MeetingsFrom: Thorsten JoachimsDate: 24 Oct 2002 Subject: NIPS Workshop on Learning Rankings, Vancouver/Whistler, BC, Dec 13 or 14, 2002
Not all supervised learning problems fit the classification/regression function-learning model. Some problems require predictions other than values or classes. For example, sometimes the magnitude of the values predicted for cases are not important, but the ordering these values induce is important. This workshop addresses supervised learning problems where either the goal of learning or the input to the learner is more complex than in classification and regression. Examples of such problems include learning partial or total orderings, learning equality or match rules, learning to optimize non-standard criteria such as Precision and Recall or ROC Area, using relative preferences as training examples, learning graphs and other structures, and problems that benefit from these approaches (e.g., text retrieval, medical decision making, protein matching). The goal of this one-day workshop is to discuss the current state-of-the-art, and to inspire research on new algorithms and problems. To submit an extended abstract, see http://www.cs.cornell.edu/People/tj/ranklearn. Invited speakers include:
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