Adaptive projected subgradient method

The adaptive projected subgradient method (APSM) is an algorithm, the goal of which is to minimize iteratively a sequence of cost functions.[1][2][3]

This algorithmic "tool" is general and has been used in several tasks, such as online/adaptive parameter estimation, online classification,[4] [5] and adaptive distributed learning.[6] The algorithm can be used in both linear and non-linear scenarios (using kernels[7][8][9][10]).

References

  1. ↑ Yamada, I.; Ogura, N. (2003). "Adaptive projected subgradient method and its applications to set theoretic adaptive filtering". The Thirty-seventh Asilomar Conference on Signals, Systems & Computers, 2003. p. 600. doi:10.1109/ACSSC.2003.1291982. ISBN 0-7803-8104-1.
  2. ↑ Yamada, I.; Ogura, N. (2005). "Adaptive Projected Subgradient Method for Asymptotic Minimization of Sequence of Nonnegative Convex Functions". Numerical Functional Analysis and Optimization 25 (7–8): 593. doi:10.1081/NFA-200045806.
  3. ↑ Slavakis, Konstantinos; Yamada, Isao (5 August 2011). "The adaptive projected subgradient method constrained by families of quasi-nonexpansive mappings and its application to online learning". Ithaca, New York: Cornell University.
  4. ↑ Slavakis, Konstantinos, Sergios Theodoridis, and Isao Yamada. "Online kernel-based classification using adaptive projection algorithms." Signal Processing, IEEE Transactions on 56.7 (2008): 2781-2796.
  5. ↑ OĞUZ, ÖZKAN. PERFORMANCE OF A NON-LINEAR ADAPTIVE BEAMFORMER ALGORITHM FOR SIGNAL-OF-INTEREST EXTRACTION. Diss. MIDDLE EAST TECHNICAL UNIVERSITY, 2015.
  6. ↑ Chouvardas, Symeon, Konstantinos Slavakis, and Sergios Theodoridis. "Adaptive robust distributed learning in diffusion sensor networks." Signal Processing, IEEE Transactions on 59.10 (2011): 4692-4707.
  7. ↑ Slavakis, K.; Bouboulis, P.; Theodoridis, S. (2012-02-01). "Adaptive Multiregression in Reproducing Kernel Hilbert Spaces: The Multiaccess MIMO Channel Case". IEEE Transactions on Neural Networks and Learning Systems 23 (2): 260–276. doi:10.1109/TNNLS.2011.2178321. ISSN 2162-237X.
  8. ↑ Bouboulis, P.; Slavakis, K.; Theodoridis, S. (2012-03-01). "Adaptive Learning in Complex Reproducing Kernel Hilbert Spaces Employing Wirtinger's Subgradients". IEEE Transactions on Neural Networks and Learning Systems 23 (3): 425–438. doi:10.1109/TNNLS.2011.2179810. ISSN 2162-237X.
  9. ↑ Theodoridis, Sergios (2013). Academic Press Library in Signal Processing. CHAPTER 17 Online Learning in Reproducing Kernel Hilbert Spaces- Konstantinos Slavakis, Pantelis Bouboulis and Sergios Theodoridis: ACADEMIC PRESS. ISBN 978-0-12-397226-2.
  10. ↑ "Source code for Kernel APSM".
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