Farhad Pourkamali-Anaraki

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 41

Top Topics

Scientific Computing

Kernel Ridge Regression

Subspace Clustering

Top Venues

Publications

Farhad Pourkamali-Anaraki, Tahamina Nasrin, Robert E. Jensen, Amy M. Peterson, Christopher J. Hansen
Adaptive Activation Functions for Predictive Modeling with Sparse Experimental Data. CoRR (2024)
Farhad Pourkamali-Anaraki, Jamal F. Husseini, Scott E. Stapleton
Probabilistic Neural Networks (PNNs) for Modeling Aleatoric Uncertainty in Scientific Machine Learning. CoRR (2024)
Farhad Pourkamali-Anaraki, Jamal F. Husseini, Evan J. Pineda, Brett A. Bednarcyk, Scott E. Stapleton
Two-Stage Surrogate Modeling for Data-Driven Design Optimization with Application to Composite Microstructure Generation. CoRR (2024)
Parisa Hajibabaee, Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili
Adaptive Conformal Prediction Intervals Using Data-Dependent Weights With Application to Seismic Response Prediction. IEEE Access 12 (2024)
Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili
Evaluating Regression Models with Partial Data: A Sampling Approach. CoDIT (2023)
Carol M. Kiekhaefer, Farhad Pourkamali-Anaraki
Advancing Precision Medicine: An Evaluative Study of Feature Selection Methods. ICMLA (2023)
Farhad Pourkamali-Anaraki, Tahamina Nasrin, Robert E. Jensen, Amy M. Peterson, Christopher J. Hansen
Evaluation of classification models in limited data scenarios with application to additive manufacturing. Eng. Appl. Artif. Intell. 126 (2023)
Mohammad Amin Hariri-Ardebili, Farhad Pourkamali-Anaraki
Structural uncertainty quantification with partial information. Expert Syst. Appl. 198 (2022)
Yasin Findik, Farhad Pourkamali-Anaraki
D-CBRS: Accounting for Intra-Class Diversity in Continual Learning. ICIP (2022)
Yasin Findik, Farhad Pourkamali-Anaraki
D-CBRS: Accounting For Intra-Class Diversity in Continual Learning. CoRR (2022)
Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili, Stephen Becker, Maziar Raissi
Call for Special Issue Papers: Big Scientific Data and Machine Learning in Science and Engineering: Deadline for Manuscript Submission: February 1, 2022. Big Data 9 (5) (2021)
Parisa Hajibabaee, Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili
An Empirical Evaluation of the t-SNE Algorithm for Data Visualization in Structural Engineering. CoRR (2021)
Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili, Stephen Becker, Maziar Raissi
Call for Special Issue Papers: Big Scientific Data and Machine Learning in Science and Engineering: Deadline for Manuscript Submission: February 1, 2022. Big Data 9 (4) (2021)
Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili
Neural Networks and Imbalanced Learning for Data-Driven Scientific Computing With Uncertainties. IEEE Access 9 (2021)
Parisa Hajibabaee, Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili
An Empirical Evaluation of the t-SNE Algorithm for Data Visualization in Structural Engineering. ICMLA (2021)
Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili, Stephen Becker, Maziar Raissi
Call for Special Issue Papers: Big Scientific Data and Machine Learning in Science and Engineering: Deadline for Manuscript Submission: February 1, 2022. Big Data 9 (6) (2021)
Farhad Pourkamali-Anaraki, Walter D. Bennette
Adaptive Data Compression for Classification Problems. IEEE Access 9 (2021)
Parisa Hajibabaee, Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili
Kernel Matrix Approximation on Class-Imbalanced Data With an Application to Scientific Simulation. IEEE Access 9 (2021)
Sina Sharif Mansouri, Christoforos Kanellakis, Björn Lindqvist, Farhad Pourkamali-Anaraki, Ali-akbar Agha-mohammadi, Joel Burdick, George Nikolakopoulos
A Unified NMPC Scheme for MAVs Navigation With 3D Collision Avoidance Under Position Uncertainty. IEEE Robotics Autom. Lett. 5 (4) (2020)
