Search Results for author: Kaj-Mikael Björk

Found 6 papers, 0 papers with code

Per-sample Prediction Intervals for Extreme Learning Machines

no code implementations19 Dec 2019 Anton Akusok, Yoan Miche, Kaj-Mikael Björk, Amaury Lendasse

Prediction intervals in supervised Machine Learning bound the region where the true outputs of new samples may fall.

BIG-bench Machine Learning Prediction Intervals

Spiking Networks for Improved Cognitive Abilities of Edge Computing Devices

no code implementations19 Dec 2019 Anton Akusok, Kaj-Mikael Björk, Leonardo Espinosa Leal, Yoan Miche, Renjie Hu, Amaury Lendasse

This concept paper highlights a recently opened opportunity for large scale analytical algorithms to be trained directly on edge devices.

Edge-computing

Extreme Learning Tree

no code implementations19 Dec 2019 Anton Akusok, Emil Eirola, Kaj-Mikael Björk, Amaury Lendasse

The paper proposes a new variant of a decision tree, called an Extreme Learning Tree.

Mislabel Detection of Finnish Publication Ranks

no code implementations19 Dec 2019 Anton Akusok, Mirka Saarela, Tommi Kärkkäinen, Kaj-Mikael Björk, Amaury Lendasse

The paper proposes to analyze a data set of Finnish ranks of academic publication channels with Extreme Learning Machine (ELM).

A Web Page Classifier Library Based on Random Image Content Analysis Using Deep Learning

no code implementations18 Dec 2019 Leonardo Espinosa Leal, Kaj-Mikael Björk, Amaury Lendasse, Anton Akusok

The results show that the best method of classifying a webpage into the studies classes is to assign the class according to the maximum probability of any image belonging to this (weapon) class being above the threshold, across all the retrieved images.

General Classification Image Classification

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