Corrigendum to “Ensembling neural networks: Many could be better than all” [Artificial Intelligence 137 (1–2) (2002) 239–263] [Book Review]

, &
Artificial Intelligence 174 (18):1570 (2010)
  Copy   BIBTEX

Abstract

This article has no associated abstract. (fix it)

Categories

Keywords

Reprint years

DOI

10.1016/j.artint.2010.10.001

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 91,386

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

My notes

Similar books and articles

Ensembling neural networks: Many could be better than all.Zhi-Hua Zhou, Jianxin Wu & Wei Tang - 2002 - Artificial Intelligence 137 (1-2):239-263.
What are neural networks not good at? On artificial creativity.Anton Oleinik - 2019 - Big Data and Society 6 (1).
Out of their minds: Legal theory in neural networks. [REVIEW]Dan Hunter - 1999 - Artificial Intelligence and Law 7 (2-3):129-151.
Diabetes Prediction Using Artificial Neural Network.Nesreen Samer El_Jerjawi & Samy S. Abu-Naser - 2018 - International Journal of Advanced Science and Technology 121:54-64.
Connectionism and artificial intelligence as cognitive models.Daniel Memmi - 1990 - AI and Society 4 (2):115-136.
Artificial intelligence and symbols.Chris Moss - 1989 - AI and Society 3 (4):345-356.
Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human Representations.Joshua C. Peterson, Joshua T. Abbott & Thomas L. Griffiths - 2018 - Cognitive Science 42 (8):2648-2669.
Neural networks in artificial intelligence.David S. Touretzky - 1993 - Artificial Intelligence 62 (1):163-164.
What is Interpretability?Adrian Erasmus, Tyler D. P. Brunet & Eyal Fisher - 2021 - Philosophy and Technology 34:833–862.
On the artificiality of artificial intelligence.Hans F. M. Crombag - 1993 - Artificial Intelligence and Law 2 (1):39-49.
Artificial nonmonotonic neural networks.B. Boutsinas & M. N. Vrahatis - 2001 - Artificial Intelligence 132 (1):1-38.
Knowledge-based artificial neural networks.Geoffrey G. Towell & Jude W. Shavlik - 1994 - Artificial Intelligence 70 (1-2):119-165.
Optimal modular feedforward neural networks based on functional networks.A. S. Cofino & J. M. Gutiérrez - 2001 - In P. Bouquet (ed.), Lecture Notes in Artificial Intelligence. Kluwer Academic Publishers. pp. 2083--308.
Higher-order Petri net models based on artificial neural networks.Tommy W. S. Chow & Jin-Yan Li - 1997 - Artificial Intelligence 92 (1-2):289-300.
Stacked neural networks must emulate evolution's hierarchical complexity.Michael Lamport Commons - 2008 - World Futures 64 (5-7):444 – 451.

Analytics

Added to PP
2020-12-22

Downloads
8 (#1,291,989)

6 months
6 (#512,819)

Historical graph of downloads
How can I increase my downloads?

Citations of this work

No citations found.

Add more citations

References found in this work

Add more references