We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...
For object category recognition to scale beyond a small number of classes, it is important that algorithms be able to learn from a small amount of labeled data per additional clas...
Kevin Tang, Marshall Tappen, Rahul Sukthankar, Chr...
This paper proposes a two-phase example-based machine translation methodology which develops translation templates from examples and then translates using template matching. This ...
Accurately locating users in a wireless environment is an important task for many pervasive computing and AI applications, such as activity recognition. In a WiFi environment, a m...
Sinno Jialin Pan, James T. Kwok, Qiang Yang, Jeffr...
Abstract. We propose a novel method for unsupervised class segmentation on a set of images. It alternates between segmenting object instances and learning a class model. The method...