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
21 - 40 out of 45Page size: 20

Research Output

  1. 2018
  2. 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 Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 10
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  3. 2017
  4. 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 Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 155
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  5. 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 Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 89
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  6. 2016
  7. 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 Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 26
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  8. Published

    Model-free Variable Selection in Reproducing Kernel Hilbert Space

    Yang, L., Lv, S. & Wang, J., May 2016, In: Journal of Machine Learning Research. 17, 82.

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 29
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  9. Published

    Sparsity and error analysis of empirical feature-based regularization schemes

    Guo, X., Fan, J. & Zhou, D., 2016, In: Journal of Machine Learning Research (Print). 17, p. 1-34

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 6
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  10. 2015
  11. Published

    Learning theory of randomized Kaczmarz algorithm

    Lin, J. & Zhou, D., 2015, In: Journal of Machine Learning Research (Print). 16, p. 3341-3365

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 28
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  12. 2014
  13. Published

    Clustering hidden Markov models with variational HEM

    Coviello, E., Chan, A. B. & Lanckriet, G. R. G., 2014, In: Journal of Machine Learning Research. 15, p. 697-747

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 62
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  14. 2013

  15. Consistent selection of tuning parameters via variable selection stability

    Sun, W., Wang, J. & Fang, Y., Nov 2013, In: Journal of Machine Learning Research. 14, p. 3419-3440

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 55
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  16. Stationary-sparse causality network learning

    He, Y., She, Y. & Wu, D., Oct 2013, In: Journal of Machine Learning Research. 14, p. 3073-3104

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 15
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  17. Published

    Learning theory approach to minimum error entropy criterion

    Hu, T., Fan, J., Wu, Q. & Zhou, D., Feb 2013, In: Journal of Machine Learning Research. 14, 1, p. 377-397

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 79
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  18. Published

    Efficient program synthesis using constraint satisfaction in inductive logic programming

    Ahlgren, J. & Yuen, S. Y., 2013, In: Journal of Machine Learning Research. 14, p. 3649 - 3681

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 16
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  19. 2009
  20. Published

    Classification with gaussians and convex loss

    Xiang, D. & Zhou, D., Jul 2009, In: Journal of Machine Learning Research. 10, p. 1447-1468

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 40
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  21. On efficient large margin semisupervised learning: Method and theory

    Wang, J., Shen, X. & Pan, W., Jan 2009, In: Journal of Machine Learning Research. 10, p. 719-742

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 40
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  22. Published

    Online learning with samples drawn from non-identical distributions

    Hu, T. & Zhou, D., 2009, In: Journal of Machine Learning Research. 10, p. 2873-2898

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 8
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  23. 2008
  24. Published

    Universal multi-task Kernels

    Caponnetto, A., Micchelli, C. A., Pontil, M. & Ying, Y., Jul 2008, In: Journal of Machine Learning Research. 9, p. 1615-1646

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 108
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  25. 2007

  26. Large margin semi-supervised learning

    Wang, J. & Shen, X., Aug 2007, In: Journal of Machine Learning Research. 8, p. 1867-1891

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 48
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  27. Published

    Local discriminant wavelet packet coordinates for face recognition

    Liu, C., Dai, D. & Yan, H., May 2007, In: Journal of Machine Learning Research. 8, p. 1165-1195

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 37
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  28. Published

    Learnability of Gaussians with flexible variances

    Ying, Y. & Zhou, D., Jan 2007, In: Journal of Machine Learning Research. 8, p. 249-276

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 54
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  29. Efficient large margin semisupervised learning

    Wang, J., 2007, In: Journal of Machine Learning Research. 2, p. 588-595

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Scopus citations: 1
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