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ORCIDMichael Kirby
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- Justice Michael Kirby
- Michael J. Kirby
- Michael J. L. Kirby
- Robert M. Kirby
![[0000-0001-5712-4141]](https://dblp.org/img/orcid-mark.12x12.png "0000-0001-5712-4141")
(aka: Robert Michael Kirby, Mike Kirby) — University of Utah, Salt Lake City, UT, USA
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2020 – today
- 2024
[j23]Yajing Liu, Turgay Caglar, Chris Peterson, Michael Kirby:
Integrating geometries of ReLU feedforward neural networks. Frontiers Big Data 6 (2024)- [j22]Tomojit Ghosh, Michael Kirby:
Correction to: Nonlinear feature selection using sparsity-promoted centroid-encoder. Neural Comput. Appl. 36(1): 521 (2024) - [j21]Tomojit Ghosh, Michael Kirby:
Linear Centroid Encoder for Supervised Principal Component Analysis. Pattern Recognit. 155: 110634 (2024) - [c36]Karim Salta, Tomojit Ghosh, Michael Kirby:
A Multi-domain Multi-task Approach for Feature Selection from Bulk RNA Datasets. ICCS (4) 2024: 31-45 - [i27]Karim Salta, Tomojit Ghosh, Michael Kirby:
A Multi-Domain Multi-Task Approach for Feature Selection from Bulk RNA Datasets. CoRR abs/2405.02534 (2024) - [i26]Ugochukwu O. Ugwu, Michael Kirby:
Optimizing Sparse Generalized Singular Vectors for Feature Selection in Proximal Support Vector Machines with Application to Breast and Ovarian Cancer Detection. CoRR abs/2410.03978 (2024) - [i25]Mayla R. Boguslav, Adam Kiehl, David Kott, G. Joseph Strecker, Tracy Webb, Nadia Saklou, Terri Ward, Michael Kirby:
Fine-tuning foundational models to code diagnoses from veterinary health records. CoRR abs/2410.15186 (2024) - 2023
- [j20]Huma Jamil, Yajing Liu, Nathaniel Blanchard, Michael Kirby, Chris Peterson:
Leveraging linear mapping for model-agnostic adversarial defense. Frontiers Comput. Sci. 5 (2023) - [j19]William Pickard, Kelsey Sikes, Huma Jamil, Nicholas Chaffee, Nathaniel Blanchard, Michael Kirby, Chris Peterson:
Exploring fMRI RDMs: enhancing model robustness through neurobiological data. Frontiers Comput. Sci. 5 (2023) - [j18]Karim Karimov, Michael Kirby, Chris Peterson:
An algorithm for computing Schubert varieties of best fit with applications. Frontiers Artif. Intell. 6 (2023) - [j17]Benjamin Sattelberg, Renzo Cavalieri, Michael Kirby, Chris Peterson, J. Ross Beveridge:
Locally linear attributes of ReLU neural networks. Frontiers Artif. Intell. 6 (2023) - [j16]Tomojit Ghosh, Michael Kirby:
Nonlinear feature selection using sparsity-promoted centroid-encoder. Neural Comput. Appl. 35(29): 21883-21902 (2023) - [c35]Tomojit Ghosh, Karim Karimov, Michael Kirby:
Sparse Linear Centroid-Encoder: A Biomarker Selection tool for High Dimensional Biological Data. BIBM 2023: 3012-3019 - [c34]Tomojit Ghosh, Michael Kirby:
Feature Selection on Big Data using Masked Sparse Bottleneck Centroid-Encoder. IEEE Big Data 2023: 646-655 - [c33]Huma Jamil, Yajing Liu, Turgay Caglar, Christina M. Cole, Nathaniel Blanchard, Christopher Peterson, Michael Kirby:
Hamming Similarity and Graph Laplacians for Class Partitioning and Adversarial Image Detection. CVPR Workshops 2023: 590-599 - [c32]Yajing Liu, Christina M. Cole, Chris Peterson, Michael Kirby:
