Concentration estimates for learning with ℓ1-regularizer and data dependent hypothesis spaces L Shi, Y Feng, DX Zhou Applied and Computational Harmonic Analysis 31 (2), 286-302, 2011 | 122 | 2011 |

Learning with the maximum correntropy criterion induced losses for regression Y Feng, X Huang, L Shi, Y Yang, JAK Suykens Journal of Machine Learning Research 16, 993−1034, 2015 | 73 | 2015 |

Towards confidence in the truth: a bootstrapping based truth discovery approach H Xiao, J Gao, Q Li, F Ma, L Su, Y Feng, A Zhang ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2016 | 50 | 2016 |

A statistical learning approach to modal regression Y Feng, J Fan, JAK Suykens Journal of Machine Learning Research 21 (2), 1-35, 2020 | 39 | 2020 |

Robust low-rank tensor recovery with regularized redescending M-estimator Y Yang, Y Feng, JAK Suykens IEEE Transactions on Neural Networks and Learning Systems 27 (9), 1933 - 1946, 2015 | 35 | 2015 |

A rank-one tensor updating algorithm for tensor completion Y Yang, Y Feng, JAK Suykens IEEE Signal Processing Letters 22 (10), 1633-1637, 2015 | 31 | 2015 |

Kernelized elastic net regularization: generalization bounds and sparse recovery Y Feng, SG Lv, H Hang, JAK Suykens Neural Computation 28 (3), 525-562, 2015 | 30 | 2015 |

Rank-one tensor properties with applications to a class of tensor optimization problems Y Yang, Y Feng, X Huang, JAK Suykens SIAM Journal on Optimization 26 (1), 171-196, 2015 | 24 | 2015 |

Unified approach to coefficient-based regularized regression Y Feng, SG Lv Computers & Mathematics with Applications 62 (1), 506-515, 2011 | 23 | 2011 |

Robust support vector machines for cassification with non-convex and smooth losses Y Feng, Y Yang, X Huang, S Mehrkanoon, JAK Suykens Neural Computation 28 (6), 1217-1247, 2016 | 21 | 2016 |

Integral operator approach to learning theory with unbounded sampling SG Lv, Y Feng Complex Analysis and Operator Theory 6 (3), 533-548, 2012 | 14 | 2012 |

Kernel density estimation for dynamical systems H Hang, I Steinwart, Y Feng, JAK Suykens Journal of Machine Learning Research 19 (1), 1260-1308, 2018 | 11 | 2018 |

A nonconvex relaxation approach to robust matrix completion Y Yang, Y Feng, J Suykens Preprint, 2014 | 11 | 2014 |

Towards confidence interval estimation in truth discovery H Xiao, J Gao, Q Li, F Ma, L Su, Y Feng, A Zhang IEEE Transactions on Knowledge and Data Engineering 31 (3), 575-588, 2018 | 10 | 2018 |

Learning with correntropy-induced losses for regression with mixture of symmetric stable noise Y Feng, Y Ying Applied and Computational Harmonic Analysis 48 (2), 795-810, 2020 | 8 | 2020 |

Learning with kernelized elastic net regularization Y Feng, Y Yang, Y Zhao, S Lv, JAK Suykens Internal Report, ESAT, KU Leuven, Leuven, Belgium, 2014 | 8 | 2014 |

Learning theory estimates with observations from general stationary stochastic processes H Hang, Y Feng, I Steinwart, JAK Suykens Neural Computation 28 (12), 2853-2889, 2016 | 7 | 2016 |

Least-squares regularized regression with dependent samples and q-penalty Y Feng Applicable Analysis 91 (5), 979-991, 2012 | 7 | 2012 |

Learning under (1+ ϵ)-moment conditions Y Feng, Q Wu Applied and Computational Harmonic Analysis 49 (2), 495-520, 2020 | 6 | 2020 |

Correntropy based matrix completion Y Yang, Y Feng, JAK Suykens Entropy 20 (3), 171, 2018 | 6 | 2018 |