کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4946297 1439278 2017 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A new regularized restricted Boltzmann machine based on class preserving
ترجمه فارسی عنوان
بولتزمن محدودیتی جدید بر اساس نگهداری کلاس دارد
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
It is known that an Restricted Boltzmann machine (RBM) can be used as a feature extractor to automatically extract data features in a completely unsupervised learning manner. In this paper, we develop a new regularized RBM by adding the class information, referred to as class preserving RBM (CPr-RBM). Specifically, we impose two constraints on RBM to make the class information clearly reflected in extracted features. One constraint can decrease the distance between the features of the same class and the other one can increase the distance between the features of different classes. The two constraints introduce class information to RBM and make the extracted features contain more category information which contributes to a better classification result. Experiments are conducted on MNIST dataset and 20-newgroup dataset, which show that CPr-RBM learns more discriminate representations and outperforms other related state-of-the-art models in dealing with classification problems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 123, 1 May 2017, Pages 1-12
نویسندگان
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