Learning with queries corrupted by classification noise
نویسندگان
چکیده
منابع مشابه
Learning with Queries Corrupted by Classification Noise
Kearns introduced the “statistical query” (SQ) model as a general method for producing learning algorithms which are robust against classification noise. We extend this approach in several ways in order to tackle algorithms that use “membership queries”, focusing on the more stringent model of “persistent noise”. The main ingredients in the general analysis are: (1) Smallness of dimension of th...
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Our work relies on the design and evaluation of experimental information retrieval systems able to cope with textual misspellings in queries. In contrast to previous proposals, commonly based on the consideration of spelling correction strategies and a word language model, we also report on the use of character n-grams as indexing support.
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Consider the pattern recognition problem of learning multi-category classification from a labeled sample, for instance, the problem of learning character recognition where a category corresponds to an alphanumeric letter. The classical theory of pattern recognition assumes labeled examples appear according to the unknown underlying pattern-class conditional probability distributions where the p...
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ژورنال
عنوان ژورنال: Discrete Applied Mathematics
سال: 1999
ISSN: 0166-218X
DOI: 10.1016/s0166-218x(99)00045-1