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ORCIDLaura Balzano
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- affiliation: University of Michigan, Ann Arbor
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2020 – today
- 2024
[j20]Rachel Newton
, Zhe Du, Peter J. Seiler, Laura Balzano:
Optimality of POD for Data-Driven LQR With Low-Rank Structures. IEEE Control. Syst. Lett. 8: 85-90 (2024)- [c60]Soo Min Kwon, Zekai Zhang, Dogyoon Song, Laura Balzano, Qing Qu:
Efficient Low-Dimensional Compression of Overparameterized Models. AISTATS 2024: 1009-1017 - [c59]Davoud Ataee Tarzanagh, Parvin Nazari, Bojian Hou, Li Shen, Laura Balzano:
Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods. AISTATS 2024: 2854-2862 - [c58]Yuchen Li, Laura Balzano, Deanna Needell, Hanbaek Lyu:
Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms. ICML 2024 - [c57]Huikang Liu, Peng Wang, Longxiu Huang, Qing Qu, Laura Balzano:
Symmetric Matrix Completion with ReLU Sampling. ICML 2024 - [c56]Can Yaras, Peng Wang, Laura Balzano, Qing Qu:
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation. ICML 2024 - [i41]Can Yaras, Peng Wang, Laura Balzano, Qing Qu:
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation. CoRR abs/2406.04112 (2024) - [i40]Huikang Liu, Peng Wang, Longxiu Huang, Qing Qu, Laura Balzano:
Symmetric Matrix Completion with ReLU Sampling. CoRR abs/2406.05822 (2024) - 2023
- [j19]David Hong, Fan Yang, Jeffrey A. Fessler, Laura Balzano:
Optimally Weighted PCA for High-Dimensional Heteroscedastic Data. SIAM J. Math. Data Sci. 5(1): 222-250 (2023) - [c55]Rachel Newton, Zhe Du, Laura Balzano, Peter Seiler:
Manifold Optimization for Data Driven Reduced-Order Modeling*. Allerton 2023: 1-6 - [c54]Rudy Geelen, Laura Balzano, Karen Willcox:
Learning Latent Representations in High-Dimensional State Spaces Using Polynomial Manifold Constructions. CDC 2023: 4960-4965 - [c53]Alec S. Xu, Laura Balzano, Jeffrey A. Fessler:
HeMPPCAT: Mixtures of Probabilistic Principal Component analysers for data with heteroscedastic noise. ICASSP 2023: 1-5 - [c52]Mahdi Soleymani, Qiang Liu, Hessam Mahdavifar, Laura Balzano:
Matrix Completion over Finite Fields: Bounds and Belief Propagation Algorithms. ISIT 2023: 1166-1171 - [i39]Can Yaras, Peng Wang, Wei Hu, Zhihui Zhu, Laura Balzano, Qing Qu:
The Law of Parsimony in Gradient Descent for Learning Deep Linear Networks. CoRR abs/2306.01154 (2023) - [i38]Rudy Geelen, Laura Balzano, Karen Willcox:
Learning latent representations in high-dimensional state spaces using polynomial manifold constructions. CoRR abs/2306.13748 (2023) - [i37]Rudy Geelen, Laura Balzano, Stephen Wright, Karen Willcox:
Learning physics-based reduced-order models from data using nonlinear manifolds. CoRR abs/2308.02802 (2023) - [i36]Mahdi Soleymani, Qiang Liu, Hessam Mahdavifar, Laura Balzano:
Matrix Completion over Finite Fields: Bounds and Belief Propagation Algorithms. CoRR abs/2308.11078 (2023) - [i35]Peng Wang, Xiao Li, Can Yaras, Zhihui Zhu, Laura Balzano, Wei Hu, Qing Qu:
Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination. CoRR abs/2311.02960 (2023) - [i34]Soo Min Kwon, Zekai Zhang, Dogyoon Song, Laura Balzano, Qing Qu:
Efficient Compression of Overparameterized Deep Models through Low-Dimensional Learning Dynamics. CoRR abs/2311.05061 (2023) - 2022
- [j18]Kyle Gilman, Davoud Ataee Tarzanagh, Laura Balzano:
Grassmannian Optimization for Online Tensor Completion and Tracking With the t-SVD. IEEE Trans. Signal Process. 70: 2152-2167 (2022) - [c51]Laura Balzano:
On the equivalence of Oja's algorithm and GROUSE. AISTATS 2022: 7014-7030 - [c50]Yahya Sattar, Zhe Du, Davoud Ataee Tarzanagh, Samet Oymak, Laura Balzano, Necmiye Ozay:
Certainty Equivalent Quadratic Control for Markov Jump Systems. ACC 2022: 2871-2878 - [c49]Zhe Du, Yahya Sattar, Davoud Ataee Tarzanagh, Laura Balzano, Necmiye Ozay, Samet Oymak:
Data-Driven Control of Markov Jump Systems: Sample Complexity and Regret Bounds. ACC 2022: 4901-4908 - [c48]Rishhabh Naik, Nisarg Trivedi, Davoud Ataee Tarzanagh, Laura Balzano:
Truncated Matrix Completion - An Empirical Study. EUSIPCO 2022: 847-851 - [c47]Peng Wang, Huikang Liu, Anthony Man-Cho So, Laura Balzano:
Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering. ICML 2022: 22884-22918 - [c46]Zhe Du, Necmiye Ozay, Laura Balzano:
Clustering-based Mode Reduction for Markov Jump Systems. L4DC 2022: 689-701 - [c45]Can Yaras, Peng Wang, Zhihui Zhu, Laura Balzano, Qing Qu:
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold. NeurIPS 2022 - [i33]Zhe Du, Laura Balzano, Necmiye Ozay:
Mode Reduction for Markov Jump Systems. CoRR abs/2205.02697 (2022) - [i32]Davoud Ataee Tarzanagh, Laura Balzano:
Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods. CoRR abs/2207.02829 (2022) - [i31]Can Yaras, Peng Wang, Zhihui Zhu, Laura Balzano, Qing Qu:
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold. CoRR abs/2209.09211 (2022) - 2021
- [j17]Greg Ongie, Daniel L. Pimentel-Alarcón, Laura Balzano, Rebecca Willett, Robert D. Nowak:
Tensor Methods for Nonlinear Matrix Completion. SIAM J. Math. Data Sci. 3(1): 253-279 (2021) - [j16]David Hong, Kyle Gilman, Laura Balzano, Jeffrey A. Fessler:
HePPCAT: Probabilistic PCA for Data With Heteroscedastic Noise. IEEE Trans. Signal Process. 69: 4819-4834 (2021) - [i30]Zhe Du, Yahya Sattar, Davoud Ataee Tarzanagh, Laura Balzano, Samet Oymak, Necmiye Ozay:
Certainty Equivalent Quadratic Control for Markov Jump Systems. CoRR abs/2105.12358 (2021) - [i29]Yahya Sattar, Zhe Du, Davoud Ataee Tarzanagh, Laura Balzano, Necmiye Ozay, Samet Oymak:
Identification and Adaptive Control of Markov Jump Systems: Sample Complexity and Regret Bounds. CoRR abs/2111.07018 (2021) - [i28]Davoud Ataee Tarzanagh, Laura Balzano, Alfred O. Hero III:
Fair Structure Learning in Heterogeneous Graphical Models. CoRR abs/2112.05128 (2021) - 2020
- [j15]John Lipor, Laura Balzano:
Clustering quality metrics for subspace clustering. Pattern Recognit. 104: 107328 (2020) - [c44]Kyle Gilman, Laura Balzano:
Online Tensor Completion and Free Submodule Tracking With The T-SVD. ICASSP 2020: 3282-3286 - [c43]Amanda Bower, Laura Balzano:
