Yunlong Feng

Ph.D. Associate Professor [CV]
Department of Mathematics and Statistics
State University of New York at Albany
Albany, NY 12222, USA
Office: Catskill Building 377
Email: ylfeng at albany.edu
Phone: +1 518 4424611

Research Interests

Machine learning: theory, methods, and applications

Instructed Courses

  • AMAT101 Algebra and Calculus I
  • AMAT108 Elementary Statistics
  • AMAT112 Calculus I
  • AMAT214 Calculus of Several Variables
  • AMAT363 Statistics
  • AMAT367 Discrete Probability
  • AMAT465/565 Applied Statistics
  • AMAT591 Optimization Methods and Nonlinear Programming
  • AMAT592 Machine Learning
  • AMAT810 Time Series Analysis

Recent Papers

  • S. Huang, Y. Feng, and Q. Wu. Fast rates of Gaussian empirical gain maximization with heavy-tailed noise. TNNLS, in press.
  • Y. Feng and Q. Wu. Tikhonov regularization for Gaussian empirical gain maximization in RKHS is consistent. Submitted, 2023.
  • Y. Feng and Q. Wu. A statistical learning assessment of Huber regression. Journal of Approximation Theory, 273: 105660, 2022.
  • Y. Feng and Q. Wu. A framework of learning through empirical gain maximization. Neural Computation, 33(6):1656-1697, 2021.
  • Y. Feng. New insights into learning with correntropy based regression. Neural Computation, 33(1):157-173, 2021.
  • Y. Feng and Q. Wu. Learning under (1+ε)-moment conditions. Applied and Computational Harmonic Analysis, 49(2): 495-520, 2020.
  • Y. Feng, J. Fan, and J. Suykens. A statistical learning approach to modal regression. Journal of Machine Learning Research, 21(2):1-35, 2020.
  • Y. Feng and Y. Ying. Learning with correntropy-induced losses for regression with mixture of symmetric stable noise. Applied and Computational Harmonic Analysis, 48(2):795-810, 2020.