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2015


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Transition matrix elements for electron-phonon scattering: Phenomenological theory and ab initio electron theory

Illg, C., Haag, M., Müller, B. Y., Czycholl, G., Fähnle, M.

{Physical Review B}, 92(19), American Physical Society, Woodbury, NY, 2015 (article)

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DOI [BibTex]

2015


DOI [BibTex]


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Phase evolution in single-crystalline LiFePO4 followed by in situ scanning X-ray microscopy of a micrometre-sized battery

Ohmer, N., Fenk, B., Samuelis, D., Chen, C., Maier, J., Weigand, M., Goering, E., Schütz, G.

{Nature Communications}, 6, Nature Publishing Group, London, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Nitrogen-rich covalent triazine frameworks as high-performance platforms for selective carbon capture and storage

Hug, S., Stegbauer, L., Oh, H., Hirscher, M., Lotsch, B. V.

{Chemistry of Materials}, 27(23):8001-8010, American Chemical Society, Washington, D.C., 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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From Humans to Robots and Back: Role of Arm Movement in Medio-lateral Balance Control

Huber, M, Chiovetto, E, Schaal, S., Giese, M., Sternad, D

In Annual Meeting of Neural Control of Movement, Charleston, NC, 2015 (inproceedings)

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[BibTex]

[BibTex]


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Novel plasticity rule can explain the development of sensorimotor intelligence

Der, R., Martius, G.

Proceedings of the National Academy of Sciences, 112(45):E6224-E6232, 2015 (article)

Abstract
Grounding autonomous behavior in the nervous system is a fundamental challenge for neuroscience. In particular, self-organized behavioral development provides more questions than answers. Are there special functional units for curiosity, motivation, and creativity? This paper argues that these features can be grounded in synaptic plasticity itself, without requiring any higher-level constructs. We propose differential extrinsic plasticity (DEP) as a new synaptic rule for self-learning systems and apply it to a number of complex robotic systems as a test case. Without specifying any purpose or goal, seemingly purposeful and adaptive rhythmic behavior is developed, displaying a certain level of sensorimotor intelligence. These surprising results require no system-specific modifications of the DEP rule. They rather arise from the underlying mechanism of spontaneous symmetry breaking, which is due to the tight brain body environment coupling. The new synaptic rule is biologically plausible and would be an interesting target for neurobiological investigation. We also argue that this neuronal mechanism may have been a catalyst in natural evolution.

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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Multilayer Fresnel zone plates for X-ray microscopy

Sanli, U. T., Keskinbora, K., Grévent, C., Szeghalmi, A., Knez, M., Schütz, G.

{Microscopy and Microanalysis}, 21(Suppl 3):1987-1988, Springer-Verlag New York, New York, NY, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Interfacial dominated ferromagnetism in nanograined ZnO: a \muSR and DFT study

Tietze, T., Audehm, P., Chen, Y., Schütz, G., Straumal, B. B., Protasova, S. G., Mazilkin, A. A., Straumal, P. B., Prokscha, T., Luetkens, H., Salman, Z., Suter, A., Baretzky, B., Fink, K., Wenzel, W., Danilov, D., Goering, E.

{Scientific Reports}, 5, pages: 8871-8876, Nature Publishing Group, London, UK, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Preparation of a ferromagnetic barrier in YBa2Cu3O7-delta thinner than the coherence length

Soltan, S., Albrecht, J., Goering, E., Schütz, G., Mustafa, L., Keimer, B., Habermeier, H.

{Journal of Applied Physics}, 118(22), AIP Publishing, New York, NY, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Microanalytical methods for in-situ high-resolution analysis of rock varnish at the micrometer to nanometer scale

Macholdt, D. S., Jochum, K. P., Pöhlker, C., Stoll, B., Weis, U., Weber, B., Müller, M., Kapl, M., Buhre, S., Kilcoyne, A. L. D., Weigand, M., Scholz, D., Al-Amri, A. M., Andreae, M. O.

{Chemical Geology}, 411, pages: 57-68, Elsevier, Amsterdam, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Chemical composition, microstructure, and hygroscopic properties of aerosol particles at the Zotino Tall Tower Observatory (ZOTTO), Siberia, during a summer campaign

Mikhailov, E. F., Mironov, G. N., Pöhlker, C., Chi, X., Krüger, M., Shiraiwa, M., Förster, J., Pöschl, U., Vlasenko, S. S., Ryshkevich, T. I., Weigand, M., Kilcoyne, A. L. D., Andreae, M.

