155 citations · 1.6k across the 76 of their papers we have counts for
13 papers · 1 filter
Recovery Theory for Projected Power Iterations in Permutation Synchronization
Vahan Huroyan, Gilad Lerman
We study the projected power method (PPM) for synchronizing \(n\) unknown permutations of \(m\) objects under a possibly sparse uniform corruption model. Each pair is observed with…
Global Convergence of Iteratively Reweighted Least Squares for Robust Subspace Recovery
Gilad Lerman, Kang Li, Tyler Maunu +1
Robust subspace estimation is fundamental to many machine learning and data analysis tasks. Iteratively Reweighted Least Squares (IRLS) is an elegant and empirically effective appr…
Robust Group Synchronization via Quadratic Programming
Yunpeng Shi, Cole Wyeth, Gilad Lerman
We propose a novel quadratic programming formulation for estimating the corruption levels in group synchronization, and use these estimates to solve this problem. Our objective fun…
Robust Group Synchronization via Cycle-Edge Message Passing
Gilad Lerman, Yunpeng Shi
We propose a general framework for solving the group synchronization problem, where we focus on the setting of adversarial or uniform corruption and sufficiently small noise. Speci…
Fast Landmark Subspace Clustering
Xu Wang, Gilad Lerman
Kernel methods obtain superb performance in terms of accuracy for various machine learning tasks since they can effectively extract nonlinear relations. However, their time complex…
Riemannian Multi-Manifold Modeling
Xu Wang, Konstantinos Slavakis, Gilad Lerman
This paper advocates a novel framework for segmenting a dataset in a Riemannian manifold into clusters lying around low-dimensional submanifolds of . Important examples of $…