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ORCIDGilad Lerman
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- affiliation: University of Minnesota, USA
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2020 – today
- 2024
[j20]Casey Garner
, Gilad Lerman, Shuzhong Zhang:
Spectrally Constrained Optimization. J. Sci. Comput. 100(3): 89 (2024)- [c25]Yinglong Guo, Shaohan Li, Gilad Lerman:
The effect of Leaky ReLUs on the training and generalization of overparameterized networks. AISTATS 2024: 4393-4401 - [c24]Shaohan Li, Yunpeng Shi, Gilad Lerman:
Efficient Detection of Long Consistent Cycles and its Application to Distributed Synchronization. CVPR 2024: 5260-5269 - [c23]Feng Yu, Teng Zhang, Gilad Lerman:
A Subspace-Constrained Tyler's Estimator and its Applications to Structure from Motion. CVPR 2024: 14575-14584 - [c22]Yifei Yang, Wonjun Lee, Dongmian Zou, Gilad Lerman:
Improving Hyperbolic Representations via Gromov-Wasserstein Regularization. ECCV (82) 2024: 211-227 - [i44]Yinglong Guo, Shaohan Li, Gilad Lerman:
The effect of Leaky ReLUs on the training and generalization of overparameterized networks. CoRR abs/2402.11942 (2024) - [i43]Feng Yu, Teng Zhang, Gilad Lerman:
A Subspace-Constrained Tyler's Estimator and its Applications to Structure from Motion. CoRR abs/2404.11590 (2024) - [i42]Cristian Chica, Yinglong Guo, Gilad Lerman:
Artificial Intelligence and Algorithmic Price Collusion in Two-sided Markets. CoRR abs/2407.04088 (2024) - [i41]Shaohan Li, Yunpeng Shi, Gilad Lerman:
Efficient Detection of Long Consistent Cycles and its Application to Distributed Synchronization. CoRR abs/2407.04260 (2024) - [i40]Yifei Yang, Wonjun Lee, Dongmian Zou, Gilad Lerman:
Improving Hyperbolic Representations via Gromov-Wasserstein Regularization. CoRR abs/2407.10495 (2024) - [i39]Daniel Miao, Gilad Lerman, Joe Kileel:
Tensor-Based Synchronization and the Low-Rankness of the Block Trifocal Tensor. CoRR abs/2409.09313 (2024) - 2023
- [j19]Tyler Maunu, Gilad Lerman:
Depth Descent Synchronization in ${{\,\mathrm{\text {SO}}\,}}(D)$. Int. J. Comput. Vis. 131(4): 968-986 (2023) - [c21]Yinglong Guo, Dongmian Zou, Gilad Lerman:
An Unpooling Layer for Graph Generation. AISTATS 2023: 3179-3209 - [c20]Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman:
Robust Variational Autoencoding with Wasserstein Penalty for Novelty Detection. AISTATS 2023: 3538-3567 - [i38]Wonjun Lee, Yifei Yang, Dongmian Zou, Gilad Lerman:
Monotone Generative Modeling via a Gromov-Monge Embedding. CoRR abs/2311.01375 (2023) - [i37]Casey Garner, Gilad Lerman, Teng Zhang:
Improved Convergence Rates of Anderson Acceleration for a Large Class of Fixed-Point Iterations. CoRR abs/2311.02490 (2023) - 2022
- [j18]Gilad Lerman, Yunpeng Shi:
Robust Group Synchronization via Cycle-Edge Message Passing. Found. Comput. Math. 22(6): 1665-1741 (2022) - [c19]Shaohan Li, Yunpeng Shi, Gilad Lerman:
Fast, Accurate and Memory-Efficient Partial Permutation Synchronization. CVPR 2022: 15714-15722 - [c18]Yunpeng Shi, Cole M. Wyeth, Gilad Lerman:
Robust Group Synchronization via Quadratic Programming. ICML 2022: 20095-20105 - [c17]Tyler Maunu, Chenyu Yu, Gilad Lerman:
Stochastic and Private Nonconvex Outlier-Robust PCAs. MSML 2022: 173-188 - [i36]Yunpeng Shi, Shaohan Li, Tyler Maunu, Gilad Lerman:
