61 citations · 84 across the 5 of their papers we have counts for
5 papers
A New Analysis of Compressive Sensing by Stochastic Proximal Gradient Descent
Rong Jin, Tianbao Yang, Shenghuo Zhu
In this manuscript, we analyze the sparse signal recovery (compressive sensing) problem from the perspective of convex optimization by stochastic proximal gradient descent. This vi…
Efficient Distance Metric Learning by Adaptive Sampling and Mini-Batch Stochastic Gradient Descent (SGD)
Qi Qian, Rong Jin, Jinfeng Yi +2
Distance metric learning (DML) is an important task that has found applications in many domains. The high computational cost of DML arises from the large number of variables to be…
Large Scale Strongly Supervised Ensemble Metric Learning, with Applications to Face Verification and Retrieval
Chang Huang, Shenghuo Zhu, Kai Yu
Learning Mahanalobis distance metrics in a high- dimensional feature space is very difficult especially when structural sparsity and low rank are enforced to improve com- putationa…
Influence Analysis in the Blogosphere
Michinari Momma, Yun Chi, Yuanqing Lin +2
In this paper we analyze influence in the blogosphere. Recently, influence analysis has become an increasingly important research topic, as online communities, such as social netwo…
A short note on the tail bound of Wishart distribution
Shenghuo Zhu
We study the tail bound of the emperical covariance of multivariate normal distribution. Following the work of (Gittens & Tropp, 2011), we provide a tail bound with a small constan…