arXiv Machine Learning July 10, 2026 By Zhiwei Han, Stefan Matthes, Hao Shen

Provable Subspace Identification of Nonlinear Multi-view CCA

Read the original on arXiv Machine Learning →

arXiv:2602. 23785v2 Announce Type: replace Abstract: We investigate the identifiability of nonlinear canonical correlation analysis (CCA) in a multi-view setup, in which each view is generated by applying an unknown nonlinear map to a linear mixture of shared latent variables plus view-private noise.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning

Jul 9

Provable Affine Identifiability of Nonlinear CCA under Latent Distributional Priors

arXiv:2510. 04758v3 Announce Type: replace Abstract: In this work, we establish the sufficient conditions under which nonlinear Canonical Correlation Analysis (CCA) recovers ground-truth latent factors up to an affine transformation.

By Zhiwei Han, Stefan Matthes, Hao Shen

arXiv Machine Learning

Jun 30

Nonlinear mixture model motivated subspace clustering

arXiv:2606. 29261v1 Announce Type: new Abstract: We derive the linear union-of-subspaces (UoS) model for subspace clustering (SC) from the nonlinear mixture model (NMM) used in blind source separation (BSS) to represent a D-dimensional observation vector as an unknown multivariate nonlinear mapping of C latent variables.

By Ivica Kopriva

efficiency benchmarks

arXiv AI

Jun 3

Exact Stiefel Optimization for Probabilistic PLS: Closed-Form Updates, Error Bounds, and Calibrated Uncertainty

arXiv:2605. 11607v2 Announce Type: replace-cross Abstract: Probabilistic partial least squares (PPLS) is a central likelihood-based model for two-view learning when one needs both interpretable latent factors and calibrated uncertainty.

By Haoran Hu, Xingce Wang

benchmarks safety

arXiv Machine Learning

Jun 9

Identifiability and Estimation for Unlabeled Finite Mixtures under Marginal Independence

arXiv:2606. 07914v1 Announce Type: cross Abstract: We study component recovery and mixing-matrix estimation from unlabeled finite mixtures whose observable distributions share the same latent components but have unknown mixing weights.

By Takafumi Kanamori, Yushi Hirose, Shohei Yamamoto

arXiv Machine Learning

5d ago

Multiview Representation Learning via Distributed Joint Latent Space Structuring

arXiv:2504. 18455v2 Announce Type: replace-cross Abstract: We study distributed multiview representation learning, a problem in which $K$ clients each observe a distinct but possibly statistically correlated view.

By Milad Sefidgaran, Piotr Krasnowski, Abdellatif Zaidi

diffusion safety

arXiv Machine Learning

1d ago

One-shot Robust Federated Learning of Independent Component Analysis

arXiv:2505. 20532v2 Announce Type: replace Abstract: This paper studies robust one-shot aggregation for distributed and federated Independent Component Analysis (ICA).

By Dian Jin, Xin Bing, Yuqian Zhang

Related stories

Provable Affine Identifiability of Nonlinear CCA under Latent Distributional Priors

Nonlinear mixture model motivated subspace clustering

Exact Stiefel Optimization for Probabilistic PLS: Closed-Form Updates, Error Bounds, and Calibrated Uncertainty

Identifiability and Estimation for Unlabeled Finite Mixtures under Marginal Independence

Multiview Representation Learning via Distributed Joint Latent Space Structuring

One-shot Robust Federated Learning of Independent Component Analysis