A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
We propose a class of graphical models appropriate for structure prediction problems where the model structure is a function of the output structure. Incremental Sigmoid Belief Ne...
We describe computationally efficient methods for learning mixtures in which each component is a directed acyclic graphical model (mixtures of DAGs or MDAGs). We argue that simple...
Bo Thiesson, Christopher Meek, David Maxwell Chick...
In order to achieve optimal efficiency in a learning process, individual learner needs his/her own personalized assistance. For a web-based open and dynamic learning environment, ...
Abstract— We present and examine a technique for estimating the ego-motion of a mobile robot using memory-based learning and a monocular camera. Unlike other approaches that rely...
Richard Roberts, Hai Nguyen, Niyant Krishnamurthi,...