Journal of Machine Learning Research

Journal of Machine Learning Research

ISSNs: 1532-4435, 1533-7928

Additional searchable ISSN (electronic): 1533-7928

MICROTOME PUBL, United States

Scopus rating (2023): CiteScore 18.8 SJR 2.796 SNIP 4.031

Journal

Journal Metrics

Research Output

  1. 2024
  2. Published

    Classification with Deep Neural Networks and Logistic Loss

    Zhang, Z., Shi, L. & Zhou, D., 2024, In: Journal of Machine Learning Research. 25, 125.

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Check@CityULib
  3. Published

    More Efficient Estimation of Multivariate Additive Models Based on Tensor Decomposition and Penalization

    Liu, X., Lian, H. & Huang, J., 2024, In: Journal of Machine Learning Research. 25, 27 p., 161.

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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  4. Published

    Nonparametric Regression Using Over-parameterized Shallow ReLU Neural Networks

    Yang, Y. & Zhou, D., 2024, In: Journal of Machine Learning Research. 25, 165.

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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  5. 2023
  6. Published

    Distributed Algorithms for U-statistics-based Empirical Risk Minimization

    Chen, L., Wan, A. T., Zhang, S. & Zhou, Y., 2023, In: Journal of Machine Learning Research. 24, 263.

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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  7. 2022
  8. Published

    Debiased Distributed Learning for Sparse Partial Linear Models in High Dimensions

    Lv, S. & Lian, H., 2022, In: Journal of Machine Learning Research. 23, 2.

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Scopus citations: 9
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  9. Published

    Decimated Framelet System on Graphs and Fast G-Framelet Transforms

    Zheng, X., Zhou, B., Wang, Y. G. & Zhuang, X., 2022, In: Journal of Machine Learning Research. 23, 18.

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Scopus citations: 15
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  10. Published

    Learning linear non-Gaussian directed acyclic graph with diverging number of nodes

    Zhao, R., He, X. & Wang, J., 2022, In: Journal of Machine Learning Research. 23, 269.

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Scopus citations: 4
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  11. Published

    Statistical Rates of Convergence for Functional Partially Linear Support Vector Machines for Classification

    Zhang, Y., Zhao, Y. & Lian, H., 2022, In: Journal of Machine Learning Research. 23, p. 1-24

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Scopus citations: 3
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  12. 2021
  13. Published

    Partial policy iteration for L1-Robust Markov decision processes

    Ho, C. P., Petrik, M. & Wiesemann, W., Oct 2021, In: Journal of Machine Learning Research. 22, 275.

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Scopus citations: 27
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  14. Published

    On ADMM in deep learning: Convergence and saturation-avoidance

    Zeng, J., Lin, S., Yao, Y. & Zhou, D., 2021, In: Journal of Machine Learning Research. 22, 199.

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Scopus citations: 11
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  15. 2020
  16. Published

    Ultra-High Dimensional Single-Index Quantile Regression

    Zhang, Y., Lian, H. & Yu, Y., Nov 2020, In: Journal of Machine Learning Research. 21, 224.

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Scopus citations: 11
    Check@CityULib
  17. Published

    High-dimensional Quantile Tensor Regression

    Lu, W., Zhu, Z. & Lian, H., Oct 2020, In: Journal of Machine Learning Research. 21, 250.

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Scopus citations: 12
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  18. Published

    Distributed Kernel Ridge Regression with Communications

    Lin, S., Wang, D. & Zhou, D., 2020, In: Journal of Machine Learning Research. 21, 38 p., 93.

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Scopus citations: 24
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  19. 2019
  20. Published

    Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping

    Lin, S., Lei, Y. & Zhou, D., 2019, In: Journal of Machine Learning Research. 20, 46.

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Scopus citations: 16
    Check@CityULib
  21. Published

    Smooth neighborhood recommender systems

    Dai, B., Wang, J., Shen, X. & Qu, A., 2019, In: Journal of Machine Learning Research. 20, 16.

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Scopus citations: 21
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  22. 2018
  23. Published

    Divide-and-Conquer for Debiased l1-norm Support Vector Machine in Ultra-high Dimensions

    Lian, H. & Fan, Z., Aug 2018, In: Journal of Machine Learning Research. 18, 182.

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Scopus citations: 29
    Check@CityULib
  24. Published

    Convergence of unregularized online learning algorithms

    Lei, Y., Shi, L. & Guo, Z., Apr 2018, In: Journal of Machine Learning Research. 18, 1

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Scopus citations: 10
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  25. 2017
  26. Published

    Distributed learning with regularized least squares

    Lin, S., Guo, X. & Zhou, D., Sept 2017, In: Journal of Machine Learning Research. 18, 92, p. 1-31

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Scopus citations: 155
    Check@CityULib
  27. Published

    Distributed Semi-supervised Learning with Kernel Ridge Regression

    Chang, X., Lin, S. & Zhou, D., 2017, In: Journal of Machine Learning Research. 18

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Scopus citations: 89
    Check@CityULib
  28. 2016
  29. Published

    Iterative regularization for learning with convex loss functions

    Lin, J., Rosasco, L. & Zhou, D., 1 May 2016, In: Journal of Machine Learning Research. 17, p. 1-38

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Scopus citations: 26
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