Titlebook: Wave Dynamics, Mechanics and Physics of Microstructured Metamaterials; Theoretical and Expe Mezhlum A. Sumbatyan Book 2019 Springer Nature

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Mels V. Belubekyan,Vagharshak M. Belubekyaning method of discovering subspace structures of data. Graph regularized sparse coding has been extensively studied for keeping the locality of the high-dimensional observations. However, in practice, data is always corrupted by noises such that samples from the same class may not inhabit the neares

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Vladimir M. Zotov,Vitaly V. Popuzin,Alexander E. Tarasovfor pruning algorithms. According to this idea, we propose a pruning thought—.. We can combine . with almost all existing pruning algorithms. Compared with the original pruning algorithms based on a large number of pre-training, the modified algorithms (by .) has competitive compression effect. On t

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Mels V. Belubekyan,Vagharshak M. Belubekyan the correlations of heterogeneous data for cross-media retrieval is a challenging problem. In order to handle with multiple media types, this paper proposes a novel distance-preserving correlation learning and multi-modal manifold regularization (DCLMM) approach to exploit the common representation

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Roman A. Gerasimov,Tatiana O. Petrova,Victor A. Eremeyev,Andrei V. Maximov,Olga G. Maximovafor conventional text. We introduce a POS tagging model that takes advantages of deep learning and manually engineered features to overcome the challenges of the task. The main part of the model consists of several bidirectional long short-term memory (BiLSTM) layers that are used to learn intermedi

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G. Iovane,A. V. Nasedkintime series based on predicted results of the sentiment classifiers, which may not correspond to the actual values due to the lack of labeled data or the limited performance of the classifier. To alleviate this problem, we propose a calibrated-based method to generate time series composed of accurat