17 citations · 59 across the 15 of their papers we have counts for
5 papers · 1 filter
Robust Unsupervised Multi-task and Transfer Learning on Gaussian Mixture Models
Ye Tian, Haolei Weng, Lucy Xia +1
Unsupervised learning has been widely used in many real-world applications. One of the simplest and most important unsupervised learning models is the Gaussian mixture model (GMM).…
Transfer Learning under High-dimensional Generalized Linear Models
Ye Tian, Yang Feng
In this work, we study the transfer learning problem under high-dimensional generalized linear models (GLMs), which aim to improve the fit on target data by borrowing information f…
Machine Collaboration
Qingfeng Liu, Yang Feng
We propose a new ensemble framework for supervised learning, called machine collaboration (MaC), using a collection of base machines for prediction tasks. Unlike bagging/stacking (…
Spectral clustering via adaptive layer aggregation for multi-layer networks
Sihan Huang, Haolei Weng, Yang Feng
One of the fundamental problems in network analysis is detecting community structure in multi-layer networks, of which each layer represents one type of edge information among the…
RaSE: Random Subspace Ensemble Classification
Ye Tian, Yang Feng
We propose a flexible ensemble classification framework, Random Subspace Ensemble (RaSE), for sparse classification. In the RaSE algorithm, we aggregate many weak learners, where e…