Header logo is mms


2018


no image
Direct observations of sub-100 nm spin wave propagation in magnonic wave-guides

Träger, N., Gruszecki, P., Lisiecki, F., Förster, J., Weigand, M., Kuswik, P., Dubowik, J., Schütz, G., Krawczyk, M., Gräfe, J.

In 2018 IEEE International Magnetics Conference (INTERMAG 2018), IEEE, Singapore, 2018 (inproceedings)

DOI [BibTex]

2018

DOI [BibTex]


no image
Interpreting FORC diagrams beyond the Preisach model: an experimental permalloy micro array investigation

Gross, F., Ilse, S., Schütz, G., Gräfe, J., Goering, E.

In 2018 IEEE International Magnetics Conference (INTERMAG 2018), IEEE, Singapore, 2018 (inproceedings)

DOI [BibTex]

DOI [BibTex]

2014


no image
Increasing the sensor performance using Au modified high temperature superconducting YBa2Cu3O7-delta thin films

Katzer, C., Stahl, C., Michalowski, P., Treiber, S., Westernhausen, M., Schmidl, F., Seidel, P., Schütz, G., Albrecht, J.

In {Journal of Physics: Condensed Matter}, 507, IOP Pub., Genova, Italy, 2014 (inproceedings)

DOI [BibTex]

2014

DOI [BibTex]

2011


no image
Amorphous grain boundary layers in the ferromagnetic nanograined ZnO films

Straumal, B. B., Mazilkin, A. A., Protasova, S. G., Myatiev, A. A., Straumal, P. B., Goering, E., Baretzky, B.

In {Thin Solid Films}, 520, pages: 1192-1194, Hersonissos, Greece, 2011 (inproceedings)

DOI [BibTex]

2011

DOI [BibTex]


no image
Inversed solid-phase grain boundary wetting in the Al-Zn system

Protasova, S. G., Kogtenkova, O. A., Straumal, B. B., Zieba, P., Baretzky, B.

In {Interface Science Issue}, 46, pages: 4349-4353, Mie, Japan, 2011 (inproceedings)

DOI [BibTex]

DOI [BibTex]


no image
First measurement of the heat effect of the grain boundary wetting phase transition

Straumal, B. B., Kogtenkova, O. A., Protasova, S. G., Zieba, P., Czeppe, T., Baretzky, B., Valiev, R. Z.

In {Interface Science Issue}, 46, pages: 4243, Mie, Japan, 2011 (inproceedings)

DOI [BibTex]

DOI [BibTex]


no image
Transmission electron microscopy investigation of boundaries between amorphous "grains" in Ni50Nb20Y30 alloy

Mazilkin, A. A., Abrosimova, G. E., Protasova, S. G., Straumal, B. B., Schütz, G., Dobatkin, S. V., Bakai, A. S.

In {Journal of Materials Science}, 46, pages: 4336-4342, Mie, Japan, 2011 (inproceedings)

DOI [BibTex]

DOI [BibTex]


no image
Projected Newton-type methods in machine learning

Schmidt, M., Kim, D., Sra, S.

In Optimization for Machine Learning, pages: 305-330, MIT Press, Cambridge, MA, USA, 2011 (incollection)

Abstract
{We consider projected Newton-type methods for solving large-scale optimization problems arising in machine learning and related fields. We first introduce an algorithmic framework for projected Newton-type methods by reviewing a canonical projected (quasi-)Newton method. This method, while conceptually pleasing, has a high computation cost per iteration. Thus, we discuss two variants that are more scalable, namely, two-metric projection and inexact projection methods. Finally, we show how to apply the Newton-type framework to handle non-smooth objectives. Examples are provided throughout the chapter to illustrate machine learning applications of our framework.}

link (url) [BibTex]

link (url) [BibTex]