Search: semi-supervised learning — Academic Articles

Neural Network Methods for Natural Language Processing

Yang Liu, Meng Zhang • Computational Linguistics (2017)

Deep learning has attracted dramatic attention in recent years, both in academia and industry. The popular term deep learning generally refers to neural network methods. Indeed, many core ideas and methods were born years ago in the era of ...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1162/coli_r_00312

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A unified architecture for natural language processing

Ronan Collobert, Jason Weston • International Conference on Machine Learning (2008)

We describe a single convolutional neural network architecture that, given a sentence, outputs a host of language processing predictions: part-of-speech tags, chunks, named entity tags, semantic roles, semantically similar words and the lik...

OPENALEX DOI: https://doi.org/10.1145/1390156.1390177

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Deep learning in food category recognition

Yudong Zhang, Lijia Deng, Hengde Zhu, Wei Wang et al. • Information Fusion (2023)

Integrating artificial intelligence with food category recognition has been a field of interest for research for the past few decades. It is potentially one of the next steps in revolutionizing human interaction with food. The modern advent...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.inffus.2023.101859

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Deep learning applications and challenges in big data analytics

Maryam Mousaarab Najafabadi, Flavio Villanustre, Taghi M. Khoshgoftaar, Naeem Seliya et al. • Journal Of Big Data (2015)

Abstract Big Data Analytics and Deep Learning are two high-focus of data science. Big Data has become important as many organizations both public and private have been collecting massive amounts of domain-specific information, which can con...

OPENALEX cc-by DOI: https://doi.org/10.1186/s40537-014-0007-7

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Deep learning for power quality

Roger Alves de Oliveira, Math Bollen • Electric Power Systems Research (2022)

This paper aims to introduce deep learning to the power quality community by reviewing the latest applications and discussing the open challenges of this technology. Publications covering deep learning to power quality are stratified in ter...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.epsr.2022.108887

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Malware Detection via Extended Label Propagation Through Graph Inference

Yitu Fu, Ju Xu • IEEE Access (2019)

In this paper, we model the malware detection problem as a graph inference problem, and develop a novel belief propagation approach within a semi-supervised learning scheme that fully makes use of files' and hosts' connections to detect mal...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2019.2948374

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Academic Articles & Research Papers

Neural Network Methods for Natural Language Processing

A unified architecture for natural language processing

Deep learning in food category recognition

Deep learning applications and challenges in big data analytics

Deep learning for power quality

Malware Detection via Extended Label Propagation Through Graph Inference