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Approximated Infomax Early Stopping: Revisiting Gaussian RBMs on Natural Images [article]

Taichi Kiwaki, Takaki Makino, Kazuyuki Aihara
2014 arXiv   pre-print
We pursue an early stopping technique that helps Gaussian Restricted Boltzmann Machines (GRBMs) to gain good natural image representations in terms of overcompleteness and data fitting.  ...  To gain GRBM representations that are overcomplete and fit data well, we propose a measure for GRBM representation quality, approximated mutual information, and an early stopping technique based on this  ...  This research is supported by the Aihara Innovative Mathematical Modelling Project, the Japan Society for the Promotion of Science (JSPS) through the Funding Program for World-Leading Innovative R&D on  ... 
arXiv:1312.5412v3 fatcat:nyyhbekdafbyhn5trwwpazulfq

A Brief Introduction to Machine Learning for Engineers [article]

Osvaldo Simeone
2018 arXiv   pre-print
The treatment concentrates on probabilistic models for supervised and unsupervised learning problems.  ...  The material is organized according to clearly defined categories, such as discriminative and generative models, frequentist and Bayesian approaches, exact and approximate inference, as well as directed  ...  One approach is to modify the optimization scheme by using techniques such as early stopping [56] .  ... 
arXiv:1709.02840v3 fatcat:4ivew7im6ndyhgzdymval3jh2m

Utilizing Brain-Computer Interfaces for Human-Machine Systems

Thorsten Oliver Zander, Technische Universität Berlin, Technische Universität Berlin, Matthias Roetting
Based on a detailed description of the state-of-the-art in BCI research I identify unreliability, limited bandwidth of information transfer, high cognitive effort and cumbersome and time-consuming preparation  ...  In one session, approximately 40 rounds were played in both modes.  ...  extremities is a natural concept.  ... 
doi:10.14279/depositonce-3231 fatcat:4vbvxkqfovgczoapkxyn5gwv4a