101 citations · 105 across the 5 of their papers we have counts for
5 papers
Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data
Bin Gu, Zhiyuan Dang, Xiang Li +1
In a lot of real-world data mining and machine learning applications, data are provided by multiple providers and each maintains private records of different feature sets about com…
Safe Sample Screening for Robust Support Vector Machine
Zhou Zhai, Bin Gu, Xiang Li +1
Robust support vector machine (RSVM) has been shown to perform remarkably well to improve the generalization performance of support vector machine under the noisy environment. Unfo…
Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization
Wanli Shi, Bin Gu, Xiang Li +2
Semi-supervised learning is pervasive in real-world applications, where only a few labeled data are available and large amounts of instances remain unlabeled. Since AUC is an impor…
Scalable Semi-Supervised SVM via Triply Stochastic Gradients
Xiang Geng, Bin Gu, Xiang Li +3
Semi-supervised learning (SSL) plays an increasingly important role in the big data era because a large number of unlabeled samples can be used effectively to improve the performan…
Pelee: A Real-Time Object Detection System on Mobile Devices
Robert J. Wang, Xiang Li, Charles X. Ling
An increasing need of running Convolutional Neural Network (CNN) models on mobile devices with limited computing power and memory resource encourages studies on efficient model des…