Xin Xu, Tao Xie, Dewen Hu, Xicheng Lu, Xin Xu, Tao Xie, ...
Kernel methods have attracted many research interests recently since by utilizing Mercer kernels, non-linear and non-parametric versions of conventional supervised or unsupervised learning algorithms...
Efficient Reinforcement Learning Using Recursire Least-Squares Methods (2007)
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is mainly due to its fast...
A Visual System Theoretic Cost Criterion and Its Application to Clustering (2007)
Shitong Wang, Fu-lai Chung, Min Xu, Zhaohong Deng, Dewen Hu
We all know that our eyes can inherently and effectively recognize/classify objects under complex conditions. Hence, we believe that an efficient clustering approach not only depends on the...
Growing Locally Linear Embedding for Manifold Learning (2007)
Junsong Yin, Dewen Hu, Zongtan Zhou
Locally linear embedding is an effective nonlinear dimensionality reduction method for exploring the intrinsic characteristics of high dimensional data. This paper proposes a new manifold learning...
Efficient reinforcement learning using recursive least-squares methods (2002)
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is mainly due to its fast...
Efficient reinforcement learning using recursive least-squares methods (2002)
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is mainly due to its fast...