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...
When given a small sample, we show that classification with SVM can be considerably enhanced by using a kernel function learned from the training data prior to discrimination. Thi...
Social media such as blogs, Facebook, Flickr, etc., presents data in a network format rather than classical IID distribution. To address the interdependency among data instances, ...
We construct an image segmentation scheme that combines top-down (TD) with bottom-up (BU) processing. In the proposed scheme, segmentation and recognition are intertwined rather th...
Abstract: Classification-based reinforcement learning (RL) methods have recently been proposed as an alternative to the traditional value-function based methods. These methods use...