Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Rückstieß, Thomas"'
Despite the popularity and widespread use of semi-structured data formats such as JSON, end-to-end supervised learning applied directly to such data remains underexplored. We present ORIGAMI (Object RepresentatIon via Generative Autoregressive Modell
Externí odkaz:
http://arxiv.org/abs/2412.17348
Publikováno v:
Paladyn, Vol 1, Iss 1, Pp 14-24 (2010)
This paper discusses parameter-based exploration methods for reinforcement learning. Parameter-based methods perturb parameters of a general function approximator directly, rather than adding noise to the resulting actions. Parameter-based exploratio
Externí odkaz:
https://doaj.org/article/1d7d7f4ee4c14115b57878db43f50fab
Autor:
Sehnke, Frank, Osendorfer, Christian, Rückstieß, Thomas, Graves, Alex, Peters, Jan, Schmidhuber, Jürgen
Publikováno v:
In Neural Networks 2010 23(4):551-559
Autor:
Rückstieß, Thomas Frank
This thesis discusses novel information processing methods and algorithms capable of directing attention to relevant details and analysing them in sequence to keep up with the data explosion that has been witnessed in the last decades. The concept of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______518::e583c36793941892d1318c8df29f4f50
https://mediatum.ub.tum.de/doc/1174677/document.pdf
https://mediatum.ub.tum.de/doc/1174677/document.pdf