Gilad Lerman

According to our database, Gilad Lerman authored at least 63 papers between 1998 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Spectrally Constrained Optimization.

Casey Garner, Gilad Lerman, Shuzhong Zhang

J. Sci. Comput., September, 2024

Tensor-Based Synchronization and the Low-Rankness of the Block Trifocal Tensor.

Daniel Miao, Gilad Lerman, Joe Kileel

CoRR, 2024

Artificial Intelligence and Algorithmic Price Collusion in Two-sided Markets.

Cristian Chica, Yinglong Guo, Gilad Lerman

CoRR, 2024

Improving Hyperbolic Representations via Gromov-Wasserstein Regularization.

Yifei Yang, Wonjun Lee, Dongmian Zou, Gilad Lerman

Proceedings of the Computer Vision - ECCV 2024, 2024

A Subspace-Constrained Tyler's Estimator and its Applications to Structure from Motion.

Feng Yu, Teng Zhang, Gilad Lerman

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Efficient Detection of Long Consistent Cycles and its Application to Distributed Synchronization.

Shaohan Li, Yunpeng Shi, Gilad Lerman

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

The effect of Leaky ReLUs on the training and generalization of overparameterized networks.

Yinglong Guo, Shaohan Li, Gilad Lerman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Depth Descent Synchronization in ${{\,\mathrm{\text {SO}}\,}}(D)$.

Tyler Maunu, Gilad Lerman

Int. J. Comput. Vis., April, 2023

Improved Convergence Rates of Anderson Acceleration for a Large Class of Fixed-Point Iterations.

Casey Garner, Gilad Lerman, Teng Zhang

CoRR, 2023

Monotone Generative Modeling via a Gromov-Monge Embedding.

Wonjun Lee, Yifei Yang, Dongmian Zou, Gilad Lerman

CoRR, 2023

Robust Variational Autoencoding with Wasserstein Penalty for Novelty Detection.

Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

An Unpooling Layer for Graph Generation.

Yinglong Guo, Dongmian Zou, Gilad Lerman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Robust Group Synchronization via Cycle-Edge Message Passing.

Gilad Lerman, Yunpeng Shi

Found. Comput. Math., 2022

Cubic-Regularized Newton for Spectral Constrained Matrix Optimization and its Application to Fairness.

Casey Garner, Gilad Lerman, Shuzhong Zhang

CoRR, 2022

Stochastic and Private Nonconvex Outlier-Robust PCA.

Tyler Maunu, Chenyu Yu, Gilad Lerman

CoRR, 2022

Stochastic and Private Nonconvex Outlier-Robust PCAs.

Tyler Maunu, Chenyu Yu, Gilad Lerman

Proceedings of the Mathematical and Scientific Machine Learning, 2022

Robust Group Synchronization via Quadratic Programming.

Yunpeng Shi, Cole M. Wyeth, Gilad Lerman

Proceedings of the International Conference on Machine Learning, 2022

Fast, Accurate and Memory-Efficient Partial Permutation Synchronization.

Shaohan Li, Yunpeng Shi, Gilad Lerman

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Scalable Cluster-Consistency Statistics for Robust Multi-Object Matching.

Yunpeng Shi, Shaohan Li, Tyler Maunu, Gilad Lerman

Proceedings of the International Conference on 3D Vision, 2021

2020

Solving Jigsaw Puzzles by the Graph Connection Laplacian.

Vahan Huroyan, Gilad Lerman, Hau-Tieng Wu

SIAM J. Imaging Sci., 2020

Novelty Detection via Robust Variational Autoencoding.

Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman

CoRR, 2020

A Provably Robust Multiple Rotation Averaging Scheme for SO(2).

Tyler Maunu, Gilad Lerman

CoRR, 2020

Robust Multi-Object Matching via Iterative Reweighting of the Graph Connection Laplacian.

Yunpeng Shi, Shaohan Li, Gilad Lerman

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Message Passing Least Squares Framework and its Application to Rotation Synchronization.

Yunpeng Shi, Gilad Lerman

Proceedings of the 37th International Conference on Machine Learning, 2020

Robust Subspace Recovery Layer for Unsupervised Anomaly Detection.

Chieh-Hsin Lai, Dongmian Zou, Gilad Lerman

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

A Well-Tempered Landscape for Non-convex Robust Subspace Recovery.

Tyler Maunu, Teng Zhang, Gilad Lerman

J. Mach. Learn. Res., 2019

Robust Subspace Recovery with Adversarial Outliers.

Tyler Maunu, Gilad Lerman

CoRR, 2019

Algorithms for 𝓁_p-based semi-supervised learning on graphs.

Mauricio Flores Rios, Jeff Calder, Gilad Lerman

CoRR, 2019

Encoding robust representation for graph generation.

Dongmian Zou, Gilad Lerman

Proceedings of the International Joint Conference on Neural Networks, 2019

2018

Distributed Robust Subspace Recovery.

Vahan Huroyan, Gilad Lerman

SIAM J. Sci. Comput., 2018

Exact Camera Location Recovery by Least Unsquared Deviations.

