theoretical Aspects
F. Pourkamali-Anaraki and S. Becker
Neurocomputing, vol. 363, pages 261-272, 2019
Large-Scale Sparse Subspace Clustering Using Landmarks
F. Pourkamali-Anaraki
IEEE Machine Learning for Signal Processing (MLSP) Workshop, pages 1-6, 2019
Matrix Completion for Cost Reduction in Finite Element Simulations Under Hybrid Uncertainties
M. Hariri-Ardebili and F. Pourkamali-Anaraki
Applied Mathematical Modeling, vol. 69, pages 164-180, 2019
Application of Response Surface Meta-model in Probabilistic Analysis of Concrete Dams
M. Hariri-Ardebili, M. Noori, F. Pourkamali-Anaraki, and S. Kolbadi
United States Society on Dams (USSD) Annual Conference & Exhibition, 2019
Support Vector Machine Based Reliability Analysis of Concrete Dams
M. Hariri-Ardebili and F. Pourkamali-Anaraki
Soil Dynamics and Earthquake Engineering, vol. 104, pages 276-295, 2018
Simplified Reliability Analysis of Multi Hazard Risk in Gravity Dams via Machine Learning Techniques
M. Hariri-Ardebili and F. Pourkamali-Anaraki
Archives of Civil and Mechanical Engineering, vol. 18, no. 2, pages 592-610, 2018
Randomized Clustered Nystrom for Large-Scale Kernel Machines
F. Pourkamali-Anaraki, S. Becker, and M. Wakin
Proceedings of the 32nd AAAI Conference on Artificial Intelligence, pages 3960-3967, 2018
Preconditioned Data Sparsification for Big Data with Applications to PCA and K-means
F. Pourkamali-Anaraki and S. Becker
IEEE Transactions on Information Theory, vol. 63, no. 5, pages 2954–2974, 2017
A Randomized Approach to Efficient Kernel Clustering
F. Pourkamali-Anaraki and S. Becker
IEEE Global Conference on Signal and Information Processing (GlobalSIP), pages 207-211, 2016
Estimation of the Sample Covariance Matrix from Compressive Measurements
F. Pourkamali-Anaraki
IET Signal Processing, vol. 10, no. 9, pages 1089-1095, 2016
Published version, arXiv version
Efficient Dictionary Learning via Very Sparse Random Projections
F. Pourkamali-Anaraki, S. Becker, and S. Hughes
Sampling Theory and Applications (SampTA), pages 478-482, 2015
Memory and Computation Efficient PCA via Very Sparse Random Projections
F. Pourkamali-Anaraki and S. Hughes
Proceedings of the 31st International Conference on Machine Learning (ICML), pages 1341-1349, 2014
Efficient Recovery of Principal Components from Compressive Measurements with Application to Gaussian Mixture Model Estimation
F. Pourkamali-Anaraki and S. Hughes
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pages 2332-2336, 2014
Kernel Compressive Sensing
F. Pourkamali-Anaraki and S. Hughes
IEEE International Conference on Image Processing (ICIP), pages 494-498, 2013
Compressive K-SVD
F. Pourkamali-Anaraki and S. Hughes
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pages 5469–5473, 2013