Codebook-based representations are widely employed in the classification of complex objects such as images and documents. Most previous codebook-based methods construct a single c...
Wei Zhang, Akshat Surve, Xiaoli Fern, Thomas G. Di...
Although semi-supervised learning has been an active area of research, its use in deployed applications is still relatively rare because the methods are often difficult to impleme...
We consider a setting for discriminative semisupervised learning where unlabeled data are used with a generative model to learn effective feature representations for discriminativ...
Distance metric learning and nonlinear dimensionality reduction are two interesting and active topics in recent years. However, the connection between them is not thoroughly studi...
We describe a causal learning method, which employs measuring the strength of statistical dependences in terms of the Hilbert-Schmidt norm of kernel-based cross-covariance operato...