97 citations · 122 across the 4 of their papers we have counts for
4 papers
Gaussian Process Inference Using Mini-batch Stochastic Gradient Descent: Convergence Guarantees and Empirical Benefits
Hao Chen, Lili Zheng, Raed Al Kontar +1
Stochastic gradient descent (SGD) and its variants have established themselves as the go-to algorithms for large-scale machine learning problems with independent samples due to the…
Structure Parameter Optimized Kernel Based Online Prediction with a Generalized Optimization Strategy for Nonstationary Time Series
Jinhua Guo, Hao Chen, Jingxin Zhang +1
In this paper, sparsification techniques aided online prediction algorithms in a reproducing kernel Hilbert space are studied for nonstationary time series. The online prediction a…
Process monitoring based on orthogonal locality preserving projection with maximum likelihood estimation
Jingxin Zhang, Maoyin Chen, Hao Chen +2
By integrating two powerful methods of density reduction and intrinsic dimensionality estimation, a new data-driven method, referred to as OLPP-MLE (orthogonal locality preserving…
An improved mixture of probabilistic PCA for nonlinear data-driven process monitoring
Jingxin Zhang, Hao Chen, Songhang Chen +1
An improved mixture of probabilistic principal component analysis (PPCA) has been introduced for nonlinear data-driven process monitoring in this paper. To realize this purpose, th…