9 citations · 19 across the 4 of their papers we have counts for
4 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…
O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions
Lijun Zhang, Tianbao Yang, Rong Jin +1
Traditional algorithms for stochastic optimization require projecting the solution at each iteration into a given domain to ensure its feasibility. When facing complex domains, suc…
Sparse Multiple Kernel Learning with Geometric Convergence Rate
Rong Jin, Tianbao Yang, Mehrdad Mahdavi
In this paper, we study the problem of sparse multiple kernel learning (MKL), where the goal is to efficiently learn a combination of a fixed small number of kernels from a large p…
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…