subspace-learning

Oja and implicit Krasulina approaches to batched approximate top-k PCA estimation.

[NeurIPS 2026] Machine Unlearning in Low-Dimensional Feature Subspace

Subspace Learning in Domain Adaptation with PCA

[ICCV 2025] Estimating 2D Camera Motion with Hybrid Motion Basis

Ellipsoidal Subspace Support Vector Data Description

A novel dynamic learning strategy that overcomes the empirical search of an optimal number of subspace learners in multiple metric learners.

source code for SDSPCAAN

The code for prototype selection and instance ranking using matrix decomposition and subspace learning

We implement some sparse representation based face recognition algorithms here, including LRC, SRC, CRC, ESRC and etc.

We propose a global and local feature transformation method for PRID. The global feature transformation matrix projects the data from different cameras to a common space. We further hypothesize that a latent basis matrix can be learnt in this space which represents the shared structure between different cameras using matrix factorization.

Subspaces in Python!

Subspace Support Vector Data Description

Multimodal Subspace Support Vector Data Description

models/scripts for subspace learning written in MATLAB (2018 Yau Award CS Bronze)

Data Augmented Flatness-aware Gradient Projection for Continual Learning. ICCV, 2023.

We use self-expressive layer to learn the affinity matrix of the hidden space of a generator, and we found subspace in GAN. Also we propsed a subspace-based high-fidelity GAN inversion model.

MATLAB implementation of "Federated Over-Air Subspace Tracking from Incomplete and Corrupted Data", IEEE Transactions on Signal Processing, Jun 2022.

Matlab implementation of L0 motivated low-rank sparse subspace clustering

Dual Shared-Specific Multiview Subspace Clustering

MATLAB implementation of "Nearly Optimal Robust Subspace Tracking", ICML 2018. Longer version to appear in IEEE Journal of Selected Areas in Information Theory, 2020.