Abstract. Approximations based on random Fourier features have recently emerged as an efficient and elegant methodology for designing large-scale kernel machines [4]. By expressing...
Kernel density estimation (KDE) has been used in many computational intelligence and computer vision applications. In this paper we propose a Bayesian estimation method for findin...
This paper proposes a switching hypothesized measurements (SHM) model supporting multimodal probability distributions and presents the application of the model in handling potenti...
K Nearest Neighbor search has many applications including data mining, multi-media, image processing, and monitoring moving objects. In this paper, we study the problem of KNN over...
Wenjie Zhang, Xuemin Lin, Muhammad Aamir Cheema, Y...
In this paper, an unsupervised learning algorithm, neighborhood linear embedding (NLE), is proposed to discover the intrinsic structures such as neighborhood relationships, global ...
Shuzhi Sam Ge, Feng Guan, Yaozhang Pan, Ai Poh Loh