70 citations · 560 across the 53 of their papers we have counts for
5 papers · 1 filter
A Simple Analysis for Exp-concave Empirical Minimization with Arbitrary Convex Regularizer
Tianbao Yang, Zhe Li, Lijun Zhang
In this paper, we present a simple analysis of {\bf fast rates} with {\it high probability} of {\bf empirical minimization} for {\it stochastic composite optimization} over a finit…
Learning with Feature Evolvable Streams
Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou
Learning with streaming data has attracted much attention during the past few years. Though most studies consider data stream with fixed features, in real practice the features may…
Empirical Risk Minimization for Stochastic Convex Optimization: - and -type of Risk Bounds
Lijun Zhang, Tianbao Yang, Rong Jin
Although there exist plentiful theories of empirical risk minimization (ERM) for supervised learning, current theoretical understandings of ERM for a related problem---stochastic c…
Scalable Demand-Aware Recommendation
Jinfeng Yi, Cho-Jui Hsieh, Kush Varshney +2
Recommendation for e-commerce with a mix of durable and nondurable goods has characteristics that distinguish it from the well-studied media recommendation problem. The demand for…
Dynamic Regret of Strongly Adaptive Methods
Lijun Zhang, Tianbao Yang, Rong Jin +1
To cope with changing environments, recent developments in online learning have introduced the concepts of adaptive regret and dynamic regret independently. In this paper, we illus…