22 citations · 41 across the 16 of their papers we have counts for
7 papers · 1 filter
Fast Online Node Labeling for Very Large Graphs
Baojian Zhou, Yifan Sun, Reza Babanezhad
This paper studies the online node classification problem under a transductive learning setting. Current methods either invert a graph kernel matrix with runtime…
Stochastic Hard Thresholding Algorithms for AUC Maximization
Zhenhuan Yang, Baojian Zhou, Yunwen Lei +1
In this paper, we aim to develop stochastic hard thresholding algorithms for the important problem of AUC maximization in imbalanced classification. The main challenge is the pairw…
Online AUC Optimization for Sparse High-Dimensional Datasets
Baojian Zhou, Yiming Ying, Steven Skiena
The Area Under the ROC Curve (AUC) is a widely used performance measure for imbalanced classification arising from many application domains where high-dimensional sparse data is ab…
Dual Averaging Method for Online Graph-structured Sparsity
Baojian Zhou, Feng Chen, Yiming Ying
Online learning algorithms update models via one sample per iteration, thus efficient to process large-scale datasets and useful to detect malicious events for social benefits, suc…
Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization
Baojian Zhou, Feng Chen, Yiming Ying
Stochastic optimization algorithms update models with cheap per-iteration costs sequentially, which makes them amenable for large-scale data analysis. Such algorithms have been wid…
A Generic Framework for Interesting Subspace Cluster Detection in Multi-attributed Networks
Feng Chen, Baojian Zhou, Adil Alim +1
Detection of interesting (e.g., coherent or anomalous) clusters has been studied extensively on plain or univariate networks, with various applications. Recently, algorithms have b…
Technical Report: A Generalized Matching Pursuit Approach for Graph-Structured Sparsity
Feng Chen, Baojian Zhou
Sparsity-constrained optimization is an important and challenging problem that has wide applicability in data mining, machine learning, and statistics. In this paper, we focus on s…