Preference Modeling with Context-Dependent Salient Features. ICML 2020: 1067-1077 - [i27]Kyle Gilman, Laura Balzano:
Grassmannian Optimization for Online Tensor Completion and Tracking in the t-SVD Algebra. CoRR abs/2001.11419 (2020) - [i26]Amanda Bower, Laura Balzano:
Preference Modeling with Context-Dependent Salient Features. CoRR abs/2002.09615 (2020) - [i25]Alexander Ritchie, Laura Balzano, Clayton D. Scott:
Supervised PCA: A Multiobjective Approach. CoRR abs/2011.05309 (2020)
2010 – 2019
- 2019
- [j14]Armin Eftekhari, Gregory Ongie, Laura Balzano, Michael B. Wakin:
Streaming Principal Component Analysis From Incomplete Data. J. Mach. Learn. Res. 20: 86:1-86:62 (2019) - [c42]David Hong, Laura Balzano, Jeffrey A. Fessler:
Probabilistic PCA for Heteroscedastic Data. CAMSAP 2019: 26-30 - [c41]Zhe Du, Necmiye Ozay, Laura Balzano:
Mode Clustering for Markov Jump Systems. CAMSAP 2019: 126-130 - [c40]Alexander Ritchie, Clayton D. Scott, Laura Balzano, Daniel Kessler, Chandra Sekhar Sripada:
Supervised Principal Component Analysis Via Manifold Optimization. DSW 2019: 6-10 - [c39]David Hong, Shunbo Lei, Johanna L. Mathieu, Laura Balzano:
Exploration of tensor decomposition applied to commercial building baseline estimation. GlobalSIP 2019: 1-5 - [c38]Kyle Gilman, Laura Balzano:
Panoramic Video Separation with Online Grassmannian Robust Subspace Estimation. ICCV Workshops 2019: 643-651 - [i24]Zhe Du, Necmiye Ozay, Laura Balzano:
Mode Clustering for Markov Jump Systems. CoRR abs/1910.02193 (2019) - [i23]Hanbaek Lyu, Deanna Needell, Laura Balzano:
Online matrix factorization for Markovian data and applications to Network Dictionary Learning. CoRR abs/1911.01931 (2019) - 2018
- [j13]Andrew Gitlin, Biaoshuai Tao, Laura Balzano, John Lipor:
Improving K-Subspaces via Coherence Pursuit. IEEE J. Sel. Top. Signal Process. 12(6): 1575-1588 (2018) - [j12]David Hong, Laura Balzano, Jeffrey A. Fessler:
Asymptotic performance of PCA for high-dimensional heteroscedastic data. J. Multivar. Anal. 167: 435-452 (2018) - [j11]Laura Balzano, Yuejie Chi, Yue M. Lu:
Streaming PCA and Subspace Tracking: The Missing Data Case. Proc. IEEE 106(8): 1293-1310 (2018) - [c37]Gregory S. Ledva, Laura Balzano, Johanna L. Mathieu:
Exploring Connections Between a Multiple Model Kalman Filter and Dynamic Fixed Share with Applications to Demand Response. CCTA 2018: 217-223 - [c36]David Hong, Robert P. Malinas, Jeffrey A. Fessler, Laura Balzano:
Learning Dictionary-Based Unions of Subspaces for Image Denoising. EUSIPCO 2018: 1597-1601 - [c35]Amanda Bower, Lalit Jain, Laura Balzano:
The Landscape of Non-Convex Quadratic Feasibility. ICASSP 2018: 3974-3978 - [c34]Dejiao Zhang, Haozhu Wang, Mário A. T. Figueiredo, Laura Balzano:
Learning to Share: simultaneous parameter tying and Sparsification in Deep Learning. ICLR (Poster) 2018 - [c33]Dejiao Zhang, Julian Katz-Samuels, Mário A. T. Figueiredo, Laura Balzano:
Simultaneous Sparsity and Parameter Tying for Deep Learning Using Ordered Weighted ℓ1 Regularization. SSP 2018: 65-69 - [c32]Greg Ongie, David Hong, Dejiao Zhang, Laura Balzano:
