PEIR, the Personal Environmental Impact Report, is a participatory sensing application that uses location data sampled from everyday mobile phones to calculate personalized estima...
Min Mun, Sasank Reddy, Katie Shilton, Nathan Yau, ...
In this paper, we introduce the “Plug” sensor network, a ubiquitous networked sensing platform ideally suited to broad deployment in environments where people work and live. T...
Joshua Lifton, Mark Feldmeier, Yasuhiro Ono, Camer...
This paper presents the Topic-Aspect Model (TAM), a Bayesian mixture model which jointly discovers topics and aspects. We broadly define an aspect of a document as a characteristi...
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...