Gilad Lerman, Yunpeng Shi, Teng Zhang

SIAM J. Imaging Sci., 2018

An Overview of Robust Subspace Recovery.

Gilad Lerman, Tyler Maunu

Proc. IEEE, 2018

Graph Generation via Scattering.

Dongmian Zou, Gilad Lerman

CoRR, 2018

Phase transition in random tensors with multiple spikes.

Wei-Kuo Chen, Madeline Handschy, Gilad Lerman

CoRR, 2018

Graph Convolutional Neural Networks via Scattering.

Dongmian Zou, Gilad Lerman

CoRR, 2018

Estimation of Camera Locations in Highly Corrupted Scenarios: All About That Base, No Shape Trouble.

Yunpeng Shi, Gilad Lerman

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Spectral Clustering Based on Local PCA.

Ery Arias-Castro, Gilad Lerman, Teng Zhang

J. Mach. Learn. Res., 2017

2016

Enhancing feature tracking with gyro regularization.

Bryan Poling, Gilad Lerman

Image Vis. Comput., 2016

2015

Robust Computation of Linear Models by Convex Relaxation.

Gilad Lerman, Michael B. McCoy, Joel A. Tropp, Teng Zhang

Found. Comput. Math., 2015

Multi-Manifold Modeling in Non-Euclidean spaces.

Xu Wang, Konstantinos Slavakis, Gilad Lerman

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

A novel M-estimator for robust PCA.

Teng Zhang, Gilad Lerman

J. Mach. Learn. Res., 2014

A New Approach to Two-View Motion Segmentation Using Global Dimension Minimization.

Bryan Poling, Gilad Lerman

Int. J. Comput. Vis., 2014

Riemannian Multi-Manifold Modeling.

Xu Wang, Konstantinos Slavakis, Gilad Lerman

CoRR, 2014

Fast algorithm for robust subspace recovery.

Gilad Lerman, Tyler Maunu

CoRR, 2014

Better Feature Tracking through Subspace Constraints.

Bryan Poling, Gilad Lerman, Arthur Szlam

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

Robust Stochastic Principal Component Analysis.

John Goes, Teng Zhang, Raman Arora, Gilad Lerman

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

Robust Locally Linear Analysis with Applications to Image Denoising and Blind Inpainting.

Yi Wang, Arthur Szlam, Gilad Lerman

SIAM J. Imaging Sci., 2013

Fast Subspace Search via Grassmannian Based Hashing.

Xu Wang, Stefan Atev, John Wright, Gilad Lerman

Proceedings of the IEEE International Conference on Computer Vision, 2013

2012

Hybrid Linear Modeling via Local Best-Fit Flats.

Teng Zhang, Arthur Szlam, Yi Wang, Gilad Lerman

Int. J. Comput. Vis., 2012

Robust computation of linear models, or How to find a needle in a haystack

Gilad Lerman, Michael B. McCoy, Joel A. Tropp, Teng Zhang

CoRR, 2012

On the Sample Complexity of Robust PCA.

Matthew Coudron, Gilad Lerman

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2010

lp-Recovery of the Most Significant Subspace among Multiple Subspaces with Outliers

Gilad Lerman, Teng Zhang

CoRR, 2010

Randomized hybrid linear modeling by local best-fit flats.

Teng Zhang, Arthur Szlam, Yi Wang, Gilad Lerman

Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

Invited Talk Abstracts.

Yi Ma, Fei Sha, Lawrence Carin, Gilad Lerman, Neil D. Lawrence

Proceedings of the Manifold Learning and Its Applications, 2010

2009

On d-dimensional d-semimetrics and simplex-type inequalities for high-dimensional sine functions.

Gilad Lerman, J. Tyler Whitehouse

J. Approx. Theory, 2009

Spectral Curvature Clustering (SCC).

Guangliang Chen, Gilad Lerman

Int. J. Comput. Vis., 2009

Foundations of a Multi-way Spectral Clustering Framework for Hybrid Linear Modeling.

Guangliang Chen, Gilad Lerman

Found. Comput. Math., 2009

Median K-Flats for hybrid linear modeling with many outliers.

Teng Zhang, Arthur Szlam, Gilad Lerman

Proceedings of the 12th IEEE International Conference on Computer Vision Workshops, 2009

Motion segmentation by SCC on the hopkins 155 database.

Guangliang Chen, Gilad Lerman

Proceedings of the 12th IEEE International Conference on Computer Vision Workshops, 2009

Kernel Spectral Curvature Clustering (KSCC).

Guangliang Chen, Stefan Atev, Gilad Lerman

Proceedings of the 12th IEEE International Conference on Computer Vision Workshops, 2009

2007

Functional genomics via multiscale analysis: application to gene expression and ChIP-on-chip data.

Gilad Lerman, Joseph McQuown, Alexandre Blais, Brian D. Dynlacht, Guangliang Chen, Bud Mishra

Bioinform., 2007

1999

Emerging Challenges in Computational Topology

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

CoRR, 1999

1998

Asymptotic Theory of Large Deviations for Markov Chains.

Gilad Lerman, Zeev Schuss

SIAM J. Appl. Math., 1998