Dropout Rademacher complexity of deep neural networks

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Cite
Gao, Wei, and Zhi-Hua Zhou. “Dropout Rademacher Complexity of Deep Neural Networks”. Science China Information Sciences, vol. 59, no. 7, 2016, https://doi.org/10.1007/s11432-015-5470-z.
Gao, W., & Zhou, Z.-H. (2016). Dropout Rademacher complexity of deep neural networks. Science China Information Sciences, 59(7). https://doi.org/10.1007/s11432-015-5470-z
Gao, Wei, and Zhi-Hua Zhou. “Dropout Rademacher Complexity of Deep Neural Networks”. Science China Information Sciences 59, no. 7 (2016). https://doi.org/10.1007/s11432-015-5470-z.
Gao W, Zhou ZH. Dropout Rademacher complexity of deep neural networks. Science China Information Sciences. 2016;59(7).
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Mathematics
Instruments and machines
Electronic computers
Computer science
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Computer software
Science
Science (General)
Cybernetics
Information theory
Technology
Electrical engineering
Electronics
Nuclear engineering
Electric apparatus and materials
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Refrences
Title Journal Journal Categories Citations Publication Date
The dropout learning algorithm Artificial Intelligence
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
 168 2014
10.1109/MSP.2012.2205597 2012
10.1109/TASL.2011.2134090 2012
10.1162/NECO_a_00052 Neural Computation
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry
  • Technology: Mechanical engineering and machinery
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics
  • Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
 2010
Reducing the Dimensionality of Data with Neural Networks

 Science
  • Science: Science (General)
 8,731 2006
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Dropout drops double descent Japanese Journal of Statistics and Data Science
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 2024
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 2024
Deep Learning Algorithm Based on Molecular Fingerprint for Prediction of Drug‐Induced Liver Injury Toxicology
  • Medicine: Therapeutics. Pharmacology
  • Medicine: Public aspects of medicine: Toxicology. Poisons
  • Medicine: Public aspects of medicine: Toxicology. Poisons
 2024
Greedy training algorithms for neural networks and applications to PDEs Journal of Computational Physics
  • Science: Mathematics: Instruments and machines: Electronic computers. Computer science
  • Science: Mathematics
  • Science: Physics
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Modelling and optimization of surface roughness in chemical mechanical polishing based on DNN-GA

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 2023
Citations Analysis
Category Category Repetition
Science: Mathematics: Instruments and machines: Electronic computers. Computer science19
Technology: Electrical engineering. Electronics. Nuclear engineering: Electric apparatus and materials. Electric circuits. Electric networks11
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics: Computer engineering. Computer hardware11
Science: Mathematics: Instruments and machines: Electronic computers. Computer science: Computer software9
Technology: Mechanical engineering and machinery8
Technology: Electrical engineering. Electronics. Nuclear engineering: Electronics8
Science: Science (General): Cybernetics: Information theory8
Technology: Engineering (General). Civil engineering (General)5
Medicine: Medicine (General): Medical technology2
Science: Mathematics2
Science: Biology (General)2
Science: Physics2
Science: Chemistry2
Science: Chemistry: General. Including alchemy2
Technology: Technology (General): Industrial engineering. Management engineering2
Science: Mathematics: Probabilities. Mathematical statistics2
Medicine: Medicine (General)1
Medicine: Therapeutics. Pharmacology1
Medicine: Public aspects of medicine: Toxicology. Poisons1
Medicine1
Science1
Science: Science (General)1
Technology: Chemical technology1
Technology: Electrical engineering. Electronics. Nuclear engineering: Materials of engineering and construction. Mechanics of materials1
Technology: Manufactures1
Science: Chemistry: Organic chemistry: Biochemistry1
Medicine: Medicine (General): Computer applications to medicine. Medical informatics1
Science: Geology: Petrology1
Science: Geology: Mineralogy1
Technology: Chemical technology: Oils, fats, and waxes: Petroleum refining. Petroleum products1
Medicine: Medicine (General): Medical physics. Medical radiology. Nuclear medicine1
Technology: Electrical engineering. Electronics. Nuclear engineering: Telecommunication1
The category Science: Mathematics: Instruments and machines: Electronic computers. Computer science 19 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Survey of recent progress in semantic image segmentation with CNNs and was published in 2017. The most recent citation comes from a 2024 study titled Dropout drops double descent. This article reached its peak citation in 2022, with 7 citations. It has been cited in 26 different journals, 11% of which are open access. Among related journals, the Science China Information Sciences cited this research the most, with 5 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year