ReLU Neural Networks, Polyhedral Decompositions, and Persistent Homology. TAG-ML 2023: 455-468 - [i24]Huma Jamil, Yajing Liu, Turgay Caglar, Christina M. Cole, Nathaniel Blanchard, Christopher Peterson, Michael Kirby:
Hamming Similarity and Graph Laplacians for Class Partitioning and Adversarial Image Detection. CoRR abs/2305.01808 (2023) - [i23]Tomojit Ghosh, Michael Kirby:
Yet Another Algorithm for Supervised Principal Component Analysis: Supervised Linear Centroid-Encoder. CoRR abs/2306.04622 (2023) - [i22]Tomojit Ghosh, Michael Kirby:
Feature Selection using Sparse Adaptive Bottleneck Centroid-Encoder. CoRR abs/2306.04795 (2023) - [i21]Tomojit Ghosh, Michael Kirby, Karim Karimov:
Sparse Linear Centroid-Encoder: A Convex Method for Feature Selection. CoRR abs/2306.04824 (2023) - [i20]Yajing Liu, Christina M. Cole, Chris Peterson, Michael Kirby:
ReLU Neural Networks, Polyhedral Decompositions, and Persistent Homolog. CoRR abs/2306.17418 (2023) - 2022
- [j15]Tomojit Ghosh, Michael Kirby:
Supervised Dimensionality Reduction and Visualization using Centroid-Encoder. J. Mach. Learn. Res. 23: 20:1-20:34 (2022) - [j14]Xiaofeng Ma, Michael Kirby, Chris Peterson:
Self-organizing mappings on the flag manifold with applications to hyper-spectral image data analysis. Neural Comput. Appl. 34(1): 39-49 (2022) - [c31]Huma Jamil, Yajing Liu, Christina M. Cole, Nathaniel Blanchard, Emily J. King, Michael Kirby, Christopher Peterson:
Dual Graphs of Polyhedral Decompositions for the Detection of Adversarial Attacks. IEEE Big Data 2022: 2913-2921 - [c30]Nathan Mankovich, Emily J. King, Chris Peterson, Michael Kirby:
The Flag Median and FlagIRLS. CVPR 2022: 10329-10337 - [i19]Tomojit Ghosh, Michael Kirby:
Sparse Centroid-Encoder: A Nonlinear Model for Feature Selection. CoRR abs/2201.12910 (2022) - [i18]Nathan Mankovich, Emily J. King, Chris Peterson, Michael Kirby:
The Flag Median and FlagIRLS. CoRR abs/2203.04437 (2022) - [i17]Kenneth Herner, Michael Kirby, Steven Timm:
Towards an HPC Complementary Computing Facility. CoRR abs/2203.08861 (2022) - [i16]Huma Jamil, Yajing Liu, Christina M. Cole, Nathaniel Blanchard, Emily J. King, Michael Kirby, Christopher Peterson:
Dual Graphs of Polyhedral Decompositions for the Detection of Adversarial Attacks. CoRR abs/2211.13305 (2022) - 2021
- [c29]Xiaofeng Ma, Michael Kirby, Chris Peterson:
The Flag Manifold as a Tool for Analyzing and Comparing Sets of Data Sets. ICCVW 2021: 4168-4177 - 2020
- [j13]Xiaofeng Ma, Michael Kirby, Chris Peterson, Louis Scharf:
Self-organizing mappings on the Grassmannian with applications to data analysis in high dimensions. Neural Comput. Appl. 32(24): 18243-18254 (2020) - [c28]Manuchehr Aminian, Eric Kehoe, Xiaofeng Ma, Amy Peterson, Michael Kirby:
Exploring Musical Structure Using Tonnetz Lattice Geometry and LSTMs. ICCS (2) 2020: 414-424 - [i15]Tomojit Ghosh, Michael Kirby:
Supervised Dimensionality Reduction and Visualization using Centroid-encoder. CoRR abs/2002.11934 (2020) - [i14]Xiaofeng Ma, Michael Kirby, Chris Peterson:
The flag manifold as a tool for analyzing and comparing data sets. CoRR abs/2006.14086 (2020) - [i13]Benjamin Sattelberg, Renzo Cavalieri, Michael Kirby, Chris Peterson, J. Ross Beveridge:
