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A semi|supervised deep learning method based on stacked sparse ...


A semi-supervised deep learning method based on stacked sparse ...

In this paper, we present a semi-supervised deep learning strategy, the stacked sparse auto-encoder (SSAE) based classification, for cancer prediction using ...

A semi-supervised deep learning method based on stacked sparse ...

The proposed SSAE based semi-supervised deep learning model shows its promising ability to process high-dimensional gene expression data and is proved to be ...

A semi-supervised deep learning method based on stacked sparse ...

Conclusions: The proposed SSAE based semi-supervised deep learning model shows its promising ability to process high-dimensional gene expression data and is ...

A semi-supervised deep learning method based on stacked sparse ...

81 Citations · A Transfer-Learning Approach to Feature Extraction from Cancer Transcriptomes with Deep Autoencoders · Transfer learning with convolutional ...

A semi-supervised deep learning method based on stacked sparse ...

A deep learning model, the stacked sparse auto-encoder based model, is proposed for cancer prediction.•The deep learning model, with pre-training and ...

A semi-supervised deep learning method based on stacked sparse ...

A semi-supervised deep learning method based on stacked sparse auto-encoder for cancer prediction using RNA-seq data. Yawen Xiao, J. W. & Zongli Lin, ...

a semi-supervised approach using stacked sparse autoencoder - HAL

To do so, this paper presents a stacked sparse autoencoder (SSAE) based semi-supervised deep-learning model for traffic classification. The ...

A Semi-supervised Stacked Autoencoder Approach for Network ...

To handle this issue, we propose a semi-supervised approach based on deep learning. ... To achieve these goals, we propose an approach using stacked sparse ...

Web-S4AE: a semi-supervised stacked sparse autoencoder model ...

In this paper, we propose a deep learning-based Semi-Supervised Stacked Sparse AutoEncoder (Web-S4AE) for web robot detection. The proposed ...

a semi-supervised approach using stacked sparse autoencoder - HAL

To do so, this paper presents a stacked sparse autoencoder (SSAE) based semi-supervised deep-learning model for traffic classification. The main motivations ...

A Semi-supervised Stacked Autoencoder Approach for Network ...

To handle this important issue, this paper presents a stacked sparse autoencoder (SSAE) based semi-supervised deep learning model for traffic classification. In ...

A semi-supervised approach using stacked sparse autoencoder

Barut; Shi, An efficient feature generation approach based on deep learning and feature selection techniques for traffic classification, Comput.

A Semi-Supervised Stacked Autoencoder Using the Pseudo Label ...

As a typical deep learning algorithm, the stacked autoencoder ... Semi-supervised learning methods based on the pseudo label have been ...

Stacked Convolutional Sparse Auto-Encoders for Representation ...

Semi-supervised deep rule-based approach for image classification. ... Pseudo-label: The simple and efficient semi-supervised learning method for ...

Unsupervised Feature Learning With Distributed Stacked Denoising ...

... deep detection method is required. In this paper, we propose a novel semi -supervised distributed approach based on stacked denoising sparse autoencoder and ...

Deep learning based on stacked sparse autoencoder applied to ...

In the case of a novel virus identification, the early elucidation of taxonomic classification and origin of the virus genomic sequence is ...

Feature-Aligned Stacked Autoencoder: A Novel Semisupervised ...

Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Since the use ...

A deep learning approach for semi-supervised community detection ...

Deep stacked sparse autoencoders able to learn the node representation ... Liu, Scalable learning of collective behavior based on sparse social ...

Deep learning model construction for a semi-supervised ...

The information is feed into a DNN with deep stacked sparse ... based sparse feature extraction for semi-supervised learning. Signal ...

a semi-supervised stacked sparse autoencoder model for web robot ...

... based on deep semi-supervised learning. In: IFIP advances in information and communication technology. Springer International Publishing, pp 302–313 https ...