Zobrazeno 1 - 10
of 49
pro vyhledávání: '"Akusok, Anton"'
Publikováno v:
International Conference on Extreme Learning Machine 2017 Oct 4 (pp. 240-248). Springer, Cham
The paper proposes to analyze a data set of Finnish ranks of academic publication channels with Extreme Learning Machine (ELM). The purpose is to introduce and test recently proposed ELM-based mislabel detection approach with a rich set of features c
Externí odkaz:
http://arxiv.org/abs/1912.09094
Publikováno v:
Int. J. Mach. Learn. & Cyber. (2019) 10: 991
Prediction intervals in supervised Machine Learning bound the region where the true outputs of new samples may fall. They are necessary in the task of separating reliable predictions of a trained model from near random guesses, minimizing the rate of
Externí odkaz:
http://arxiv.org/abs/1912.09090
Autor:
Akusok, Anton, Björk, Kaj-Mikael, Leal, Leonardo Espinosa, Miche, Yoan, Hu, Renjie, Lendasse, Amaury
Publikováno v:
Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments (PETRA '19). ACM, New York, NY, USA, 307-308. 2019
This concept paper highlights a recently opened opportunity for large scale analytical algorithms to be trained directly on edge devices. Such approach is a response to the arising need of processing data generated by natural person (a human being),
Externí odkaz:
http://arxiv.org/abs/1912.09083
Publikováno v:
Cao J., Vong C., Miche Y., Lendasse A. (eds) Proceedings of ELM-2017. ELM 2017. Proceedings in Adaptation, Learning and Optimization, vol 10. Springer, Cham
The paper proposes a new variant of a decision tree, called an Extreme Learning Tree. It consists of an extremely random tree with non-linear data transformation, and a linear observer that provides predictions based on the leaf index where the data
Externí odkaz:
http://arxiv.org/abs/1912.09087
Autor:
Akusok, Anton, Eirola, Emil, Miche, Yoan, Oliver, Ian, Björk, Kaj-Mikael, Gritsenko, Andrey, Baek, Stephen, Lendasse, Amaury
Publikováno v:
Proceedings of ELM-2016 (pp. 183-193). Springer, Cham
An incremental version of the ELMVIS+ method is proposed in this paper. It iteratively selects a few best fitting data samples from a large pool, and adds them to the model. The method keeps high speed of ELMVIS+ while allowing for much larger possib
Externí odkaz:
http://arxiv.org/abs/1912.08638
In this paper, we present a methodology and the corresponding Python library 1 for the classification of webpages. Our method retrieves a fixed number of images from a given webpage, and based on them classifies the webpage into a set of established
Externí odkaz:
http://arxiv.org/abs/1912.08644
Autor:
Akusok, Anton, Eirola, Emil
The big data trend has inspired feature-driven learning tasks, which cannot be handled by conventional machine learning models. Unstructured data produces very large binary matrices with millions of columns when converted to vector form. However, suc
Externí odkaz:
http://arxiv.org/abs/1912.08616
Autor:
Akusok, Anton
Publikováno v:
Theses and Dissertations.
Extreme Learning Machine (ELM) is a recently discovered way of training Single Layer Feed-forward Neural Networks with an explicitly given solution, which exists because the input weights and biases are generated randomly and never change. The method
Externí odkaz:
https://ir.uiowa.edu/etd/3036
https://ir.uiowa.edu/cgi/viewcontent.cgi?article=6380&context=etd
https://ir.uiowa.edu/cgi/viewcontent.cgi?article=6380&context=etd
Publikováno v:
In Journal of the Franklin Institute March 2018 355(4):1752-1779
Autor:
Akusok, Anton, Veganzones, David, Miche, Yoan, Björk, Kaj-Mikael, Jardin, Philippe du, Severin, Eric, Lendasse, Amaury
Publikováno v:
In Neurocomputing 2 July 2015 159:242-250