767 citations · 4.4k across the 70 of their papers we have counts for
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Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets
Jie Wang, Jieping Ye
Sparse-Group Lasso (SGL) has been shown to be a powerful regression technique for simultaneously discovering group and within-group sparse patterns by using a combination of the $\…
Persistent Homology in Sparse Regression and its Application to Brain Morphometry
Moo K. Chung, Jamie L. Hanson, Jieping Ye +2
Sparse systems are usually parameterized by a tuning parameter that determines the sparsity of the system. How to choose the right tuning parameter is a fundamental and difficult p…
Stochastic Coordinate Coding and Its Application for Drosophila Gene Expression Pattern Annotation
Binbin Lin, Qingyang Li, Qian Sun +4
\textit{Drosophila melanogaster} has been established as a model organism for investigating the fundamental principles of developmental gene interactions. The gene expression patte…
Linear Convergence of Variance-Reduced Stochastic Gradient without Strong Convexity
Pinghua Gong, Jieping Ye
Stochastic gradient algorithms estimate the gradient based on only one or a few samples and enjoy low computational cost per iteration. They have been widely used in large-scale op…
Geodesic Distance Function Learning via Heat Flow on Vector Fields
Binbin Lin, Ji Yang, Xiaofei He +1
Learning a distance function or metric on a given data manifold is of great importance in machine learning and pattern recognition. Many of the previous works first embed the manif…
Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion
Zheng Wang, Ming-Jun Lai, Zhaosong Lu +3
In this paper, we propose an efficient and scalable low rank matrix completion algorithm. The key idea is to extend orthogonal matching pursuit method from the vector case to the m…