Exploiting separability in large-scale linear support vector machine training
نویسندگان
چکیده
منابع مشابه
Exploiting separability in large-scale linear support vector machine training
Linear support vector machine training can be represented as a large quadratic program. We present an efficient and numerically stable algorithm for this problem using interior point methods, which requires only O(n) operations per iteration. Through exploiting the separability of the Hessian, we provide a unified approach, from an optimization perspective, to 1-norm classification, 2-norm clas...
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Support vector machine training can be represented as a large quadratic program. We present an efficient and numerically stable algorithm for this problem using interior point methods, which requires only O(n) operations per iteration. Through exploiting the separability of the Hessian, we provide a unified approach, from an optimization perspective, to 1-norm classification, 2-norm classificat...
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ژورنال
عنوان ژورنال: Computational Optimization and Applications
سال: 2009
ISSN: 0926-6003,1573-2894
DOI: 10.1007/s10589-009-9296-8