In this paper, we consider a smoothing kernelbased classification rule and propose an algorithm for optimizing the performance of the rule by learning the bandwidth of the smoothi...
Bharath K. Sriperumbudur, Omer A. Lang, Gert R. G....
We propose a novel technique for semi-supervised image annotation which introduces a harmonic regularizer based on the graph Laplacian of the data into the probabilistic semantic ...
Yuanlong Shao, Yuan Zhou, Xiaofei He, Deng Cai, Hu...
We develop a supervised dimensionality reduction method, called Lorentzian Discriminant Projection (LDP), for feature extraction and classification. Our method represents the str...
We present the Conformal Embedding Analysis (CEA) for feature extraction and dimensionality reduction. Incorporating both conformal mapping and discriminating analysis, CEA projec...
Embedding images into a low dimensional space has a wide range of applications: visualization, clustering, and pre-processing for supervised learning. Traditional dimension reduct...