Locally Linear Attributes of ReLU Neural Networks. CoRR abs/2012.01940 (2020)
2010 – 2019
- 2019
- [j12]Xiaofeng Ma, Manuchehr Aminian, Michael Kirby:
Error-adaptive modeling of streaming time-series data using radial basis functions. J. Comput. Appl. Math. 362: 295-308 (2019) - [j11]Robert T. Arn, Pradyumna Narayana, Tegan Emerson, Bruce A. Draper, Michael Kirby, Chris Peterson:
Motion Segmentation via Generalized Curvatures. IEEE Trans. Pattern Anal. Mach. Intell. 41(12): 2919-2932 (2019) - [c27]Xiaofeng Ma, Michael Kirby, Chris Peterson:
Self-Organizing Mappings on the Flag Manifold. WSOM+ 2019: 13-22 - [c26]Henry Kvinge, Michael Kirby, Chris Peterson, Chad Eitel, Tod Clapp:
A Walk Through Spectral Bands: Using Virtual Reality to Better Visualize Hyperspectral Data. WSOM+ 2019: 160-165 - [c25]Shannon Stiverson, Michael Kirby, Chris Peterson:
Subspace Quantization on the Grassmannian. WSOM+ 2019: 251-260 - [i12]Elin Farnell, Henry Kvinge, John P. Dixon, Julia R. Dupuis, Michael Kirby, Chris Peterson, Elizabeth C. Schundler, Christian W. Smith:
A data-driven approach to sampling matrix selection for compressive sensing. CoRR abs/1906.08869 (2019) - [i11]Henry Kvinge, Elin Farnell, Julia R. Dupuis, Michael Kirby, Chris Peterson, Elizabeth C. Schundler:
More chemical detection through less sampling: amplifying chemical signals in hyperspectral data cubes through compressive sensing. CoRR abs/1906.11818 (2019) - 2018
- [c24]Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson:
Monitoring the shape of weather, soundscapes, and dynamical systems: a new statistic for dimension-driven data analysis on large datasets. IEEE BigData 2018: 1045-1051 - [c23]Elin Farnell, Henry Kvinge, Michael Kirby, Chris Peterson:
Endmember Extraction on the Grassmannian. DSW 2018: 71-75 - [c22]Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson:
Too many secants: a hierarchical approach to secant-based dimensionality reduction on large data sets. HPEC 2018: 1-7 - [c21]Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson:
A GPU-Oriented Algorithm Design for Secant-Based Dimensionality Reduction. ISPDC 2018: 69-76 - [c20]Javier Álvarez-Vizoso, Michael Kirby, Chris Peterson:
Manifold Curvature From Covariance Analysis. SSP 2018: 353-357 - [i10]Elin Farnell, Henry Kvinge, Michael Kirby, Chris Peterson:
Endmember Extraction on the Grassmannian. CoRR abs/1807.01401 (2018) - [i9]Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson:
A GPU-Oriented Algorithm Design for Secant-Based Dimensionality Reduction. CoRR abs/1807.03425 (2018) - [i8]Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson:
Too many secants: a hierarchical approach to secant-based dimensionality reduction on large data sets. CoRR abs/1808.01686 (2018) - [i7]Henry Kvinge, Elin Farnell, Michael Kirby, Chris Peterson:
Monitoring the shape of weather, soundscapes, and dynamical systems: a new statistic for dimension-driven data analysis on large data sets. CoRR abs/1810.11562 (2018) - 2017
- [j10]Henry Adams, Tegan Emerson, Michael Kirby, Rachel Neville, Chris Peterson, Patrick D. Shipman, Sofya Chepushtanova, Eric M. Hanson, Francis C. Motta, Lori Ziegelmeier:
Persistence Images: A Stable Vector Representation of Persistent Homology. J. Mach. Learn. Res. 18: 8:1-8:35 (2017) - [j9]Sofya Chepushtanova, Michael Kirby:
