App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 6

Ensemble meta net based on adaptive reweight and regularization

Wang Jiaqi
Yuan Ye
Zhu Yongtong
Li Qingdu
Liu Na
The Institute of Machine Intelligence, University of Shanghai for Science & Technology, Shanghai 200093, China
DOI: 10.19734/j.issn.1001-3695.2023.09.0501

Abstract

Deep neural networks tend to overfit to biased training data when there are noisy labels or imbalanced class distributions in the training set. Using reweighting strategies with appropriate sample weighting is a common method to address this issue. However, improper reweighting schemes can introduce additional overhead and bias to the network's learning process, making it difficult to solve overfitting problems in biased distribution networks using only reweighting methods. To address this problem, this paper proposes a method that combines label smoothing regularization, class margin regularization, and reweighting, and presents an ensemble meta-learning method based on adaptive reweighting and regularization (Ensemble Meta Net, EMN) , which consists of a base network for classification and an ensemble meta-net for hyperparameter estimation. The method first obtains the sample loss through the base network, then uses three meta-learners to estimate the hyperparameters of adaptive reweighting and regularization in an integrated manner based on the loss, and finally uses the three hyperparameters to calculate the final ensemble meta-loss and update the base network, thereby improving its performance on biased distribution datasets. Experimental results demonstrate that EMN achieves higher accuracy on CIFAR and OCTMNIST datasets compared to other methods, and the effectiveness of different strategies is demonstrated through policy correlation analysis.

Foundation Support

国家自然科学基金资助项目(92048205,61773083)
上海市浦江人才计划资助项目(2019PJD035)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.09.0501
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 6

Publish History

[2024-02-02] Accepted Paper

Cite This Article

王佳琦, 袁野, 朱永同, 等. 基于自适应重加权和正则化的集成元学习算法 [J]. 计算机应用研究, 2024, 41 (6). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.09.0501. (Wang Jiaqi, Yuan Ye, Zhu Yongtong, et al. Ensemble meta net based on adaptive reweight and regularization [J]. Application Research of Computers, 2024, 41 (6). (2024-04-10). https://doi.org/10.19734/j.issn.1001-3695.2023.09.0501. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)