Source Themes

k-Factorization Subspace Clustering

Low-Rank Tensor Recovery with Euclidean-Norm-Induced Schatten-p Quasi-Norm Regularization

AutoML Pipeline Selection: Efficiently Navigating the Combinatorial Space

$k$FW: A Frank-Wolfe style algorithm with stronger subproblem oracles

Efficient AutoML Pipeline Search with Matrix and Tensor Factorization

Robust Non-Linear Matrix Factorization for Dictionary Learning, Denoising, and Clustering

Polynomial Matrix Completion for Missing Data Imputation and Transductive Learning

This paper develops new methods to recover the missing entries of a high-rank or even full-rank matrix when the intrinsic dimension of the data is low compared to the ambient dimension. Specifically, we assume that the columns of a matrix are …

Factor group sparse regularization for efficient low-rank matrix recovery

This paper develops a new class of nonconvex regularizers for low-rank matrix recovery. Many regularizers are motivated as convex relaxations of the matrix rank function. Our new factor group-sparse regularizers are motivated as a relaxation of the …