{Atmospheric Chemistry and Physics}, 15(15):8847-8869, European Geosciences Union, Katlenburg-Lindau, Germany, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Orbital reflectometry of PrNiO3/PrAlO3 superlattices

Wu, M., Benckiser, E., Audehm, P., Goering, E., Wochner, P., Christiani, G., Logvenov, G., Habermeier, H., Keimer, B.

{Physical Review B}, 91(19), American Physical Society, Woodbury, NY, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Dynamic domain wall chirality rectification by rotating magnetic fields

Bisig, A., Mawass, M., Stärk, M., Moutafis, C., Rhensius, J., Heidler, J., Gliga, S., Weigand, M., Tyliszczak, T., Van Waeyenberge, B., Stoll, H., Schütz, G., Kläui, M.

{Applied Physics Letters}, 106(12), American Institute of Physics, Melville, NY, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Ultrafast demagnetization after laser pulse irradiation in Ni: Ab-initio electron-phonon scattering and phase space calculations

Illg, C., Haag, M., Fähnle, M.

In Ultrafast Magnetism I. Proceedings of the International Conference UMC 2013, 159, pages: 131-133, Springer Proceedings in Physics, Springer, Strasbourg, 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Imaging spin dynamics on the nanoscale using X-ray microscopy

Stoll, H., Noske, M., Weigand, M., Richter, K., Krüger, B., Reeve, R. M., Hänze, M., Adolff, C. F., Stein, F., Meier, G., Kläui, M., Schütz, G.

{Frontiers in Physics}, 3, Frontiers Media, Lausanne, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Trajectory generation for multi-contact momentum control

Herzog, A., Rotella, N., Schaal, S., Righetti, L.

In 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids), pages: 874-880, IEEE, Seoul, South Korea, 2015 (inproceedings)

Abstract
Simplified models of the dynamics such as the linear inverted pendulum model (LIPM) have proven to perform well for biped walking on flat ground. However, for more complex tasks the assumptions of these models can become limiting. For example, the LIPM does not allow for the control of contact forces independently, is limited to co-planar contacts and assumes that the angular momentum is zero. In this paper, we propose to use the full momentum equations of a humanoid robot in a trajectory optimization framework to plan its center of mass, linear and angular momentum trajectories. The model also allows for planning desired contact forces for each end-effector in arbitrary contact locations. We extend our previous results on linear quadratic regulator (LQR) design for momentum control by computing the (linearized) optimal momentum feedback law in a receding horizon fashion. The resulting desired momentum and the associated feedback law are then used in a hierarchical whole body control approach. Simulation experiments show that the approach is computationally fast and is able to generate plans for locomotion on complex terrains while demonstrating good tracking performance for the full humanoid control.

am mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Structure Learning in Bayesian Sensorimotor Integration

Genewein, T, Hez, E, Razzaghpanah, Z, Braun, DA

PLoS Computational Biology, 11(8):1-27, August 2015 (article)

Abstract
Previous studies have shown that sensorimotor processing can often be described by Bayesian learning, in particular the integration of prior and feedback information depending on its degree of reliability. Here we test the hypothesis that the integration process itself can be tuned to the statistical structure of the environment. We exposed human participants to a reaching task in a three-dimensional virtual reality environment where we could displace the visual feedback of their hand position in a two dimensional plane. When introducing statistical structure between the two dimensions of the displacement, we found that over the course of several days participants adapted their feedback integration process in order to exploit this structure for performance improvement. In control experiments we found that this adaptation process critically depended on performance feedback and could not be induced by verbal instructions. Our results suggest that structural learning is an important meta-learning component of Bayesian sensorimotor integration.

ei

DOI [BibTex]

DOI [BibTex]


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Unique high-temperature performance of highly consensed MnBi permanent magnets

Chen, Y., Gregori, G., Leineweber, A., Qu, F., Chen, C., Tietze, T., Kronmüller, H., Schütz, G., Goering, E.

{Scripta Materialia}, 107, pages: 131-135, Pergamon, Tarrytown, NY, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Quantifying Emergent Behavior of Autonomous Robots

Martius, G., Olbrich, E.

Entropy, 17(10):7266, 2015 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Electrical determination of vortex state in submicron magnetic elements

Gangwar, A., Bauer, H. G., Chauleau, J., Noske, M., Weigand, M., Stoll, H., Schütz, G., Back, C. H.

