منابع مشابه
Data augmentation for diffusions
The problem of formal likelihood-based (either classical or Bayesian) inference for discretely observed multi-dimensional diffusions is particularly challenging. In principle this involves data-augmentation of the observation data to give representations of the entire diffusion trajectory. Most currently proposed methodology splits broadly into two classes: either through the discretisation of ...
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Data augmentation plays a crucial role in increasing the number of training images, which often aids to improve classification performances of deep learning techniques for computer vision problems. In this paper, we employ the deep learning framework and determine the effects of several data-augmentation (DA) techniques for plant classification problems. For this, we use two convolutional neura...
متن کاملData Augmentation for Morphological Reinflection
This paper presents the submission of the Linguistics Department of the University of Colorado at Boulder for the 2017 CoNLL-SIGMORPHON Shared Task on Universal Morphological Reinflection. The system is implemented as an RNN Encoder-Decoder. It is specifically geared toward a low-resource setting. To this end, it employs data augmentation for counteracting overfitting and a copy symbol for proc...
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This short paper considers comparisons of different data augmentation algorithms in terms of their convergence and efficiency. It examines connections between the partial order 1 on Markov kernels, and inequalities of operator norms. It applies notions from Roberts and Rosenthal (2006) related to variance bounding Markov chains, together with L2 theory, to data augmentation algorithms (Tanner a...
متن کاملParameter Expansion for Data Augmentation
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ژورنال
عنوان ژورنال: Journal of Computational and Graphical Statistics
سال: 2013
ISSN: 1061-8600,1537-2715
DOI: 10.1080/10618600.2013.783484