Sparse Grassmannian Embeddings for Hyperspectral Data Representation and Classification. IEEE Geosci. Remote. Sens. Lett. 14(3): 434-438 (2017) - [j8]Lori Ziegelmeier, Michael Kirby, Chris Peterson:
Stratifying High-Dimensional Data Based on Proximity to the Convex Hull Boundary. SIAM Rev. 59(2): 346-365 (2017) - [c19]Ignacio Santamaría, Javier Vía, Michael Kirby, Tim Marrinan, Chris Peterson, Louis Scharf:
Constrained subspace estimation via convex optimization. EUSIPCO 2017: 1200-1204 - [c18]Lori Ziegelmeier, Michael Kirby, Chris Peterson:
Sparse Locally Linear Embedding. ICCS 2017: 635-644 - [c17]Xiaofeng Ma, Tomojit Ghosh, Michael Kirby:
A sequential simplex algorithm for automatic data and center selecting radial basis functions. IJCNN 2017: 549-556 - [c16]Michael Kirby, Chris Peterson:
Visualizing data sets on the Grassmannian using self-organizing mappings. WSOM 2017: 28-33 - 2016
- [c15]Mmanu Chaturvedi, Tomojit Ghosh, Michael Kirby, Xiaoyu Liu, Xiaofeng Ma, Shannon Stiverson:
Explorations in Very Early Prognosis of the Human Immune Response to Influenza. BCB 2016: 562-570 - [c14]Sofya Chepushtanova, Michael Kirby, Chris Peterson, Lori Ziegelmeier:
Persistent Homology on Grassmann Manifolds for Analysis of Hyperspectral Movies. CTIC 2016: 228-239 - [c13]Ignacio Santamaría, Louis L. Scharf, Chris Peterson, Michael Kirby, Joseph M. Francos:
An order fitting rule for optimal subspace averaging. SSP 2016: 1-4 - [c12]Tegan Emerson, Michael Kirby, Chris Peterson, Louis Scharf:
Reduced dimension estimators in matched subspace detection. WHISPERS 2016: 1-5 - [i6]Sofya Chepushtanova, Michael Kirby, Chris Peterson, Lori Ziegelmeier:
Persistent Homology on Grassmann Manifolds for Analysis of Hyperspectral Movies. CoRR abs/1607.02196 (2016) - [i5]Lori Ziegelmeier, Michael Kirby, Chris Peterson:
Stratifying High Dimensional Data Based on Proximity to the Convex Hull Boundary. CoRR abs/1611.01419 (2016) - 2015
- [j7]Tegan Emerson, Michael Kirby, Kelly Bethel, Anand Kolatkar, Madelyn Luttgen, Stephen O'Hara, Paul K. Newton, Peter Kuhn:
Fourier-ring descriptor to characterize rare circulating cells from images generated using immunofluorescence microscopy. Comput. Medical Imaging Graph. 40: 70-87 (2015) - [j6]Daniel J. Bates, Brent R. Davis, Michael Kirby, Justin Marks, Chris Peterson:
The max-length-vector line of best fit to a set of vector subspaces and an optimization problem over a set of hyperellipsoids. Numer. Linear Algebra Appl. 22(3): 453-464 (2015) - [c11]Sofya Chepushtanova, Michael Kirby, Chris Peterson, Lori Ziegelmeier:
An application of persistent homology on Grassmann manifolds for the detection of signals in hyperspectral imagery. IGARSS 2015: 449-452 - [i4]Sofya Chepushtanova, Michael Kirby:
Classification of Hyperspectral Imagery on Embedded Grassmannians. CoRR abs/1502.00946 (2015) - [i3]Sofya Chepushtanova, Tegan Emerson, Eric M. Hanson, Michael Kirby, Francis C. Motta, Rachel Neville, Chris Peterson, Patrick D. Shipman, Lori Ziegelmeier:
