In this paper we propose a new information-theoretic divisive algorithm for word clustering applied to text classification. In previous work, such "distributional clustering&...
Inderjit S. Dhillon, Subramanyam Mallela, Rahul Ku...
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
Implicit discourse relation recognition is difficult due to the absence of explicit discourse connectives between arbitrary spans of text. In this paper, we use language models to...
Zhi Min Zhou, Man Lan, Zhengyu Niu, Yu Xu, Jian Su
Social insect societies and more specifically ant colonies, are distributed systems that, in spite of the simplicity of their individuals, present a highly structured social organi...
We present a data-driven, unsupervised method for unusual
scene detection from static webcams. Such time-lapse
data is usually captured with very low or varying framerate.
This ...
Michael D. Breitenstein, Helmut Grabner, Luc Van G...