We extend the VC theory of statistical learning to data dependent spaces of classifiers. This theory can be viewed as a decomposition of classifier design into two components; the...
Adam Cannon, J. Mark Ettinger, Don R. Hush, Clint ...
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Translingual information retrieval (TLIR) consists of providing a query in one language and searching document collections in one or more di erent languages. This paper introduces...
Yiming Yang, Jaime G. Carbonell, Ralf D. Brown, Ro...
Abstract. Many complex control problems are not amenable to traditional controller design. Not only is it difficult to model real systems, but often it is unclear what kind of beha...
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
Thomas G. Dietterich, Adam Ashenfelter, Yaroslav B...