Scalable Cluster-Consistency Statistics for Robust Multi-Object Matching. CoRR abs/2201.04797 (2022) - [i35]Tyler Maunu, Chenyu Yu, Gilad Lerman:
Stochastic and Private Nonconvex Outlier-Robust PCA. CoRR abs/2203.09276 (2022) - [i34]Shaohan Li, Yunpeng Shi, Gilad Lerman:
Fast, Accurate and Memory-Efficient Partial Permutation Synchronization. CoRR abs/2203.16505 (2022) - [i33]Yinglong Guo, Dongmian Zou, Gilad Lerman:
An Unpooling Layer for Graph Generation. CoRR abs/2206.01874 (2022) - [i32]Yunpeng Shi, Cole Wyeth, Gilad Lerman:
Robust Group Synchronization via Quadratic Programming. CoRR abs/2206.08994 (2022) - [i31]Casey Garner, Gilad Lerman, Shuzhong Zhang:
Cubic-Regularized Newton for Spectral Constrained Matrix Optimization and its Application to Fairness. CoRR abs/2209.01229 (2022) - 2021
- [c16]Yunpeng Shi, Shaohan Li, Tyler Maunu, Gilad Lerman:
Scalable Cluster-Consistency Statistics for Robust Multi-Object Matching. 3DV 2021: 352-360 - 2020
- [j17]Vahan Huroyan, Gilad Lerman, Hau-Tieng Wu:
Solving Jigsaw Puzzles by the Graph Connection Laplacian. SIAM J. Imaging Sci. 13(4): 1717-1753 (2020) - [c15]Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman:
Robust Subspace Recovery Layer for Unsupervised Anomaly Detection. ICLR 2020 - [c14]Yunpeng Shi, Gilad Lerman:
Message Passing Least Squares Framework and its Application to Rotation Synchronization. ICML 2020: 8796-8806 - [c13]Yunpeng Shi, Shaohan Li, Gilad Lerman:
Robust Multi-Object Matching via Iterative Reweighting of the Graph Connection Laplacian. NeurIPS 2020 - [i30]Tyler Maunu, Gilad Lerman:
A Provably Robust Multiple Rotation Averaging Scheme for SO(2). CoRR abs/2002.05299 (2020) - [i29]Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman:
Novelty Detection via Robust Variational Autoencoding. CoRR abs/2006.05534 (2020) - [i28]Yunpeng Shi, Shaohan Li, Gilad Lerman:
Robust Multi-object Matching via Iterative Reweighting of the Graph Connection Laplacian. CoRR abs/2006.06658 (2020) - [i27]Yunpeng Shi, Gilad Lerman:
Message Passing Least Squares Framework and its Application to Rotation Synchronization. CoRR abs/2007.13638 (2020)
2010 – 2019
- 2019
- [j16]Tyler Maunu, Teng Zhang, Gilad Lerman:
A Well-Tempered Landscape for Non-convex Robust Subspace Recovery. J. Mach. Learn. Res. 20: 37:1-37:59 (2019) - [c12]Dongmian Zou, Gilad Lerman:
Encoding robust representation for graph generation. IJCNN 2019: 1-9 - [i26]Mauricio Flores Rios, Jeff Calder, Gilad Lerman:
Algorithms for 𝓁p-based semi-supervised learning on graphs. CoRR abs/1901.05031 (2019) - [i25]Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman:
Robust Subspace Recovery Layer for Unsupervised Anomaly Detection. CoRR abs/1904.00152 (2019) - [i24]Tyler Maunu, Gilad Lerman:
Robust Subspace Recovery with Adversarial Outliers. CoRR abs/1904.03275 (2019) - [i23]Gilad Lerman, Yunpeng Shi:
Robust Group Synchronization via Cycle-Edge Message Passing. CoRR abs/1912.11347 (2019) - 2018
- [j15]Gilad Lerman, Tyler Maunu:
An Overview of Robust Subspace Recovery. Proc. IEEE 106(8): 1380-1410 (2018) - [j14]Gilad Lerman, Yunpeng Shi, Teng Zhang:
Exact Camera Location Recovery by Least Unsquared Deviations. SIAM J. Imaging Sci. 11(4): 2692-2721 (2018) - [j13]Vahan Huroyan, Gilad Lerman:
Distributed Robust Subspace Recovery. SIAM J. Sci. Comput. 40(5): A3067-A3090 (2018) - [c11]Yunpeng Shi, Gilad Lerman:
Estimation of Camera Locations in Highly Corrupted Scenarios: All About That Base, No Shape Trouble. CVPR 2018: 2868-2876 - [i22]Gilad Lerman, Tyler Maunu:
An Overview of Robust Subspace Recovery. CoRR abs/1803.01013 (2018) - [i21]Dongmian Zou, Gilad Lerman:
Graph Convolutional Neural Networks via Scattering. CoRR abs/1804.00099 (2018) - [i20]Yunpeng Shi, Gilad Lerman:
Estimation of Camera Locations in Highly Corrupted Scenarios: All About that Base, No Shape Trouble. CoRR abs/1804.02591 (2018) - [i19]Wei-Kuo Chen, Madeline Handschy, Gilad Lerman:
Phase transition in random tensors with multiple spikes. CoRR abs/1809.06790 (2018) - [i18]Dongmian Zou, Gilad Lerman:
Graph Generation via Scattering. CoRR abs/1809.10851 (2018) - [i17]Vahan Huroyan, Gilad Lerman, Hau-Tieng Wu:
Solving Jigsaw Puzzles By the Graph Connection Laplacian. CoRR abs/1811.03188 (2018) - 2017
- [j12]Ery Arias-Castro, Gilad Lerman, Teng Zhang:
Spectral Clustering Based on Local PCA. J. Mach. Learn. Res. 18: 9:1-9:57 (2017) - [i16]Vahan Huroyan, Gilad Lerman:
Distributed Robust Subspace Recovery. CoRR abs/1705.09382 (2017) - [i15]Tyler Maunu, Teng Zhang, Gilad Lerman:
A Well-Tempered Landscape for Non-convex Robust Subspace Recovery. CoRR abs/1706.03896 (2017) - [i14]Gilad Lerman, Yunpeng Shi, Teng Zhang:
Exact Camera Location Recovery by Least Unsquared Deviations. CoRR abs/1709.09683 (2017) - 2016
- [j11]Bryan Poling, Gilad Lerman:
Enhancing feature tracking with gyro regularization. Image Vis. Comput. 50: 42-58 (2016) - 2015
- [j10]Gilad Lerman, Michael B. McCoy, Joel A. Tropp, Teng Zhang:
Robust Computation of Linear Models by Convex Relaxation. Found. Comput. Math. 15(2): 363-410 (2015) - [c10]Xu Wang, Konstantinos Slavakis, Gilad Lerman:
Multi-Manifold Modeling in Non-Euclidean spaces. AISTATS 2015 - [i13]Bryan Poling, Gilad Lerman:
Enhancing Feature Tracking With Gyro Regularization. CoRR abs/1511.01508 (2015) - 2014
- [j9]Bryan Poling, Gilad Lerman:
A New Approach to Two-View Motion Segmentation Using Global Dimension Minimization. Int. J. Comput. Vis. 108(3): 165-185 (2014) - [j8]Teng Zhang, Gilad Lerman:
A novel M-estimator for robust PCA. J. Mach. Learn. Res. 15(1): 749-808 (2014) - [c9]John Goes, Teng Zhang, Raman Arora, Gilad Lerman:
Robust Stochastic Principal Component Analysis. AISTATS 2014: 266-274 - [c8]Bryan Poling, Gilad Lerman, Arthur Szlam:
Better Feature Tracking through Subspace Constraints. CVPR 2014: 3454-3461 - [i12]Bryan Poling, Gilad Lerman, Arthur Szlam:
Better Feature Tracking Through Subspace Constraints. CoRR abs/1405.2316 (2014) - [i11]Gilad Lerman, Tyler Maunu:
Fast algorithm for robust subspace recovery. CoRR abs/1406.6145 (2014) - [i10]Xu Wang, Konstantinos Slavakis, Gilad Lerman:
Riemannian Multi-Manifold Modeling. CoRR abs/1410.0095 (2014) - 2013
- [j7]Yi Wang, Arthur Szlam, Gilad Lerman:
Robust Locally Linear Analysis with Applications to Image Denoising and Blind Inpainting. SIAM J. Imaging Sci. 6(1): 526-562 (2013) - [c7]Xu Wang, Stefan Atev, John Wright, Gilad Lerman:
Fast Subspace Search via Grassmannian Based Hashing. ICCV 2013: 2776-2783 - [i9]Bryan Poling, Gilad Lerman:
A New Approach To Two-View Motion Segmentation Using Global Dimension Minimization. CoRR abs/1304.2999 (2013) - 2012