{Physical Review B}, 91(9), American Physical Society, Woodbury, NY, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Mechanisms for the symmetric and antisymmetric switching of a magnetic vortex core: Differences and common aspects

Noske, M., Stoll, H., Fähnle, M., Hertel, R., Schütz, G.

{Physical Review B}, 91(1), American Physical Society, Woodbury, NY, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Automotive domain wall propagation in ferromagnetic rings

Richter, K., Mawass, M., Krone, A., Krüger, B., Weigand, M., Schütz, G., Stoll, H., Kläui, M.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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High resolution, high efficiency mulitlayer Fresnel zone plates for soft and hard X-rays

Sanli, U., Keskinbora, K., Gregorczyk, K., Leister, J., Teeny, N., Grévent, C., Knez, M., Schütz, G.

{Proceedings of SPIE}, 9592, SPIE, Bellingham, Washington, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Macroscopic drift current in the inverse Faraday effect

Hertel, R., Fähnle, M.

{Physical Review B}, 91(2), American Physical Society, Woodbury, NY, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Single-step 3D nanofabrication of kinoform optics via gray-scale focused ion beam lithography for efficient X-ray focusing

Keskinbora, K., Grévent, C., Hirscher, M., Weigand, M., Schütz, G.

{Advanced Optical Materials}, 3, pages: 792-800, WILEY-VCH Verlag GmbH Co. KGaA, Weinheim, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Band structure engineering of two-dimensional magnonic vortex crystals

Behncke, C., Hänze, M., Adolff, C. F., Weigand, M., Meier, G.

{Physical Review B}, 91(22), American Physical Society, Woodbury, NY, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Towards denoising XMCD movies of fast magnetization dynamics using extended Kalman filter

Kopp, M., Harmeling, S., Schütz, G., Schölkopf, B., Fähnle, M.

{Ultramicroscopy}, 148, pages: 115-122, North-Holland, Amsterdam, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Humanoid Momentum Estimation Using Sensed Contact Wrenches

Rotella, N., Herzog, A., Schaal, S., Righetti, L.

In 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids), pages: 556-563, IEEE, Seoul, South Korea, 2015 (inproceedings)

Abstract
This work presents approaches for the estimation of quantities important for the control of the momentum of a humanoid robot. In contrast to previous approaches which use simplified models such as the Linear Inverted Pendulum Model, we present estimators based on the momentum dynamics of the robot. By using this simple yet dynamically-consistent model, we avoid the issues of using simplified models for estimation. We develop an estimator for the center of mass and full momentum which can be reformulated to estimate center of mass offsets as well as external wrenches applied to the robot. The observability of these estimators is investigated and their performance is evaluated in comparison to previous approaches.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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A Reward-Maximizing Spiking Neuron as a Bounded Rational Decision Maker

Leibfried, F, Braun, DA

Neural Computation, 27(8):1686-1720, July 2015 (article)

Abstract
Rate distortion theory describes how to communicate relevant information most efficiently over a channel with limited capacity. One of the many applications of rate distortion theory is bounded rational decision making, where decision makers are modeled as information channels that transform sensory input into motor output under the constraint that their channel capacity is limited. Such a bounded rational decision maker can be thought to optimize an objective function that trades off the decision maker's utility or cumulative reward against the information processing cost measured by the mutual information between sensory input and motor output. In this study, we interpret a spiking neuron as a bounded rational decision maker that aims to maximize its expected reward under the computational constraint that the mutual information between the neuron's input and output is upper bounded. This abstract computational constraint translates into a penalization of the deviation between the neuron's instantaneous and average firing behavior. We derive a synaptic weight update rule for such a rate distortion optimizing neuron and show in simulations that the neuron efficiently extracts reward-relevant information from the input by trading off its synaptic strengths against the collected reward.

ei

DOI [BibTex]

DOI [BibTex]


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Magnetic moments induce strong phonon renormalization in FeSi

Krannich, S., Sidis, Y., Lamago, D., Heid, R., Mignot, J., von Löhneysen, H., Ivanov, A., Steffens, P., Keller, T., Wang, L., Goering, E., Weber, F.

