7 citations · 14 across the 6 of their papers we have counts for
6 papers
Subset Node Representation Learning over Large Dynamic Graphs
Xingzhi Guo, Baojian Zhou, Steven Skiena
Dynamic graph representation learning is a task to learn node embeddings over dynamic networks, and has many important applications, including knowledge graphs, citation networks t…
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 Quadratic Programming Relaxation Approach to Compute-and-Forward Network Coding Design
Baojian Zhou, Jinming Wen, Wai Ho Mow
Using physical layer network coding, compute-and-forward is a promising relaying scheme that effectively exploits the interference between users and thus achieves high rates. In th…