Sina Sharif Mansouri, Farhad Pourkamali-Anaraki, Miguel Castano Arranz, Ali-akbar Agha-mohammadi, Joel Burdick, George Nikolakopoulos
Unsupervised Learning for Subterranean Junction Recognition Based on 2D Point Cloud. CoRR (2020)
Sina Sharif Mansouri, Christoforos Kanellakis, Björn Lindqvist, Farhad Pourkamali-Anaraki, Ali-akbar Agha-mohammadi, Joel Burdick, George Nikolakopoulos
A Unified NMPC Scheme for MAVs Navigation with 3D Collision Avoidance under Position Uncertainty. CoRR (2020)
Farhad Pourkamali-Anaraki, James Folberth, Stephen Becker
Efficient Solvers for Sparse Subspace Clustering. Signal Process. 172 (2020)
Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili, Lydia Morawiec
Kernel Ridge Regression Using Importance Sampling with Application to Seismic Response Prediction. CoRR (2020)
Mohammad Amin Hariri-Ardebili, Farhad Pourkamali-Anaraki, Siamak Sattar
Uncertainty Quantification of Structural Systems with Subset of Data. CoRR (2020)
Farhad Pourkamali-Anaraki
Scalable Spectral Clustering with Nystrom Approximation: Practical and Theoretical Aspects. CoRR (2020)
Sina Sharif Mansouri, Farhad Pourkamali-Anaraki, Miguel Castano, Ali-Akbar Agha-Mohammadi, Joel Burdick, George Nikolakopoulos
Unsupervised Learning for Subterranean Junction Recognition Based on 2D Point Cloud. MED (2020)
Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili, Lydia Morawiec
Kernel Ridge Regression Using Importance Sampling with Application to Seismic Response Prediction. ICMLA (2020)
Farhad Pourkamali-Anaraki
Large-Scale Sparse Subspace Clustering Using Landmarks. CoRR (2019)
Farhad Pourkamali-Anaraki, Stephen Becker
Improved fixed-rank Nyström approximation via QR decomposition: Practical and theoretical aspects. Neurocomputing 363 (2019)
Farhad Pourkamali-Anaraki, Michael B. Wakin
The Effectiveness of Variational Autoencoders for Active Learning. CoRR (2019)
Farhad Pourkamali-Anaraki
Large-Scale Sparse Subspace Clustering Using Landmarks. MLSP (2019)
Farhad Pourkamali-Anaraki, Stephen Becker, Michael B. Wakin
Randomized Clustered Nystrom for Large-Scale Kernel Machines. AAAI (2018)
Farhad Pourkamali-Anaraki, Stephen Becker
Efficient Solvers for Sparse Subspace Clustering. CoRR (2018)
Farhad Pourkamali-Anaraki, Stephen Becker
Improved Fixed-Rank Nyström Approximation via QR Decomposition: Practical and Theoretical Aspects. CoRR (2017)
Farhad Pourkamali-Anaraki, Stephen Becker
Preconditioned Data Sparsification for Big Data With Applications to PCA and K-Means. IEEE Trans. Inf. Theory 63 (5) (2017)
Farhad Pourkamali-Anaraki, Stephen Becker
A randomized approach to efficient kernel clustering. GlobalSIP (2016)
Farhad Pourkamali-Anaraki, Stephen Becker
Randomized Clustered Nystrom for Large-Scale Kernel Machines. CoRR (2016)
Farhad Pourkamali-Anaraki
Estimation of the sample covariance matrix from compressive measurements. IET Signal Process. 10 (9) (2016)
Farhad Pourkamali-Anaraki
Estimation of the sample covariance matrix from compressive measurements. CoRR (2015)
Farhad Pourkamali-Anaraki, Stephen Becker, Shannon M. Hughes
Efficient Dictionary Learning via Very Sparse Random Projections. CoRR (2015)
Farhad Pourkamali-Anaraki, Stephen Becker
Preconditioned Data Sparsification for Big Data with Applications to PCA and K-means. CoRR (2015)
Farhad Pourkamali-Anaraki, Shannon M. Hughes
Memory and Computation Efficient PCA via Very Sparse Random Projections. ICML (2014)
Farhad Pourkamali-Anaraki, Shannon M. Hughes
Efficient recovery of principal components from compressive measurements with application to Gaussian mixture model estimation. ICASSP (2014)
Farhad Pourkamali-Anaraki, Shannon M. Hughes
Compressive K-SVD. ICASSP (2013)
Farhad Pourkamali-Anaraki, Shannon M. Hughes
Kernel compressive sensing. ICIP (2013)