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An important way to make large training sets is to gather noisy labels from crowds of nonexperts. We propose a minimax entropy principle to improve the quality of these labels. Our method assumes that labels are generated by a probability distribution over workers, items, and labels. By maximizing the entropy of this distribution, the method naturally(More)
An inescapable bottleneck with learning from large data sets is the high cost of labeling training data. Unsupervised learning methods have promised to lower the cost of tagging by leveraging notions of similarity among data points to assign tags. However, unsupervised and semi-supervised learning techniques often provide poor results due to errors in(More)
The Facilitator Room is a conference room that is outfitted with sensors and actuators in order to observe and influence human behavior in conversational settings. This work describes our efforts thus far in developing robust sensing mechanisms in the visual and auditory domains and designing statistical models to analyze and predict behavior. We review the(More)
Glucuronidation mediated by UDP-glucuronosyltransferases (UGTs) is a significant metabolic pathway that facilitates efficient elimination of numerous endobiotics and xenobiotics, including phenolics. UGT genetic deficiency and polymorphisms or inhibition of glucuronidation by concomitant use of drugs are associated with inherited physiological disorders or(More)
We describe tools that use measurements from video for the extraction of facial modeling and animation parameters, head tracking, and real-time interactive facial animation. These tools share common goals but rely on varying details of physical and geometric modeling and in their input measurement system. Accurate facial modeling involves fine details of(More)
An overwhelming number of news articles are available every day via the internet. Unfortunately, it is impossible for us to peruse more than a handful; furthermore it is difficult to ascertain an article’s social context, i.e., is it popular, what sorts of people are reading it, etc. In this paper, we develop a system to address this problem in the(More)