Balzano, Laura

28 publications

LoG 2025 A Spectral Framework for Tracking Communities in Evolving Networks Jacob Hume, Laura Balzano
NeurIPS 2025 MonarchAttention: Zero-Shot Conversion to Fast, Hardware-Aware Structured Attention Can Yaras, Alec S Xu, Pierre Abillama, Changwoo Lee, Laura Balzano
TMLR 2025 Streaming Heteroscedastic Probabilistic PCA with Missing Data Kyle Gilman, David Hong, Jeffrey A Fessler, Laura Balzano
JMLR 2025 Understanding Deep Representation Learning via Layerwise Feature Compression and Discrimination Peng Wang, Xiao Li, Can Yaras, Zhihui Zhu, Laura Balzano, Wei Hu, Qing Qu
ICML 2024 Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation Can Yaras, Peng Wang, Laura Balzano, Qing Qu
ICML 2024 Convergence and Complexity Guarantee for Inexact First-Order Riemannian Optimization Algorithms Yuchen Li, Laura Balzano, Deanna Needell, Hanbaek Lyu
AISTATS 2024 Efficient Low-Dimensional Compression of Overparameterized Models Soo Min Kwon, Zekai Zhang, Dogyoon Song, Laura Balzano, Qing Qu
AISTATS 2024 Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods Davoud Ataee Tarzanagh, Parvin Nazari, Bojian Hou, Li Shen, Laura Balzano
ICML 2024 Symmetric Matrix Completion with ReLU Sampling Huikang Liu, Peng Wang, Longxiu Huang, Qing Qu, Laura Balzano
NeurIPSW 2023 Invariant Low-Dimensional Subspaces in Gradient Descent for Learning Deep Matrix Factorizations Can Yaras, Peng Wang, Wei Hu, Zhihui Zhu, Laura Balzano, Qing Qu
AISTATS 2022 On the Equivalence of Oja’s Algorithm and GROUSE Laura Balzano
L4DC 2022 Clustering-Based Mode Reduction for Markov Jump Systems Zhe Du, Necmiye Ozay, Laura Balzano
ICML 2022 Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering Peng Wang, Huikang Liu, Anthony Man-Cho So, Laura Balzano
NeurIPSW 2022 Linear Convergence Analysis of Neural Collapse with Unconstrained Features Peng Wang, Huikang Liu, Can Yaras, Laura Balzano, Qing Qu
NeurIPS 2022 Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold Can Yaras, Peng Wang, Zhihui Zhu, Laura Balzano, Qing Qu
JMLR 2020 Online Matrix Factorization for Markovian Data and Applications to Network Dictionary Learning Hanbaek Lyu, Deanna Needell, Laura Balzano
ICML 2020 Preference Modeling with Context-Dependent Salient Features Amanda Bower, Laura Balzano
ICCVW 2019 Panoramic Video Separation with Online Grassmannian Robust Subspace Estimation Kyle Gilman, Laura Balzano
JMLR 2019 Streaming Principal Component Analysis from Incomplete Data Armin Eftekhari, Gregory Ongie, Laura Balzano, Michael B. Wakin
ICLR 2018 Learning to Share: Simultaneous Parameter Tying and Sparsification in Deep Learning Dejiao Zhang, Haozhu Wang, Mario Figueiredo, Laura Balzano
ICML 2017 Algebraic Variety Models for High-Rank Matrix Completion Greg Ongie, Rebecca Willett, Robert D. Nowak, Laura Balzano
ICML 2017 Leveraging Union of Subspace Structure to Improve Constrained Clustering John Lipor, Laura Balzano
AAAI 2017 On Learning High Dimensional Structured Single Index Models Ravi Ganti, Nikhil Rao, Laura Balzano, Rebecca Willett, Robert D. Nowak
AISTATS 2016 Global Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation Dejiao Zhang, Laura Balzano
NeurIPS 2015 Matrix Completion Under Monotonic Single Index Models Ravi Sastry Ganti, Laura Balzano, Rebecca Willett
WACV 2014 Online Algorithms for Factorization-Based Structure from Motion Ryan Kennedy, Laura Balzano, Stephen J. Wright, Camillo J. Taylor
AISTATS 2012 High-Rank Matrix Completion Brian Eriksson, Laura Balzano, Robert Nowak
CVPR 2012 Incremental Gradient on the Grassmannian for Online Foreground and Background Separation in Subsampled Video Jun He, Laura Balzano, Arthur Szlam