- [j6]Teng Zhang, Arthur Szlam, Yi Wang, Gilad Lerman:
Hybrid Linear Modeling via Local Best-Fit Flats. Int. J. Comput. Vis. 100(3): 217-240 (2012) - [c6]Matthew Coudron, Gilad Lerman:
On the Sample Complexity of Robust PCA. NIPS 2012: 3230-3238 - [i8]Gilad Lerman, Michael B. McCoy, Joel A. Tropp, Teng Zhang:
Robust computation of linear models, or How to find a needle in a haystack. CoRR abs/1202.4044 (2012) - 2010
- [c5]Yi Ma, Fei Sha, Lawrence Carin, Gilad Lerman, Neil D. Lawrence:
Invited Talk Abstracts. AAAI Fall Symposium: Manifold Learning and Its Applications 2010 - [c4]Teng Zhang, Arthur Szlam, Yi Wang, Gilad Lerman:
Randomized hybrid linear modeling by local best-fit flats. CVPR 2010: 1927-1934 - [i7]Teng Zhang, Arthur Szlam, Yi Wang, Gilad Lerman:
Randomized hybrid linear modeling by local best-fit flats. CoRR abs/1005.0858 (2010) - [i6]Teng Zhang, Arthur Szlam, Yi Wang, Gilad Lerman:
Hybrid Linear Modeling via Local Best-fit Flats. CoRR abs/1010.3460 (2010) - [i5]Gilad Lerman, Teng Zhang:
lp-Recovery of the Most Significant Subspace among Multiple Subspaces with Outliers. CoRR abs/1012.4116 (2010)
2000 – 2009
- 2009
- [j5]Guangliang Chen, Gilad Lerman:
Foundations of a Multi-way Spectral Clustering Framework for Hybrid Linear Modeling. Found. Comput. Math. 9(5): 517-558 (2009) - [j4]Guangliang Chen, Gilad Lerman:
Spectral Curvature Clustering (SCC). Int. J. Comput. Vis. 81(3): 317-330 (2009) - [j3]Gilad Lerman, J. Tyler Whitehouse:
On d-dimensional d-semimetrics and simplex-type inequalities for high-dimensional sine functions. J. Approx. Theory 156(1): 52-81 (2009) - [c3]Teng Zhang, Arthur Szlam, Gilad Lerman:
Median K-Flats for hybrid linear modeling with many outliers. ICCV Workshops 2009: 234-241 - [c2]Guangliang Chen, Gilad Lerman:
Motion segmentation by SCC on the hopkins 155 database. ICCV Workshops 2009: 759-764 - [c1]Guangliang Chen, Stefan Atev, Gilad Lerman:
Kernel Spectral Curvature Clustering (KSCC). ICCV Workshops 2009: 765-772 - [i4]Guangliang Chen, Stefan Atev, Gilad Lerman:
Kernel Spectral Curvature Clustering (KSCC). CoRR abs/0909.1605 (2009) - [i3]Guangliang Chen, Gilad Lerman:
Motion Segmentation by SCC on the Hopkins 155 Database. CoRR abs/0909.1608 (2009) - [i2]Teng Zhang, Arthur Szlam, Gilad Lerman:
Median K-flats for hybrid linear modeling with many outliers. CoRR abs/0909.3123 (2009) - 2007
- [j2]Gilad Lerman, Joseph McQuown, Alexandre Blais, Brian D. Dynlacht, Guangliang Chen, Bud Mishra:
Functional genomics via multiscale analysis: application to gene expression and ChIP-on-chip data. Bioinform. 23(3): 314-320 (2007)
1990 – 1999
- 1999
- [i1]Marshall W. Bern, David Eppstein, Pankaj K. Agarwal, Nina Amenta, L. Paul Chew, Tamal K. Dey, David P. Dobkin, Herbert Edelsbrunner, Cindy Grimm, Leonidas J. Guibas, John Harer, Joel Hass, Andrew Hicks, Carroll K. Johnson, Gilad Lerman, David Letscher, Paul E. Plassmann, Eric Sedgwick, Jack Snoeyink, Jeff Weeks, Chee-Keng Yap, Denis Zorin:
Emerging Challenges in Computational Topology. CoRR cs.CG/9909001 (1999) - 1998
- [j1]Gilad Lerman, Zeev Schuss:
Asymptotic Theory of Large Deviations for Markov Chains. SIAM J. Appl. Math. 58(6): 1862-1877 (1998)
Coauthor Index
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