منابع مشابه
Note on Weight Noise Injection During Training a MLP
Although many analytical works have been done to investigate the change of prediction error of a trained NN if its weights are injected by noise, seldom of them has truly investigated on the dynamical properties (such as objective functions and convergence behavior) of injecting weight noise during training. In this paper, four different online weight noise injection training algorithms for mul...
متن کاملConstructing noise-reducing operators from training images
We discuss constructing non-linear noise reduction operators on binary images using a training set of noiseless images. We extract from the training set a probability distribution over local neighborhoods. Our operator changes pixel values when such a change turns a low probability neighborhood into high probability one. 1 1 Motivation We have developed an operator that modiies a pixel based on...
متن کاملConvergence analysis of on-line weight noise injection training algorithms for MLP networks
Injecting weight noise during training has been proposed for almost two decades as a simple technique to improve fault tolerance and generalization of a multilayer perceptron (MLP). However, little has been done regarding their convergence behaviors. Therefore, we presents in this paper the convergence proofs of two of these algorithms for MLPs. One is based on combining injecting multiplicativ...
متن کاملthe impact of training on second language writing assessment: a case of raters’ biasedness
چکیده هدف اول این تحقیق بررسی تأثیر آموزش مصحح بر آموزش گیرندگان براساس پایایی نمره های آنها در پنج بخش شامل محتوا ، سازمان ، لغت ، زبان و مکانیک بود. هدف دوم این بود که بدانیم آیا تفاوتهای بین آموزشی گیرندگان زن و مرد در پایایی نمرات آنها وجود دارد. برای بررسی این موارد ، ما 90 دانشجو در سطح میانه (متوسط) که از طریق تست تعیین سطح شده بودند انتخاب شدند. بعد از آنها خواستیم که درباره دو موضوع ا...
15 صفحه اولSNIWD: Simultaneous Weight Noise Injection with Weight Decay for MLP Training
Despite noise injecting during training has been demonstrated with success in enhancing the fault tolerance of neural network, theoretical analysis on the dynamic of this noise injection-based online learning algorithm has far from complete. In particular, the convergence proofs for those algorithms have not been shown. In this regards, this paper presents an empirical study on the non-converge...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Soft Computing
سال: 2015
ISSN: 1432-7643,1433-7479
DOI: 10.1007/s00500-015-1690-9