40 citations · 50 across the 5 of their papers we have counts for
5 papers
Stochastic Gradient Made Stable: A Manifold Propagation Approach for Large-Scale Optimization
Yadong Mu, Wei Liu, Wei Fan
Stochastic gradient descent (SGD) holds as a classical method to build large scale machine learning models over big data. A stochastic gradient is typically calculated from a limit…
Stochastic Coordinate Coding and Its Application for Drosophila Gene Expression Pattern Annotation
Binbin Lin, Qingyang Li, Qian Sun +4
\textit{Drosophila melanogaster} has been established as a model organism for investigating the fundamental principles of developmental gene interactions. The gene expression patte…
Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion
Zheng Wang, Ming-Jun Lai, Zhaosong Lu +3
In this paper, we propose an efficient and scalable low rank matrix completion algorithm. The key idea is to extend orthogonal matching pursuit method from the vector case to the m…
Generalization Bounds for Representative Domain Adaptation
Chao Zhang, Lei Zhang, Wei Fan +1
In this paper, we propose a novel framework to analyze the theoretical properties of the learning process for a representative type of domain adaptation, which combines data from m…
Multilabel Consensus Classification
Sihong Xie, Xiangnan Kong, Jing Gao +2
In the era of big data, a large amount of noisy and incomplete data can be collected from multiple sources for prediction tasks. Combining multiple models or data sources helps to…