23 citations · 35 across the 5 of their papers we have counts for
5 papers
Certifying optimality in nonconvex robust PCA
Pinxi Gong, Lexiao Lai, Jianhao Ma
Robust principal component analysis seeks to recover a low-rank matrix from fully observed data with sparse corruptions. A scalable approach fits a low-rank factorization by minimi…
Rotation Equivariance and Invariance in Convolutional Neural Networks
Benjamin Chidester, Minh N. Do, Jian Ma
Performance of neural networks can be significantly improved by encoding known invariance for particular tasks. Many image classification tasks, such as those related to cellular i…
Correlating Cellular Features with Gene Expression using CCA
Vaishnavi Subramanian, Benjamin Chidester, Jian Ma +1
To understand the biology of cancer, joint analysis of multiple data modalities, including imaging and genomics, is crucial. The involved nature of gene-microenvironment interactio…
On the Reconstruction Risk of Convolutional Sparse Dictionary Learning
Shashank Singh, Barnabás Póczos, Jian Ma
Sparse dictionary learning (SDL) has become a popular method for adaptively identifying parsimonious representations of a dataset, a fundamental problem in machine learning and sig…
Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex Optimizations
Pan Xu, Jian Ma, Quanquan Gu
We study the estimation of the latent variable Gaussian graphical model (LVGGM), where the precision matrix is the superposition of a sparse matrix and a low-rank matrix. In order…