We propose a new transductive learning algorithm for learning optimal linear representations that utilizes unlabeled data. We pose the problem of learning linear representations a...
We consider negotiations between publishers and advertisers in a marketplace for ads. Motivated by Google’s online PrintAds system which is such a marketplace, we focus on the r...
The structure of a Markov network is typically learned using top-down search. At each step, the search specializes a feature by conjoining it to the variable or feature that most ...
Abstract. We analyze the expected cost of a greedy active learning algorithm. Our analysis extends previous work to a more general setting in which different queries have differe...
We have combined methods from volume visualization and data analysis to support better diagnosis and treatment of human retinal diseases. Many diseases can be identified by abnorma...
Alfred R. Fuller, Rober t J. Zawadzki, Stacey Ch...