We study the problem of classifying data in a given taxonomy when classifications associated with multiple and/or partial paths are allowed. We introduce an incremental algorithm u...
We introduce a constructive, incremental learning system for regression problems that models data by means of spatially localized linear models. In contrast to other approaches, t...
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...
Abstract. This paper describes how function-based shape modeling can be expanded to web visualization, as well as how web-based visualization can be greatly improved by using the f...
— Classical position-based visual servoing approaches rely on the presence of distinctive features in the image such as corners and edges. In this contribution we exploit a hiera...