37 citations · 78 across the 7 of their papers we have counts for
4 papers · 1 filter
Low-Rank Compression of Pretrained Models via Randomized Subspace Iteration
Farhad Pourkamali-Anaraki
The massive scale of pretrained models has made efficient compression essential for practical deployment. Low-rank decomposition based on the singular value decomposition (SVD) pro…
An Empirical Evaluation of the t-SNE Algorithm for Data Visualization in Structural Engineering
Parisa Hajibabaee, Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili
A fundamental task in machine learning involves visualizing high-dimensional data sets that arise in high-impact application domains. When considering the context of large imbalanc…
Kernel Ridge Regression Using Importance Sampling with Application to Seismic Response Prediction
Farhad Pourkamali-Anaraki, Mohammad Amin Hariri-Ardebili, Lydia Morawiec
Scalable kernel methods, including kernel ridge regression, often rely on low-rank matrix approximations using the Nystrom method, which involves selecting landmark points from lar…
Scalable Spectral Clustering with Nystrom Approximation: Practical and Theoretical Aspects
Farhad Pourkamali-Anaraki
Spectral clustering techniques are valuable tools in signal processing and machine learning for partitioning complex data sets. The effectiveness of spectral clustering stems from…