| 2024 | AISTATS | Efficient Low-Dimensional Compression of Overparameterized Models. | Soo Min Kwon, Zekai Zhang, Dogyoon Song, Laura Balzano, Qing Qu |
| 2024 | AISTATS | Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods. | Davoud Ataee Tarzanagh, Parvin Nazari, Bojian Hou, Li Shen, Laura Balzano |
| 2024 | ICML | Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms. | Yuchen Li, Laura Balzano, Deanna Needell, Hanbaek Lyu |
| 2024 | ICML | Symmetric Matrix Completion with ReLU Sampling. | Huikang Liu, Peng Wang, Longxiu Huang, Qing Qu, Laura Balzano |
| 2024 | ICML | Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation. | Can Yaras, Peng Wang, Laura Balzano, Qing Qu |
| 2023 | ICASSP | HeMPPCAT: Mixtures of Probabilistic Principal Component analysers for data with heteroscedastic noise. | Alec S. Xu, Laura Balzano, Jeffrey A. Fessler |
| 2023 | ISIT | Matrix Completion over Finite Fields: Bounds and Belief Propagation Algorithms. | Mahdi Soleymani, Qiang Liu, Hessam Mahdavifar, Laura Balzano |
| 2022 | AISTATS | On the equivalence of Oja's algorithm and GROUSE. | Laura Balzano |
| 2022 | ICML | Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering. | Peng Wang, Huikang Liu, Anthony Man-Cho So, Laura Balzano |
| 2020 | ICASSP | Online Tensor Completion and Free Submodule Tracking With The T-SVD. | Kyle Gilman, Laura Balzano |
| 2020 | ICML | Preference Modeling with Context-Dependent Salient Features. | Amanda Bower, Laura Balzano |
| 2018 | ICASSP | The Landscape of Non-Convex Quadratic Feasibility. | Amanda Bower, Lalit Jain, Laura Balzano |
| 2018 | ICLR | Learning to Share: simultaneous parameter tying and Sparsification in Deep Learning. | Dejiao Zhang, Haozhu Wang, Mrio A. T. Figueiredo, Laura Balzano |
| 2017 | AAAI | On Learning High Dimensional Structured Single Index Models. | Ravi Ganti, Nikhil Rao, Laura Balzano, Rebecca Willett, Robert D. Nowak |
| 2017 | ACSSC | Enhanced online subspace estimation via adaptive sensing. | Greg Ongie, David Hong, Dejiao Zhang, Laura Balzano |
| 2017 | ICASSP | Matched subspace detection using compressively sampled data. | Dejiao Zhang, Laura Balzano |
| 2017 | ICML | Leveraging Union of Subspace Structure to Improve Constrained Clustering. | John Lipor, Laura Balzano |
| 2017 | ICML | Algebraic Variety Models for High-Rank Matrix Completion. | Greg Ongie, Rebecca Willett, Robert D. Nowak, Laura Balzano |
| 2016 | AISTATS | Global Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation. | Dejiao Zhang, Laura Balzano |
| 2014 | ICASSP | Robust blind calibration via total least squares. | John Lipor, Laura Balzano |
| 2014 | WACV | Online algorithms for factorization-based structure from motion. | Ryan Kennedy, Laura Balzano, Stephen J. Wright, Camillo J. Taylor |
| 2012 | CVPR | Incremental gradient on the Grassmannian for online foreground and background separation in subsampled video. | Jun He, Laura Balzano, Arthur Szlam |
| 2011 | ICASSP | On the success of network inference using a markov routing model. | Laura Balzano, Robert D. Nowak, Matthew Roughan |
| 2011 | ISIT | Rank minimization over finite fields. | Vincent Y. F. Tan, Laura Balzano, Stark C. Draper |
| 2010 | ISIT | High-dimensional Matched Subspace Detection when data are missing. | Laura Balzano, Benjamin Recht, Robert D. Nowak |
| 2006 | ICTD | Designing Wireless Sensor Networks as a Shared Resource for Sustainable Development. | Nithya Ramanathan, Laura Balzano, Deborah Estrin, Mark H. Hansen, Thomas C. Harmon, Jenny Jay, William J. Kaiser, Gaurav S. Sukhatme |