My research in machine learning concerns its applications to computer vision tasks:

1. Subspace Learning (Model-based methods)

• • Subspace Learning (Subspace Learning Research/Website)

  • Robust Subspace Learning via decomposition into low-rank and sparse matrices or tensors (DLAM/DLAT Research/Website).

  • Dynamic Subspace Learning via decomposition into low-rank and sparse matrices or tensors (DLAM/DLAT Research/Website)

2. Deep Learning (Data-based Methods)

• • Supervised DeepSphere

  • Unsupervised GANs

  • Graph Neural Networks

A) SUBSPACE LEARNING (MODEL-BASED METHODS) (UNSUPERVISED/SUPERVISED METHODS)

A.1) Eigenvector Models (Gaussian, Laplacian, etc.)

A.2) Low-Rank Models 

A.3) Sparse Models

B) DEEP NEURAL NETWORKS (DATA-BASED MODELS) (SUPERVISED/SEMI-SUPERVISED METHODS)