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نمایش تعداد 1-6 از 6
Constrained Semi-Supervised Growing Self-Organizing Map
Semi-supervised clustering tries to surpass the limits of unsupervised clustering using extra information contained in occasional labeled data points. However, providing such labeled samples is not always possible or easy ...
Initial Free Self-Organizing Map by Aggregation
Initialization parameters of Self-organizing map networks (SOM) have a great influence in
their final result. This is the only known problem of SOM networks. The uncertainty of
solution is ...
Incremental Constrained Discriminant Component Analysis
Recently, a constrained Linear Discriminant Analysis (LDA) algorithm is introduced and
gained popularity. However, this algorithm is not applicable in the environment with large
amount of data points or when ...
Data Ranking in Semi-Supervised Learning
The real challenge in pattern recognition tasks and machine learning processes is to train
a discriminator using labeled data and use it to distinguish between future data points as
accurate as ...
Online discriminative component analysis feature extraction from stream data with domain knowledge
In this paper, we introduce an incremental version of recently proposed constrained Linear Discriminant Analysis (LDA). In addition of application in constrained LDA problems, our algorithm which we call ...
پیشگوی آگاه از مشخصات فیزیکی برای مدیریت پویای دمای پردازنده های چند هسته ای
با توجه به روند رشد مدارات مجتمع، و افزایش روز افزون تعداد ترانزیستور های موجود در یک تراشه، میزان انرژی مصرفی در یک مدار، و به طبع آن، میزان گرمای تولیدی، رو به افزایش می باشد. افزایش دما، باعث بوجود آمدن مشکالت بسیاری ...