Generative Restricted Kernel Machines

Arun Pandey, Joachim Schreurs, Johan A.K. Suykens

TL;DR: Gen-RKM: a novel framework for generative models using Restricted Kernel Machines with multi-view generation and uncorrelated feature learning.

Abstract: We introduce a novel framework for generative models based on Restricted Kernel Machines (RKMs) with multi-view generation and uncorrelated feature learning capabilities, called Gen-RKM. To incorporate multi-view generation, this mechanism uses a shared representation of data from various views. The mechanism is flexible to incorporate both kernel-based, (deep) neural network and convolutional based models within the same setting. To update the parameters of the network, we propose a novel training procedure which jointly learns the features and shared representation. Experiments demonstrate the potential of the framework through qualitative evaluation of generated samples.

Keywords: Generative models, Kernel methods, Deep learning

Community Implementations: [ 1 code implementation](https://www.catalyzex.com/paper/arxiv:1906.08144/code)