109 citations · 709 across the 84 of their papers we have counts for
5 papers · 1 filter
Random Fourier Features via Fast Surrogate Leverage Weighted Sampling
Fanghui Liu, Xiaolin Huang, Yudong Chen +2
In this paper, we propose a fast surrogate leverage weighted sampling strategy to generate refined random Fourier features for kernel approximation. Compared to the current state-o…
Generative Restricted Kernel Machines: A Framework for Multi-view Generation and Disentangled Feature Learning
Arun Pandey, Joachim Schreurs, Johan A. K. Suykens
This paper introduces a novel framework for generative models based on Restricted Kernel Machines (RKMs) with joint multi-view generation and uncorrelated feature learning, called…
Two-stage Best-scored Random Forest for Large-scale Regression
Hanyuan Hang, Yingyi Chen, Johan A. K. Suykens
We propose a novel method designed for large-scale regression problems, namely the two-stage best-scored random forest (TBRF). "Best-scored" means to select one regression tree wit…
Nyström landmark sampling and regularized Christoffel functions
Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens
Selecting diverse and important items, called landmarks, from a large set is a problem of interest in machine learning. As a specific example, in order to deal with large training…
Efficient hinging hyperplanes neural network and its application in nonlinear system identification
Jun Xu, Qinghua Tao, Zhen Li +3
In this paper, the efficient hinging hyperplanes (EHH) neural network is proposed based on the model of hinging hyperplanes (HH). The EHH neural network is a distributed representa…