163 citations · 1.6k across the 92 of their papers we have counts for
9 papers · 1 filter
A Simple Homotopy Proximal Mapping for Compressive Sensing
Tianbao Yang, Lijun Zhang, Rong Jin +2
In this paper, we present a novel yet simple homotopy proximal mapping algorithm for compressive sensing. The algorithm adopts a simple proximal mapping of the norm at eac…
CUR Algorithm for Partially Observed Matrices
Miao Xu, Rong Jin, Zhi-Hua Zhou
CUR matrix decomposition computes the low rank approximation of a given matrix by using the actual rows and columns of the matrix. It has been a very useful tool for handling large…
Top Rank Optimization in Linear Time
Nan Li, Rong Jin, Zhi-Hua Zhou
Bipartite ranking aims to learn a real-valued ranking function that orders positive instances before negative instances. Recent efforts of bipartite ranking are focused on optimizi…
On Data Preconditioning for Regularized Loss Minimization
Tianbao Yang, Rong Jin, Shenghuo Zhu +1
In this work, we study data preconditioning, a well-known and long-existing technique, for boosting the convergence of first-order methods for regularized loss minimization. It is…
CUR Algorithm with Incomplete Matrix Observation
Rong Jin, Shenghuo Zhu
CUR matrix decomposition is a randomized algorithm that can efficiently compute the low rank approximation for a given rectangle matrix. One limitation with the existing CUR algori…
Scalable Kernel Clustering: Approximate Kernel k-means
Radha Chitta, Rong Jin, Timothy C. Havens +1
Kernel-based clustering algorithms have the ability to capture the non-linear structure in real world data. Among various kernel-based clustering algorithms, kernel k-means has gai…