{Nature Communications}, 6, Nature Publishing Group, London, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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What is epistemic value in free energy models of learning and acting? A bounded rationality perspective

Ortega, PA, Braun, DA

Cognitive Neuroscience, 6(4):215-216, December 2015 (article)

Abstract
Free energy models of learning and acting do not only care about utility or extrinsic value, but also about intrinsic value, that is, the information value stemming from probability distributions that represent beliefs or strategies. While these intrinsic values can be interpreted as epistemic values or exploration bonuses under certain conditions, the framework of bounded rationality offers a complementary interpretation in terms of information-processing costs that we discuss here.

ei

DOI [BibTex]

DOI [BibTex]


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Perpendicular magnetisation from in-plane fields in nano-scaled antidot lattices

Gräfe, J., Haering, F., Tietze, T., Audehm, P., Weigand, M., Wiedwald, U., Ziemann, P., Gawronski, P., Schütz, G., Goering, E. J.

{Nanotechnology}, 26(22), IOP Pub., Bristol, UK, 2015 (article)

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Theory of ultrafast demagnetization after femtosecond laser pulses

Fähnle, M., Illg, C., Haag, M., Teeny, N.

{Acta Physica Polonica A}, 127(2):170-175, Państwowe Wydawnictwo Naukowe, Warszawa, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Non-linear radial spinwave modes in thin magnetic disks

Helsen, M., Gangwar, Ajay, De Clercq, J., Vansteenkiste, A., Weigand, M., Back, C. H., Van Waeyenberge, B.

{Applied Physics Letters}, 106(3), American Institute of Physics, Melville, NY, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Hydrogen isotope separation in metal-organic frameworks: Kinetic or chemical affinity quantum-sieving?

Savchenko, I., Mavrandonakis, A., Heine, T., Oh, H., Teufel, J., Hirscher, M.

{Microporous and Mesoporous Materials}, 216, pages: 133-137, Elsevier, Amsterdam, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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High-resolution dichroic imaging of magnetic flux distributions in superconductors with scanning x-ray microscopy

Ruoß, S., Stahl, C., Weigand, M., Schütz, G., Albrecht, J.

{Applied Physics Letters}, 106, American Institute of Physics, Melville, NY, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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The third dimension: Vortex core reversal by interaction with \textquotesingleflexure modes’

Noske, M., Stoll, H., Fähnle, M., Weigand, M., Dieterle, G., Förster, J., Gangwar, A., Slavin, A., Back, C. H., Schütz, G.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Preparation and characterisation of epitaxial Pt/Cu/FeMn/Co thin films on (100)-oriented MgO single crystals

Schmidt, M., Gräfe, J., Audehm, P., Phillipp, F., Schütz, G., Goering, E.

{Physica Status Solidi A}, 212(10):2114-2123, Wiley-VCH, Weinheim, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Probing the magnetic moments of [MnIII6CrIII]3+ single-molecule magnets - A cross comparison of XMCD and spin-resolved electron spectroscopy

Helmstedt, A., Dohmeier, N., Müller, N., Gryzia, A., Brechling, A., Heinzmann, U., Hoeke, V., Krickemeyer, E., Glaser, T., Leicht, P., Fonin, M., Tietze, T., Joly, L., Kuepper, K.

{Journal of Electron Spectroscopy and Related Phenomena}, 198, pages: 12-19, Elsevier B.V., Amsterdam, 2015 (article)

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DOI [BibTex]

DOI [BibTex]


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Skyrmions at room temperature in magnetic multilayers

Moreau-Luchaire, C., Reyren, N., Moutafis, C., Sampaio, J., Van Horne, N., Vaz, C. A., Warnicke, P., Garcia, K., Weigand, M., Bouzehouane, K., Deranlot, C., George, J., Raabe, J., Cros, V., Fert, A.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]

2005


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Kernel Methods for Measuring Independence

Gretton, A., Herbrich, R., Smola, A., Bousquet, O., Schölkopf, B.

Journal of Machine Learning Research, 6, pages: 2075-2129, December 2005 (article)

Abstract
We introduce two new functionals, the constrained covariance and the kernel mutual information, to measure the degree of independence of random variables. These quantities are both based on the covariance between functions of the random variables in reproducing kernel Hilbert spaces (RKHSs). We prove that when the RKHSs are universal, both functionals are zero if and only if the random variables are pairwise independent. We also show that the kernel mutual information is an upper bound near independence on the Parzen window estimate of the mutual information. Analogous results apply for two correlation-based dependence functionals introduced earlier: we show the kernel canonical correlation and the kernel generalised variance to be independence measures for universal kernels, and prove the latter to be an upper bound on the mutual information near independence. The performance of the kernel dependence functionals in measuring independence is verified in the context of independent component analysis.

ei

PDF PostScript PDF [BibTex]

2005


PDF PostScript PDF [BibTex]


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Kernel ICA for Large Scale Problems

Jegelka, S., Gretton, A., Achlioptas, D.