Online Estimation of Coherent Subspaces with Adaptive Sampling. SSP 2018: 841-845 - [i22]Greg Ongie, Laura Balzano, Daniel L. Pimentel-Alarcón, Rebecca Willett, Robert D. Nowak:
Tensor Methods for Nonlinear Matrix Completion. CoRR abs/1804.10266 (2018) - [i21]Zhe Du, Necmiye Ozay, Laura Balzano:
A Robust Algorithm for Online Switched System Identification. CoRR abs/1805.01111 (2018) - [i20]Laura Balzano, Yuejie Chi, Yue M. Lu:
Streaming PCA and Subspace Tracking: The Missing Data Case. CoRR abs/1806.04609 (2018) - 2017
- [j10]Armin Eftekhari, Laura Balzano, Michael B. Wakin:
What to Expect When You Are Expecting on the Grassmannian. IEEE Signal Process. Lett. 24(6): 872-876 (2017) - [j9]John Lipor, Brandon P. Wong, Donald Scavia, Branko Kerkez, Laura Balzano:
Distance-Penalized Active Learning Using Quantile Search. IEEE Trans. Signal Process. 65(20): 5453-5465 (2017) - [c31]Ravi Ganti, Nikhil Rao, Laura Balzano, Rebecca Willett, Robert D. Nowak:
On Learning High Dimensional Structured Single Index Models. AAAI 2017: 1898-1904 - [c30]Greg Ongie, David Hong, Dejiao Zhang, Laura Balzano:
Enhanced online subspace estimation via adaptive sensing. ACSSC 2017: 993-997 - [c29]Daniel L. Pimentel-Alarcón, Gregory Ongie, Laura Balzano, Rebecca Willett, Robert D. Nowak:
Low algebraic dimension matrix completion. Allerton 2017: 790-797 - [c28]Greg Ongie, Saket Dewangan, Jeffrey A. Fessler, Laura Balzano:
Online dynamic MRI reconstruction via robust subspace tracking. GlobalSIP 2017: 1180-1184 - [c27]Dejiao Zhang, Laura Balzano:
Matched subspace detection using compressively sampled data. ICASSP 2017: 4601-4605 - [c26]John Lipor, Laura Balzano:
Leveraging Union of Subspace Structure to Improve Constrained Clustering. ICML 2017: 2130-2139 - [c25]Greg Ongie, Rebecca Willett, Robert D. Nowak, Laura Balzano:
Algebraic Variety Models for High-Rank Matrix Completion. ICML 2017: 2691-2700 - [i19]John Lipor, David Hong, Dejiao Zhang, Laura Balzano:
Subspace Clustering using Ensembles of $K$-Subspaces. CoRR abs/1709.04744 (2017) - [i18]Dejiao Zhang, Yifan Sun, Brian Eriksson, Laura Balzano:
Deep Unsupervised Clustering Using Mixture of Autoencoders. CoRR abs/1712.07788 (2017) - 2016
- [j8]Ryan Kennedy, Laura Balzano, Stephen J. Wright, Camillo J. Taylor:
Online algorithms for factorization-based structure from motion. Comput. Vis. Image Underst. 150: 139-152 (2016) - [c24]Dejiao Zhang, Laura Balzano:
Global Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation. AISTATS 2016: 1460-1468 - [c23]Pengyu Xiao, Laura Balzano:
Online sparse and orthogonal subspace estimation from partial information. Allerton 2016: 284-291 - [c22]David Hong, Laura Balzano, Jeffrey A. Fessler:
Towards a theoretical analysis of PCA for heteroscedastic data. Allerton 2016: 496-503 - [c21]Daniel L. Pimentel-Alarcón, Laura Balzano, Robert D. Nowak:
Necessary and sufficient conditions for sketched subspace clustering. Allerton 2016: 1335-1343 - [c20]Daniel L. Pimentel-Alarcón, Laura Balzano, Roummel F. Marcia, Robert D. Nowak, Rebecca Willett:
