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Scalable Kernel Logistic Regression with Nyström Approximation:
  Theoretical Analysis and Application to Discrete Choice Modelling

Scalable Kernel Logistic Regression with Nyström Approximation: Theoretical Analysis and Application to Discrete Choice Modelling

9 February 2024
José Ángel Martín-Baos
Ricardo García-Ródenas
Luis Rodriguez-Benitez
Michel Bierlaire
ArXivPDFHTML

Papers citing "Scalable Kernel Logistic Regression with Nyström Approximation: Theoretical Analysis and Application to Discrete Choice Modelling"

2 / 2 papers shown
Title
Nonlinear Principal Component Analysis with Random Bernoulli Features for Process Monitoring
Nonlinear Principal Component Analysis with Random Bernoulli Features for Process Monitoring
Ke Chen
Dandan Jiang
59
0
0
16 Mar 2025
Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark
Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark
Shenhao Wang
Baichuan Mo
Stephane Hess
Jinhuan Zhao
Jinhua Zhao
40
2
0
01 Feb 2021
1