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2002


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Initial oxidation of AlPdMn quasicrystals - A study by high-resolution RBS and ERDA

Plachke, D., Khellaf, A., Carstanjen, H. D.

{Nuclear Instruments \& Methods in Physics Research B}, 190, pages: 646-651, 2002 (article)

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[BibTex]

2002


[BibTex]


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The Verwey transition - a topical review

Walz, F.

{Journal of Physics-Condensed Matter}, 14(12):R285-R340, 2002 (article)

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[BibTex]

[BibTex]


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Composition dependence of the Zener relaxation in high-purity FeCr single crystals

Hirscher, M., Ege, M.

{Materials \textquotesingleTransactions JIM}, 43(2):182-185, 2002 (article)

mms

[BibTex]

[BibTex]


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Hydrogen storage in carbon nanostructures

Hirscher, M., Becher, M., Haluska, M., Quintel, A., Skakalova, V., Choi, Y. M., Dettlaff-Weglikowska, U., Roth, S., Stepanek, I., Bernier, P., Leonhardt, A., Fink, J.

{Journal of Alloys and Compounds}, 330, pages: 654-658, 2002 (article)

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[BibTex]

[BibTex]


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Micromagnetic investigation of sub-100-nm magnetic domains in atomically stacked Fe(001)/Au(001) multilayers

Köhler, M., Zweck, J., Bayreuther, G., Fischer, P., Schütz, G., Denbeaux, G., Attwood, D.

{Journal of Magnetism and Magnetic Materials}, 240, pages: 79-82, 2002 (article)

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DOI [BibTex]

DOI [BibTex]


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Experimental Study of a Crystal Positron Source

Chehab, R., Cizeron, R., Sylvia, C., Baier, V., Beloborodov, K., Bukin, A., Burdin, S., Dimova, T., Drozdetsky, A., Druzhinin, V., Dubrovin, M., Golubev, V., Serednyakov, S., Shary, V., Strakhovenko, V., Artru, X., Chevallier, M., Dauvergne, D., Kirsch, R., Lautesse, P., Poizat, J. C., Remillieux, J., Jejcic, A., Keppler, P., Major, J., Gatignon, L., Bochek, G., Kulibaba, V., Maslov, N., Bogdanov, A., Potylitsin, A., Vnukov, I.

{Physics Letters B}, 525, pages: 41-48, 2002 (article)

mms

[BibTex]

[BibTex]

1995


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Memory-based neural networks for robot learning

Atkeson, C. G., Schaal, S.

Neurocomputing, 9, pages: 1-27, 1995, clmc (article)

Abstract
This paper explores a memory-based approach to robot learning, using memory-based neural networks to learn models of the task to be performed. Steinbuch and Taylor presented neural network designs to explicitly store training data and do nearest neighbor lookup in the early 1960s. In this paper their nearest neighbor network is augmented with a local model network, which fits a local model to a set of nearest neighbors. This network design is equivalent to a statistical approach known as locally weighted regression, in which a local model is formed to answer each query, using a weighted regression in which nearby points (similar experiences) are weighted more than distant points (less relevant experiences). We illustrate this approach by describing how it has been used to enable a robot to learn a difficult juggling task. Keywords: memory-based, robot learning, locally weighted regression, nearest neighbor, local models.

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link (url) [BibTex]

1995


link (url) [BibTex]