Several authors have theoretically determined distribution-free bounds on sample complexity. Formulas based on several learning paradigms have been presented. However, little is kn...
We consider the question of predicting nonlinear time series. Kernel Dynamical Modeling (KDM), a new method based on kernels, is proposed as an extension to linear dynamical model...
Output coding is a general method for solving multiclass problems by reducing them to multiple binary classification problems. Previous research on output coding has employed, alm...
A method is described which, like the kernel trick in support vector machines (SVMs), lets us generalize distance-based algorithms to operate in feature spaces, usually nonlinearl...
In this paper, we tackle the problem of characterizing the aesthetic appeal of consumer videos and automatically classifying them into high or low aesthetic appeal. First, we condu...