In pages: -, NIPS Workshop on Large Scale Kernel Machines, December 2005 (inproceedings)

ei

Web [BibTex]

Web [BibTex]


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A Unifying View of Sparse Approximate Gaussian Process Regression

Quinonero Candela, J., Rasmussen, C.

Journal of Machine Learning Research, 6, pages: 1935-1959, December 2005 (article)

Abstract
We provide a new unifying view, including all existing proper probabilistic sparse approximations for Gaussian process regression. Our approach relies on expressing the effective prior which the methods are using. This allows new insights to be gained, and highlights the relationship between existing methods. It also allows for a clear theoretically justified ranking of the closeness of the known approximations to the corresponding full GPs. Finally we point directly to designs of new better sparse approximations, combining the best of the existing strategies, within attractive computational constraints.

ei

PDF [BibTex]

PDF [BibTex]


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Training Support Vector Machines with Multiple Equality Constraints

Kienzle, W., Schölkopf, B.

In Proceedings of the 16th European Conference on Machine Learning, Lecture Notes in Computer Science, Vol. 3720, pages: 182-193, (Editors: JG Carbonell and J Siekmann), Springer, Berlin, Germany, ECML, November 2005 (inproceedings)

Abstract
In this paper we present a primal-dual decomposition algorithm for support vector machine training. As with existing methods that use very small working sets (such as Sequential Minimal Optimization (SMO), Successive Over-Relaxation (SOR) or the Kernel Adatron (KA)), our method scales well, is straightforward to implement, and does not require an external QP solver. Unlike SMO, SOR and KA, the method is applicable to a large number of SVM formulations regardless of the number of equality constraints involved. The effectiveness of our algorithm is demonstrated on a more difficult SVM variant in this respect, namely semi-parametric support vector regression.

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Measuring Statistical Dependence with Hilbert-Schmidt Norms

Gretton, A., Bousquet, O., Smola, A., Schoelkopf, B.

In Algorithmic Learning Theory, Lecture Notes in Computer Science, Vol. 3734, pages: 63-78, (Editors: S Jain and H-U Simon and E Tomita), Springer, Berlin, Germany, 16th International Conference ALT, October 2005 (inproceedings)

Abstract
We propose an independence criterion based on the eigenspectrum of covariance operators in reproducing kernel Hilbert spaces (RKHSs), consisting of an empirical estimate of the Hilbert-Schmidt norm of the cross-covariance operator (we term this a Hilbert-Schmidt Independence Criterion, or HSIC). This approach has several advantages, compared with previous kernel-based independence criteria. First, the empirical estimate is simpler than any other kernel dependence test, and requires no user-defined regularisation. Second, there is a clearly defined population quantity which the empirical estimate approaches in the large sample limit, with exponential convergence guaranteed between the two: this ensures that independence tests based on {methodname} do not suffer from slow learning rates. Finally, we show in the context of independent component analysis (ICA) that the performance of HSIC is competitive with that of previously published kernel-based criteria, and of other recently published ICA methods.

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Maximal Margin Classification for Metric Spaces

Hein, M., Bousquet, O., Schölkopf, B.

Journal of Computer and System Sciences, 71(3):333-359, October 2005 (article)

Abstract
In order to apply the maximum margin method in arbitrary metric spaces, we suggest to embed the metric space into a Banach or Hilbert space and to perform linear classification in this space. We propose several embeddings and recall that an isometric embedding in a Banach space is always possible while an isometric embedding in a Hilbert space is only possible for certain metric spaces. As a result, we obtain a general maximum margin classification algorithm for arbitrary metric spaces (whose solution is approximated by an algorithm of Graepel. Interestingly enough, the embedding approach, when applied to a metric which can be embedded into a Hilbert space, yields the SVM algorithm, which emphasizes the fact that its solution depends on the metric and not on the kernel. Furthermore we give upper bounds of the capacity of the function classes corresponding to both embeddings in terms of Rademacher averages. Finally we compare the capacities of these function classes directly.

ei

PDF PDF DOI [BibTex]

PDF PDF DOI [BibTex]


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An Analysis of the Anti-Learning Phenomenon for the Class Symmetric Polyhedron

Kowalczyk, A., Chapelle, O.

