An algorithm for the principal component analysis of large data sets

30 July 2010

Papers citing "An algorithm for the principal component analysis of large data sets"

42 / 42 papers shown

Title
Shallow Recurrent Decoder for Reduced Order Modeling of Plasma Dynamics J. Nathan Kutz M. Reza Farbod Faraji A. Knoll AI4CE 21 9 0 20 May 2024
On the Noise Sensitivity of the Randomized SVD Elad Romanov 19 0 0 27 May 2023
Deep Learning Methods for Partial Differential Equations and Related Parameter Identification Problems Derick Nganyu Tanyu Jianfeng Ning Tom Freudenberg Nick Heilenkötter A. Rademacher U. Iben Peter Maass AI4CE 20 34 0 06 Dec 2022
Improved analysis of randomized SVD for top-eigenvector approximation Ruo-Chun Tzeng Po-An Wang Florian Adriaens A. Gionis Chi-Jen Lu 11 1 0 16 Feb 2022
Non-Parametric Estimation of Manifolds from Noisy Data Yariv Aizenbud B. Sober 24 19 0 11 May 2021
Spatially Coherent Clustering Based on Orthogonal Nonnegative Matrix Factorization Pascal Fernsel 14 5 0 25 Apr 2021
Quantum algorithms for SVD-based data representation and analysis Armando Bellante Alessandro Luongo S. Zanero 13 8 0 19 Apr 2021
Sparse sketches with small inversion bias Michal Derezinski Zhenyu Liao Edgar Dobriban Michael W. Mahoney 15 21 0 21 Nov 2020
Generalized Matrix Factorization: efficient algorithms for fitting generalized linear latent variable models to large data arrays L. Kidzinski Francis K. C. Hui D. Warton Trevor Hastie 17 11 0 06 Oct 2020
A Perturbation-Based Kernel Approximation Framework Roy Mitz Y. Shkolnisky 9 3 0 07 Sep 2020
Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning Steven L. Brunton J. Nathan Kutz Krithika Manohar Aleksandr Aravkin K. Morgansen ... J. Buttrick Jeffrey Poskin Agnes Blom-Schieber Thomas Hogan Darren McDonald AI4CE 10 122 0 24 Aug 2020
How to reduce dimension with PCA and random projections? Fan Yang Sifan Liu Edgar Dobriban David P. Woodruff 22 28 0 01 May 2020
Error Estimation for Sketched SVD via the Bootstrap Miles E. Lopes N. Benjamin Erichson Michael W. Mahoney 6 11 0 10 Mar 2020
Computing rank-revealing factorizations of matrices stored out-of-core N. Heavner P. Martinsson Gregorio Quintana-Ortí 62 0 0 17 Feb 2020
On-the-fly Global Embeddings Using Random Projections for Extreme Multi-label Classification Yashaswi Verma 14 0 0 17 Dec 2019
ROIPCA: An online memory-restricted PCA algorithm based on rank-one updates Roy Mitz Y. Shkolnisky 9 0 0 25 Nov 2019
Tutorial: Complexity analysis of Singular Value Decomposition and its variants Xiaocan Li Shuo Wang Yinghao Cai 6 0 0 28 Jun 2019
Identification of synoptic weather types over Taiwan area with multiple classifiers S. Su Jung‐Lien Chu Ting-Shuo Yo Lee-Yaw Lin 12 13 0 21 May 2019
Projecting "better than randomly": How to reduce the dimensionality of very large datasets in a way that outperforms random projections M. Wojnowicz Di Zhang Glenn Chisholm Xuan Zhao Matt Wolff 16 11 0 03 Jan 2019
Random Projection in Deep Neural Networks P. Wójcik 4 5 0 22 Dec 2018
End-to-end Image Captioning Exploits Multimodal Distributional Similarity Pranava Madhyastha Josiah Wang Lucia Specia CoGe 20 7 0 11 Sep 2018
A high-bias, low-variance introduction to Machine Learning for physicists Pankaj Mehta Marin Bukov Ching-Hao Wang A. G. Day C. Richardson Charles K. Fisher D. Schwab AI4CE 11 866 0 23 Mar 2018
Diffusion Maps meet Nyström N. Benjamin Erichson L. Mathelin Steven L. Brunton J. Nathan Kutz 25 4 0 23 Feb 2018
Efficient Algorithms for t-distributed Stochastic Neighborhood Embedding G. Linderman M. Rachh J. Hoskins Stefan Steinerberger Y. Kluger 22 430 0 25 Dec 2017
Lazy stochastic principal component analysis M. Wojnowicz Dinh Nguyen Li Li Xuan Zhao 25 2 0 21 Sep 2017
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data J. Tropp A. Yurtsever Madeleine Udell V. Cevher 23 79 0 18 Jun 2017
Spatial Random Sampling: A Structure-Preserving Data Sketching Tool M. Rahmani George K. Atia 17 13 0 09 May 2017
Single-Pass PCA of Large High-Dimensional Data Wenjian Yu Yu Gu Jun Yu Li Shenghua Liu Yaohang Li 14 45 0 25 Apr 2017
Integrating multiple random sketches for singular value decomposition Ting-Li Chen Dawei Chang Su‐Yun Huang Hung Chen Chienyao Lin Weichung Wang 30 12 0 29 Aug 2016
Randomized Matrix Decompositions using R N. Benjamin Erichson S. Voronin Steven L. Brunton J. Nathan Kutz 20 144 0 06 Aug 2016
A Communication Efficient and Scalable Distributed Data Mining for the Astronomical Data Aruna Govada S. K. Sahay 10 3 0 23 Jun 2016
AVEC 2016 - Depression, Mood, and Emotion Recognition Workshop and Challenge M. Valstar Jonathan Gratch Bjorn Schuller F. Ringeval D. Lalanne M. Torres Stefan Scherer Giota Stratou R. Cowie M. Pantic 19 596 0 05 May 2016
Nonparametric Canonical Correlation Analysis T. Michaeli Weiran Wang Karen Livescu 26 85 0 16 Nov 2015
Large-Scale Approximate Kernel Canonical Correlation Analysis Weiran Wang Karen Livescu 19 54 0 15 Nov 2015
Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition Cameron Musco Christopher Musco 27 20 0 21 Apr 2015
High Dimensional Low Rank plus Sparse Matrix Decomposition M. Rahmani George K. Atia 78 77 0 01 Feb 2015
Large scale canonical correlation analysis with iterative least squares Y. Lu Dean Phillips Foster 42 55 0 16 Jul 2014
Fast Ridge Regression with Randomized Principal Component Analysis and Gradient Descent Y. Lu Dean Phillips Foster ODL 41 10 0 15 May 2014
Greedy Column Subset Selection for Large-scale Data Sets Ahmed K. Farahat Ahmed Elgohary A. Ghodsi M. Kamel 48 63 0 24 Dec 2013
Combining Structured and Unstructured Randomness in Large Scale PCA Nikos Karampatziakis Paul Mineiro 49 2 0 23 Oct 2013
An Image-Based Fluid Surface Pattern Model Mauro de Amorim R. Fabbri Lucia Maria dos Santos Pinto F. D. M. Neto DiffM 42 0 0 30 Sep 2013
Rotationally Invariant Image Representation for Viewing Direction Classification in Cryo-EM Zhizhen Zhao A. Singer 51 117 0 29 Sep 2013