Farhad Pourkamali-Anaraki

Maziar Raissi

Big Data, 2021

Adaptive Data Compression for Classification Problems.

[BibT_eX]

[DOI]

Walter D. Bennette

IEEE Access, 2021

Neural Networks and Imbalanced Learning for Data-Driven Scientific Computing With Uncertainties.

[BibT_eX]

[DOI]

IEEE Access, 2021

Kernel Matrix Approximation on Class-Imbalanced Data With an Application to Scientific Simulation.

[BibT_eX]

[DOI]

Parisa Hajibabaee

IEEE Access, 2021

An Empirical Evaluation of the t-SNE Algorithm for Data Visualization in Structural Engineering.

[BibT_eX]

[DOI]

Parisa Hajibabaee

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

2020

Efficient Solvers for Sparse Subspace Clustering.

[BibT_eX]

[DOI]

James Folberth

Signal Process., 2020

A Unified NMPC Scheme for MAVs Navigation With 3D Collision Avoidance Under Position Uncertainty.

[BibT_eX]

[DOI]

Sina Sharif Mansouri

Christoforos Kanellakis

Björn Lindqvist

Ali-akbar Agha-mohammadi

Joel Burdick

George Nikolakopoulos

IEEE Robotics Autom. Lett., 2020

Uncertainty Quantification of Structural Systems with Subset of Data.

[BibT_eX]

[DOI]

Siamak Sattar

CoRR, 2020

Scalable Spectral Clustering with Nystrom Approximation: Practical and Theoretical Aspects.

[BibT_eX]

[DOI]

CoRR, 2020

Unsupervised Learning for Subterranean Junction Recognition Based on 2D Point Cloud.

[BibT_eX]

[DOI]

Sina Sharif Mansouri

Miguel Castano

Ali-Akbar Agha-Mohammadi

Joel Burdick

George Nikolakopoulos

Proceedings of the 28th Mediterranean Conference on Control and Automation, 2020

Kernel Ridge Regression Using Importance Sampling with Application to Seismic Response Prediction.

[BibT_eX]

[DOI]

Lydia Morawiec

Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020

2019

Improved fixed-rank Nyström approximation via QR decomposition: Practical and theoretical aspects.

[BibT_eX]

[DOI]

Neurocomputing, 2019

The Effectiveness of Variational Autoencoders for Active Learning.

[BibT_eX]

[DOI]

Michael B. Wakin

CoRR, 2019

Large-Scale Sparse Subspace Clustering Using Landmarks.

[BibT_eX]

[DOI]

Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

2018

Efficient Solvers for Sparse Subspace Clustering.

[BibT_eX]

[DOI]

CoRR, 2018

Randomized Clustered Nystrom for Large-Scale Kernel Machines.

[BibT_eX]

[DOI]

Michael B. Wakin

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Preconditioned Data Sparsification for Big Data With Applications to PCA and K-Means.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2017

2016

Estimation of the sample covariance matrix from compressive measurements.

[BibT_eX]

[DOI]

IET Signal Process., 2016

Randomized Clustered Nystrom for Large-Scale Kernel Machines.

[BibT_eX]

[DOI]

CoRR, 2016

A randomized approach to efficient kernel clustering.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

2015

Efficient Dictionary Learning via Very Sparse Random Projections.

[BibT_eX]

[DOI]

CoRR, 2015

2014

Memory and Computation Efficient PCA via Very Sparse Random Projections.

[BibT_eX]

[DOI]

Proceedings of the 31th International Conference on Machine Learning, 2014

Efficient recovery of principal components from compressive measurements with application to Gaussian mixture model estimation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2014

2013

Kernel compressive sensing.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Image Processing, 2013

Compressive K-SVD.

[BibT_eX]

[DOI]