Most of supervised learning algorithms assume the stability of the target concept over time. Nevertheless in many real-user modeling systems, where the data is collected over an ex...
Industrial implementation of model-based control methods, such as model predictive control, is often complicated by the lack of knowledge about the disturbances entering the syste...
Brian J. Odelson, Murali R. Rajamani, James B. Raw...
We study the retrieval task that ranks a set of objects for a given query in the pairwise preference learning framework. Recently researchers found out that raw features (e.g. word...
Xi Chen, Bing Bai, Yanjun Qi, Qihang Lin, Jaime G....
We address the problem of learning view-invariant 3D models of human motion from motion capture data, in order to recognize human actions from a monocular video sequence with arbi...
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...