Group-sparse subspace clustering with missing data. SSP 2016: 1-5 - [i17]Nikhil Rao, Ravi Ganti, Laura Balzano, Rebecca Willett, Robert D. Nowak:
On Learning High Dimensional Structured Single Index Models. CoRR abs/1603.03980 (2016) - [i16]John Lipor, Laura Balzano:
Leveraging Union of Subspace Structure to Improve Constrained Clustering. CoRR abs/1608.02146 (2016) - [i15]Dejiao Zhang, Laura Balzano:
Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation From Undersampled Data. CoRR abs/1610.00199 (2016) - [i14]Armin Eftekhari, Laura Balzano, Michael B. Wakin:
What to Expect When You Are Expecting on the Grassmannian. CoRR abs/1611.07216 (2016) - [i13]Armin Eftekhari, Laura Balzano, Dehui Yang, Michael B. Wakin:
SNIPE for Memory-Limited PCA From Incomplete Data. CoRR abs/1612.00904 (2016) - 2015
- [j7]Laura Balzano, Stephen J. Wright:
Local Convergence of an Algorithm for Subspace Identification from Partial Data. Found. Comput. Math. 15(5): 1279-1314 (2015) - [c19]Gregory S. Ledva, Laura Balzano, Johanna L. Mathieu:
Inferring the behavior of distributed energy resources with online learning. Allerton 2015: 187-194 - [c18]John Lipor, Laura Balzano, Branko Kerkez, Donald Scavia:
Quantile search: A distance-penalized active learning algorithm for spatial sampling. Allerton 2015: 1241-1248 - [c17]John Lipor, Laura Balzano:
Margin-based active subspace clustering. CAMSAP 2015: 377-380 - [c16]Ravi Sastry Ganti Mahapatruni, Laura Balzano, Rebecca Willett:
Matrix Completion Under Monotonic Single Index Models. NIPS 2015: 1873-1881 - [i12]Dejiao Zhang, Laura Balzano:
Global Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation. CoRR abs/1506.07405 (2015) - [i11]John Lipor, Laura Balzano, Branko Kerkez, Donald Scavia:
Quantile Search: A Distance-Penalized Active Learning Algorithm for Spatial Sampling. CoRR abs/1509.08387 (2015) - [i10]Ravi Ganti, Laura Balzano, Rebecca Willett:
Matrix Completion Under Monotonic Single Index Models. CoRR abs/1512.08787 (2015) - 2014
- [j6]Jun He, Dejiao Zhang, Laura Balzano, Tao Tao:
Iterative Grassmannian optimization for robust image alignment. Image Vis. Comput. 32(10): 800-813 (2014) - [c15]Ryan Kennedy, Camillo J. Taylor, Laura Balzano:
Online completion of Ill-conditioned low-rank matrices. GlobalSIP 2014: 507-511 - [c14]John Lipor, Laura Balzano:
Robust blind calibration via total least squares. ICASSP 2014: 4244-4248 - [c13]Daniel L. Pimentel-Alarcón, Robert D. Nowak, Laura Balzano:
On the sample complexity of subspace clustering with missing data. SSP 2014: 280-283 - [c12]Ryan Kennedy, Laura Balzano, Stephen J. Wright, Camillo J. Taylor:
Online algorithms for factorization-based structure from motion. WACV 2014: 37-44 - 2013
- [c11]Laura Balzano, Stephen J. Wright:
On GROUSE and incremental SVD. CAMSAP 2013: 1-4 - [c10]Jun He, Dejiao Zhang, Laura Balzano, Tao Tao:
Iterative online subspace learning for robust image alignment. FG 2013: 1-8 - [i9]Jun He, Dejiao Zhang, Laura Balzano, Tao Tao:
Iterative Grassmannian Optimization for Robust Image Alignment. CoRR abs/1306.0404 (2013) - [i8]Laura Balzano, Stephen J. Wright:
