Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Mankovich, Nathan"'
We consider the coding problem in the Stiefel manifold with chordal distance. After considering various low-dimensional instances of this problem, we use Rankin's bounds on spherical codes to prove upper bounds on the minimum distance of a Stiefel co
Externí odkaz:
http://arxiv.org/abs/2407.01813
Detecting latent confounders from proxy variables is an essential problem in causal effect estimation. Previous approaches are limited to low-dimensional proxies, sorted proxies, and binary treatments. We remove these assumptions and present a novel
Externí odkaz:
http://arxiv.org/abs/2403.14228
We introduce a causal regularisation extension to anchor regression (AR) for improved out-of-distribution (OOD) generalisation. We present anchor-compatible losses, aligning with the anchor framework to ensure robustness against distribution shifts.
Externí odkaz:
http://arxiv.org/abs/2403.01865
Principal component analysis (PCA), along with its extensions to manifolds and outlier contaminated data, have been indispensable in computer vision and machine learning. In this work, we present a unifying formalism for PCA and its variants, and int
Externí odkaz:
http://arxiv.org/abs/2401.04071
This article introduces an advanced Koopman mode decomposition (KMD) technique -- coined Featurized Koopman Mode Decomposition (FKMD) -- that uses delay embedding and a learned Mahalanobis distance to enhance analysis and prediction of high dimension
Externí odkaz:
http://arxiv.org/abs/2312.09146
Autor:
Mankovich, Nathan, Birdal, Tolga
This paper presents a new, provably-convergent algorithm for computing the flag-mean and flag-median of a set of points on a flag manifold under the chordal metric. The flag manifold is a mathematical space consisting of flags, which are sequences of
Externí odkaz:
http://arxiv.org/abs/2303.13501
Finding prototypes (e.g., mean and median) for a dataset is central to a number of common machine learning algorithms. Subspaces have been shown to provide useful, robust representations for datasets of images, videos and more. Since subspaces corres
Externí odkaz:
http://arxiv.org/abs/2203.04437
Publikováno v:
Journal of Chemical Physics; 8/14/2024, Vol. 161 Issue 6, p1-11, 11p
The sketch-and-project (SAP) framework for solving systems of linear equations has unified the theory behind popular projective iterative methods such as randomized Kaczmarz, randomized coordinate descent, and variants thereof. The randomized extende
Externí odkaz:
http://arxiv.org/abs/2110.05605
Autor:
Mankovich, Nathan1 (AUTHOR) nathan.mankovich@gmail.com, Kehoe, Eric1 (AUTHOR), Peterson, Amy1 (AUTHOR), Kirby, Michael1 (AUTHOR)
Publikováno v:
Scientific Reports. 12/17/2022, Vol. 12 Issue 1, p1-13. 13p.