In Algorithmic Learning Theory: 16th International Conference, pages: 78-92, Algorithmic Learning Theory, October 2005 (inproceedings)

Abstract
This paper deals with an unusual phenomenon where most machine learning algorithms yield good performance on the training set but systematically worse than random performance on the test set. This has been observed so far for some natural data sets and demonstrated for some synthetic data sets when the classification rule is learned from a small set of training samples drawn from some high dimensional space. The initial analysis presented in this paper shows that anti-learning is a property of data sets and is quite distinct from overfitting of a training data. Moreover, the analysis leads to a specification of some machine learning procedures which can overcome anti-learning and generate ma- chines able to classify training and test data consistently.

ei

PDF [BibTex]

PDF [BibTex]


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Selective integration of multiple biological data for supervised network inference

Kato, T., Tsuda, K., Asai, K.

Bioinformatics, 21(10):2488 , October 2005 (article)

ei

PDF [BibTex]

PDF [BibTex]


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Assessing Approximate Inference for Binary Gaussian Process Classification

Kuss, M., Rasmussen, C.

Journal of Machine Learning Research, 6, pages: 1679 , October 2005 (article)

Abstract
Gaussian process priors can be used to define flexible, probabilistic classification models. Unfortunately exact Bayesian inference is analytically intractable and various approximation techniques have been proposed. In this work we review and compare Laplace‘s method and Expectation Propagation for approximate Bayesian inference in the binary Gaussian process classification model. We present a comprehensive comparison of the approximations, their predictive performance and marginal likelihood estimates to results obtained by MCMC sampling. We explain theoretically and corroborate empirically the advantages of Expectation Propagation compared to Laplace‘s method.

ei

PDF PDF [BibTex]

PDF PDF [BibTex]


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Clustering on the Unit Hypersphere using von Mises-Fisher Distributions

Banerjee, A., Dhillon, I., Ghosh, J., Sra, S.

Journal of Machine Learning Research, 6, pages: 1345-1382, September 2005 (article)

Abstract
Several large scale data mining applications, such as text categorization and gene expression analysis, involve high-dimensional data that is also inherently directional in nature. Often such data is L2 normalized so that it lies on the surface of a unit hypersphere. Popular models such as (mixtures of) multi-variate Gaussians are inadequate for characterizing such data. This paper proposes a generative mixture-model approach to clustering directional data based on the von Mises-Fisher (vMF) distribution, which arises naturally for data distributed on the unit hypersphere. In particular, we derive and analyze two variants of the Expectation Maximization (EM) framework for estimating the mean and concentration parameters of this mixture. Numerical estimation of the concentration parameters is non-trivial in high dimensions since it involves functional inversion of ratios of Bessel functions. We also formulate two clustering algorithms corresponding to the variants of EM that we derive. Our approach provides a theoretical basis for the use of cosine similarity that has been widely employed by the information retrieval community, and obtains the spherical kmeans algorithm (kmeans with cosine similarity) as a special case of both variants. Empirical results on clustering of high-dimensional text and gene-expression data based on a mixture of vMF distributions show that the ability to estimate the concentration parameter for each vMF component, which is not present in existing approaches, yields superior results, especially for difficult clustering tasks in high-dimensional spaces.

ei

PDF [BibTex]

PDF [BibTex]


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Support Vector Machines for 3D Shape Processing

Steinke, F., Schölkopf, B., Blanz, V.

Computer Graphics Forum, 24(3, EUROGRAPHICS 2005):285-294, September 2005 (article)

Abstract
We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which are state of the art in machine learning. It is straightforward to implement and computationally competitive; its parameters can be automatically set using standard machine learning methods. The surface approximation is based on a modified Support Vector regression. We present applications to 3D head reconstruction, including automatic removal of outliers and hole filling. In a second step, we build on our SV representation to compute dense 3D deformation fields between two objects. The fields are computed using a generalized SVMachine enforcing correspondence between the previously learned implicit SV object representations, as well as correspondences between feature points if such points are available. We apply the method to the morphing of 3D heads and other objects.

ei

PDF [BibTex]

PDF [BibTex]