Stochastic Newton Method for Large Scale Nonlinear Support Vector Machine
碩士 === 國立交通大學 === 應用數學系數學建模與科學計算碩士班 === 104 === In this thesis, a stochastic Newton method is proposed to overcome the challenges of the conventional nonlinear support vector machines (SVMs) for extremely large scale dataset. Our idea comes from the scheme of stochastic optimization (or online learn...
Main Authors: | Tsai, Yi-En, 蔡宜恩 |
---|---|
Other Authors: | Wu, Chin-Tien |
Format: | Others |
Language: | en_US |
Published: |
2016
|
Online Access: | http://ndltd.ncl.edu.tw/handle/78983922536947277061 |
Similar Items
-
Online Nonlinear Support Vector Machine for Large-Scale Classification
by: Yi-Fan Chen, et al.
Published: (2014) -
Smooth Diagonal Weighted Newton Support Vector Machine
by: Jinjin Liang, et al.
Published: (2013-01-01) -
Quasi-Newton algorithms for large scale nonlinear systems
by: VandenBrink, Dennis Jay
Published: (2020) -
Stochastic Subgradient for Large-Scale Support Vector Machine Using the Generalized Pinball Loss Function
by: Wanida Panup, et al.
Published: (2021-09-01) -
A quasi-Newton algorithm for large-scale nonlinear equations
by: Linghua Huang
Published: (2017-02-01)