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Tim Marrinan
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Journal Articles
- 2020
- [j1]Tanuj Hasija, Timothy Marrinan, Christian Lameiro, Peter J. Schreier:
Determining the dimension and structure of the subspace correlated across multiple data sets. Signal Process. 176: 107613 (2020)
Conference and Workshop Papers
- 2024
- [c11]Maurice Kuschel, Tanuj Hasija, Timothy Marrinan:
Rademacher Complexity Regularization for Correlation-Based Multiview Representation Learning. ICASSP 2024: 6490-6494 - [c10]Tim Marrinan, Shahana Ibrahim, Xiao Fu:
Labeling Sequential Data From Noisy Annotations. SAM 2024: 1-5 - 2023
- [c9]Daniel Grey Wolnick, Shahana Ibrahim, Tim Marrinan, Xiao Fu:
Deep Learning from Noisy Labels via Robust Nonnegative Matrix Factorization-Based Design. CAMSAP 2023: 446-450 - [c8]Maurice Kuschel, Timothy Marrinan, Tanuj Hasija:
Geodesic-Based Relaxation For Deep Canonical Correlation Analysis. MLSP 2023: 1-6 - 2022
- [c7]Tanuj Hasija, Timothy Marrinan:
A GLRT for estimating the number of correlated components in sample-poor mCCA. EUSIPCO 2022: 2091-2095 - 2020
- [c6]Timothy Marrinan, Nicolas Gillis:
Hyperspectral Unmixing with Rare Endmembers via Minimax Nonnegative Matrix Factorization. EUSIPCO 2020: 1015-1019 - 2019
- [c5]Christian Lameiro, Tanuj Hasija, Tim Marrinan, Peter J. Schreier:
Estimating the Number of Correlated Components Based on Random Projections. ICASSP 2019: 5152-5156 - 2018
- [c4]Tim Marrinan, Tanuj Hasija, Christian Lameiro, Peter J. Schreier:
Complete Model Selection in Multiset Canonical Correlation Analysis. EUSIPCO 2018: 1082-1086 - 2017
- [c3]Ignacio Santamaría, Javier Vía, Michael Kirby, Tim Marrinan, Chris Peterson, Louis Scharf:
Constrained subspace estimation via convex optimization. EUSIPCO 2017: 1200-1204 - 2014
- [c2]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 - 2013
- [c1]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
Informal and Other Publications
- 2024
- [i4]Sinjini Banerjee, Tim Marrinan, Reilly Cannon, Tony Chiang, Anand D. Sarwate:
Measuring model variability using robust non-parametric testing. CoRR abs/2406.08307 (2024) - 2023
- [i3]Sinjini Banerjee, Reilly Cannon, Tim Marrinan, Tony Chiang, Anand D. Sarwate:
Robust Nonparametric Hypothesis Testing to Understand Variability in Training Neural Networks. CoRR abs/2310.00541 (2023) - 2020
- [i2]Timothy Marrinan, Pierre-Antoine Absil, Nicolas Gillis:
On a minimum enclosing ball of a collection of linear subspaces. CoRR abs/2003.12455 (2020) - 2019
- [i1]Tanuj Hasija, Christian Lameiro, Timothy Marrinan, Peter J. Schreier:
Determining the Dimension and Structure of the Subspace Correlated Across Multiple Data Sets. CoRR abs/1901.11366 (2019)
Coauthor Index
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