78 citations · 190 across the 13 of their papers we have counts for
13 papers
A Statistical Learning Assessment of Huber Regression
Yunlong Feng, Qiang Wu
As one of the triumphs and milestones of robust statistics, Huber regression plays an important role in robust inference and estimation. It has also been finding a great variety of…
A Framework of Learning Through Empirical Gain Maximization
Yunlong Feng, Qiang Wu
We develop in this paper a framework of empirical gain maximization (EGM) to address the robust regression problem where heavy-tailed noise or outliers may present in the response…
Optimal Rates of Distributed Regression with Imperfect Kernels
Hongwei Sun, Qiang Wu
Distributed machine learning systems have been receiving increasing attentions for their efficiency to process large scale data. Many distributed frameworks have been proposed for…
Model Adaptation via Model Interpolation and Boosting for Web Search Ranking
Jianfeng Gao, Qiang Wu, Chris Burges +5
This paper explores two classes of model adaptation methods for Web search ranking: Model Interpolation and error-driven learning approaches based on a boosting algorithm. The resu…
Overlapping Sliced Inverse Regression for Dimension Reduction
Ning Zhang, Zhou Yu, Qiang Wu
Sliced inverse regression (SIR) is a pioneer tool for supervised dimension reduction. It identifies the effective dimension reduction space, the subspace of significant factors wit…
Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network
Zhengchu Guo, Lei Shi, Qiang Wu
Distributed learning is an effective way to analyze big data. In distributed regression, a typical approach is to divide the big data into multiple blocks, apply a base regression…