Persistence Images: An Alternative Persistent Homology Representation. CoRR abs/1507.06217 (2015) - [i2]Salman Habib, Robert Roser, Tom LeCompte, Zach Marshall, Anders Borgland, Brett Viren, Peter Nugent, Makoto Asai, Lothar Bauerdick, Hal Finkel, Steven Gottlieb, Stefan Hoeche, Paul Sheldon, Jean-Luc Vay, Peter Elmer, Michael Kirby, Simon J. Patton, Maxim Potekhin, Brian Yanny, Paolo Calafiura, Eli Dart, Oliver Gutsche, Taku Izubuchi, Adam Lyon, Don Petravick:
High Energy Physics Forum for Computational Excellence: Working Group Reports (I. Applications Software II. Software Libraries and Tools III. Systems). CoRR abs/1510.08545 (2015) - 2014
- [c10]Tim Marrinan, Bruce A. Draper, J. Ross Beveridge, Michael Kirby, Chris Peterson:
Finding the Subspace Mean or Median to Fit Your Need. CVPR 2014: 1082-1089 - [c9]Sofya Chepushtanova, Michael Kirby:
Classification of hyperspectral imagery on embedded Grassmannians. WHISPERS 2014: 1-4 - 2013
- [c8]Tim Marrinan, J. Ross Beveridge, Bruce A. Draper, Michael Kirby, Chris Peterson:
Flag Manifolds for the Characterization of Geometric Structure in Large Data Sets. ENUMATH 2013: 457-465 - 2012
- [i1]Lori Ziegelmeier, Michael Kirby, Chris Peterson:
Locally Linear Embedding Clustering Algorithm for Natural Imagery. CoRR abs/1202.4387 (2012) - 2010
- [c7]Yui Man Lui, J. Ross Beveridge, Michael Kirby:
Action classification on product manifolds. CVPR 2010: 833-839 - [c6]Joshua Thompson, David W. Dreisigmeyer, Terry Jones, Michael Kirby, Joshua Ladd:
Accurate fault prediction of BlueGene/P RAS logs via geometric reduction. DSN Workshops 2010: 8-14
2000 – 2009
- 2009
- [j5]J. Ross Beveridge, Bruce A. Draper, Jen-Mei Chang, Michael Kirby, Holger Kley, Chris Peterson:
Principal Angles Separate Subject Illumination Spaces in YDB and CMU-PIE. IEEE Trans. Pattern Anal. Mach. Intell. 31(2): 351-363 (2009) - 2008
- [c5]Fatemeh Emdad, Michael Kirby, Seyed A. Zekavat:
Feature Extraction via Kernelized Signal Fraction Analysis vs Kernelized Principal Component Analysis. DMIN 2008: 180-184 - [c4]Yui Man Lui, J. Ross Beveridge, Bruce A. Draper, Michael Kirby:
Image-set matching using a geodesic distance and cohort normalization. FG 2008: 1-6 - 2007
- [c3]Jen-Mei Chang, Michael Kirby, Holger Kley, Chris Peterson, Bruce A. Draper, J. Ross Beveridge:
Recognition of Digital Images of the Human Face at Ultra Low Resolution Via Illumination Spaces. ACCV (2) 2007: 733-743 - 2006
- [c2]Jen-Mei Chang, J. Ross Beveridge, Bruce A. Draper, Michael Kirby, Holger Kley, Chris Peterson:
Illumination Face Spaces Are Idiosyncratic. IPCV 2006: 390-396 - 2003
- [c1]Fatemeh Emdad, Seyed A. Zekavat, Michael Kirby:
Adaptive Antenna Beam Forming Via Maximum Noise Fraction for Multi Carrier CDMA Systems. International Conference on Wireless Networks 2003: 431-437
1990 – 1999
- 1994
- [j4]Michael Kirby:
Biotechnology and the law. Comput. Law Secur. Rev. 10(1): 2-9 (1994) - 1993
- [j3]Michael Kirby, F. Weisser, Gerhard Dangelmayr:
A model problem in the representation of digital image sequences. Pattern Recognit. 26(1): 63-73 (1993) - 1992
- [j2]Michael Kirby:
Information security - OECD initiatives. Comput. Law Secur. Rev. 8(3): 98-101 (1992)
1980 – 1989
- 1989
- [j1]Michael Kirby:
Informatics, transborder data flows and law - the new challenges. Comput. Law Secur. Rev. 5(4): 2-8 (1989)
Coauthor Index
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