This paper proposes word clustering using word embedding. We used a neural net-based continuous skip-gram method for generating word embedding in continuous space. The proposed word clustering method represents each word in the vector space using a neural network. The K-means clustering method partitions word embedding into predetermined K-word

The selection of an embedding scheme is an important step in the modeling and prediction of chaotic dynamical systems. Theoretical work in embedding selection abounds in the literature. However in neural network research, mostly compute intensive methods for embedding selection exist. In this paper, we propose a novel embedding selection scheme based on cluster analysis. A neural network implem...

Neural Architecture Search (NAS) automates and prospers the design of neural networks. Estimator-based NAS has been proposed recently to model relationship between architectures their performance enable scalable flexible search. However, existing estimator-based methods encode architecture into a latent space without considering graph similarity. Ignoring similarity in node-based search may ind...

In this paper, an improved reversible data hiding scheme is proposed . In the method proposed by us , it apply expansion embedding , which will adaptively takes care of local specifities of image content. In our method , it classify pixels based on their predicted value and pixels prediction errors. By applying expansion embedding to the pixels prediction errors and by considering their immedia...

This paper proposed an adaptive multi-ary steganographic method based on additive noise to ensure the security of secret information. In order to minimizing the distortion caused by embedding operations, the characteristics of multi-ary steganography by adding removable noise and multi-ary matrix embedding are analyzed, and then a combination-based coding method is proposed for embedding inform...