Zobrazeno 1 - 10
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pro vyhledávání: '"Bongard, Josh C."'
Generally intelligent agents exhibit successful behavior across problems in several settings. Endemic in approaches to realize such intelligence in machines is catastrophic forgetting: sequential learning corrupts knowledge obtained earlier in the se
Externí odkaz:
http://arxiv.org/abs/1804.04286
Typically, AI researchers and roboticists try to realize intelligent behavior in machines by tuning parameters of a predefined structure (body plan and/or neural network architecture) using evolutionary or learning algorithms. Another but not unrelat
Externí odkaz:
http://arxiv.org/abs/1804.02257
Publikováno v:
IEEE Systems Journal, 2018
Crowdsourcing has been successfully applied in many domains including astronomy, cryptography and biology. In order to test its potential for useful application in a Smart Grid context, this paper investigates the extent to which a crowd can contribu
Externí odkaz:
http://arxiv.org/abs/1709.02739
Publikováno v:
Parallel Problem Solving from Nature - PPSN XIV. PPSN 2016. Lecture Notes in Computer Science, vol 9921. Springer, Cham
Satellite imagery and remote sensing provide explanatory variables at relatively high resolutions for modeling geospatial phenomena, yet regional summaries are often desirable for analysis and actionable insight. In this paper, we propose a novel met
Externí odkaz:
http://arxiv.org/abs/1706.07888
Different subsystems of organisms adapt over many time scales, such as rapid changes in the nervous system (learning), slower morphological and neurological change over the lifetime of the organism (postnatal development), and change over many genera
Externí odkaz:
http://arxiv.org/abs/1706.07296
Autor:
Allgaier, Nicholas, Banaschewski, Tobias, Barker, Gareth, Bokde, Arun L. W., Bongard, Josh C., Bromberg, Uli, Büchel, Christian, Cattrell, Anna, Conrod, Patricia J., Danforth, Christopher M., Desrivières, Sylvane, Dodds, Peter S., Flor, Herta, Frouin, Vincent, Gallinat, Jürgen, Gowland, Penny, Heinz, Andreas, Ittermann, Bernd, Mackey, Scott, Martinot, Jean-Luc, Murphy, Kevin, Nees, Frauke, Papadopoulos-Orfanos, Dimitri, Poustka, Luise, Smolka, Michael N., Walter, Henrik, Whelan, Robert, Schumann, Gunter, Garavan, Hugh, Consortium, IMAGEN
The field of neuroimaging has truly become data rich, and novel analytical methods capable of gleaning meaningful information from large stores of imaging data are in high demand. Those methods that might also be applicable on the level of individual
Externí odkaz:
http://arxiv.org/abs/1510.03765
Publikováno v:
IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 43, no. 1, pp. 176 - 185, 2013
Generating models from large data sets -- and determining which subsets of data to mine -- is becoming increasingly automated. However choosing what data to collect in the first place requires human intuition or experience, usually supplied by a doma
Externí odkaz:
http://arxiv.org/abs/1203.1833
Autor:
BONGARD, JOSH C.1 (AUTHOR) josh.bongard@uvm.edu
Publikováno v:
Communications of the ACM. Aug2013, Vol. 56 Issue 8, p74-83. 10p. 1 Color Photograph, 1 Diagram.
Publikováno v:
In Neural Networks 2010 23(8):1113-1124