Local Convergence of an Algorithm for Subspace Identification from Partial Data. CoRR abs/1306.3391 (2013) - [i7]Laura Balzano, Stephen J. Wright:
On GROUSE and Incremental SVD. CoRR abs/1307.5494 (2013) - [i6]Ryan Kennedy, Laura Balzano, Stephen J. Wright, Camillo J. Taylor:
Online Algorithms for Factorization-Based Structure from Motion. CoRR abs/1309.6964 (2013) - 2012
- [j5]Vincent Y. F. Tan, Laura Balzano, Stark C. Draper:
Rank Minimization Over Finite Fields: Fundamental Limits and Coding-Theoretic Interpretations. IEEE Trans. Inf. Theory 58(4): 2018-2039 (2012) - [c9]Jun He, Laura Balzano, Arthur Szlam:
Incremental gradient on the Grassmannian for online foreground and background separation in subsampled video. CVPR 2012: 1568-1575 - [c8]Laura Balzano, Arthur Szlam, Benjamin Recht, Robert D. Nowak:
K-subspaces with missing data. SSP 2012: 612-615 - [c7]Brian Eriksson, Laura Balzano, Robert D. Nowak:
High-Rank Matrix Completion. AISTATS 2012: 373-381 - 2011
- [c6]Laura Balzano, Robert D. Nowak, Matthew Roughan:
On the success of network inference using a markov routing model. ICASSP 2011: 3108-3111 - [c5]Vincent Y. F. Tan, Laura Balzano, Stark C. Draper:
Rank minimization over finite fields. ISIT 2011: 1195-1199 - [i5]Vincent Y. F. Tan, Laura Balzano, Stark C. Draper:
Rank Minimization over Finite Fields: Fundamental Limits and Coding-Theoretic Interpretations. CoRR abs/1104.4302 (2011) - [i4]Jun He, Laura Balzano, John C. S. Lui:
Online Robust Subspace Tracking from Partial Information. CoRR abs/1109.3827 (2011) - [i3]Brian Eriksson, Laura Balzano, Robert D. Nowak:
High-Rank Matrix Completion and Subspace Clustering with Missing Data. CoRR abs/1112.5629 (2011) - 2010
- [c4]Laura Balzano, Robert Nowak, Benjamin Recht:
Online identification and tracking of subspaces from highly incomplete information. Allerton 2010: 704-711 - [c3]Laura Balzano, Benjamin Recht, Robert D. Nowak:
High-dimensional Matched Subspace Detection when data are missing. ISIT 2010: 1638-1642 - [i2]Laura Balzano, Benjamin Recht, Robert D. Nowak:
High-Dimensional Matched Subspace Detection When Data are Missing. CoRR abs/1002.0852 (2010) - [i1]Laura Balzano, Robert D. Nowak, Benjamin Recht:
Online Identification and Tracking of Subspaces from Highly Incomplete Information. CoRR abs/1006.4046 (2010)
2000 – 2009
- 2009
- [j4]Kevin Ni, Nithya Ramanathan, Mohamed Nabil Hajj Chehade, Laura Balzano, Sheela Nair, Sadaf Zahedi, Eddie Kohler, Gregory J. Pottie, Mark H. Hansen, Mani B. Srivastava:
Sensor network data fault types. ACM Trans. Sens. Networks 5(3): 25:1-25:29 (2009) - 2008
- [j3]Saurabh Ganeriwal, Laura Balzano, Mani B. Srivastava:
Reputation-based framework for high integrity sensor networks. ACM Trans. Sens. Networks 4(3): 15:1-15:37 (2008) - 2007
- [c2]Laura Balzano, Robert D. Nowak:
Blind calibration of sensor networks. IPSN 2007: 79-88 - 2006
- [c1]Nithya Ramanathan, Laura Balzano, Deborah Estrin, Mark H. Hansen, Thomas C. Harmon, Jenny Jay, William J. Kaiser, Gaurav S. Sukhatme:
Designing Wireless Sensor Networks as a Shared Resource for Sustainable Development. ICTD 2006: 256-265 - 2004
- [j2]