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2008


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The Gilbert equation revisited: anisotropic and nonlocal damping of magnetization dynamics

Fähnle, M., Steiauf, D., Seib, J.

{Journal of Physics D}, 41, 2008 (article)

mms

DOI [BibTex]

2008


DOI [BibTex]

2003


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Support Vector Channel Selection in BCI

Lal, T., Schröder, M., Hinterberger, T., Weston, J., Bogdan, M., Birbaumer, N., Schölkopf, B.

(120), Max Planck Institute for Biological Cybernetics, Tuebingen, Germany, December 2003 (techreport)

Abstract
Designing a Brain Computer Interface (BCI) system one can choose from a variety of features that may be useful for classifying brain activity during a mental task. For the special case of classifying EEG signals we propose the usage of the state of the art feature selection algorithms Recursive Feature Elimination [3] and Zero-Norm Optimization [13] which are based on the training of Support Vector Machines (SVM) [11]. These algorithms can provide more accurate solutions than standard filter methods for feature selection [14]. We adapt the methods for the purpose of selecting EEG channels. For a motor imagery paradigm we show that the number of used channels can be reduced significantly without increasing the classification error. The resulting best channels agree well with the expected underlying cortical activity patterns during the mental tasks. Furthermore we show how time dependent task specific information can be visualized.

ei

PDF Web [BibTex]

2003


PDF Web [BibTex]


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Concentration Inequalities for Sub-Additive Functions Using the Entropy Method

Bousquet, O.

Stochastic Inequalities and Applications, 56, pages: 213-247, Progress in Probability, (Editors: Giné, E., C. Houdré and D. Nualart), November 2003 (article)

Abstract
We obtain exponential concentration inequalities for sub-additive functions of independent random variables under weak conditions on the increments of those functions, like the existence of exponential moments for these increments. As a consequence of these general inequalities, we obtain refinements of Talagrand's inequality for empirical processes and new bounds for randomized empirical processes. These results are obtained by further developing the entropy method introduced by Ledoux.

ei

PostScript [BibTex]

PostScript [BibTex]


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Image Reconstruction by Linear Programming

Tsuda, K., Rätsch, G.

(118), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, October 2003 (techreport)

ei

PDF [BibTex]

PDF [BibTex]


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Statistical Learning Theory, Capacity and Complexity

Schölkopf, B.

Complexity, 8(4):87-94, July 2003 (article)

Abstract
We give an exposition of the ideas of statistical learning theory, followed by a discussion of how a reinterpretation of the insights of learning theory could potentially also benefit our understanding of a certain notion of complexity.

ei

Web DOI [BibTex]


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Ranking on Data Manifolds

Zhou, D., Weston, J., Gretton, A., Bousquet, O., Schölkopf, B.

(113), Max Planck Institute for Biological Cybernetics, 72076 Tuebingen, Germany, June 2003 (techreport)

Abstract
The Google search engine has had a huge success with its PageRank web page ranking algorithm, which exploits global, rather than local, hyperlink structure of the World Wide Web using random walk. This algorithm can only be used for graph data, however. Here we propose a simple universal ranking algorithm for vectorial data, based on the exploration of the intrinsic global geometric structure revealed by a huge amount of data. Experimental results from image and text to bioinformatics illustrates the validity of our algorithm.

ei

PDF [BibTex]

PDF [BibTex]


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Kernel Hebbian Algorithm for Iterative Kernel Principal Component Analysis

Kim, K., Franz, M., Schölkopf, B.

(109), MPI f. biologische Kybernetik, Tuebingen, June 2003 (techreport)

Abstract
A new method for performing a kernel principal component analysis is proposed. By kernelizing the generalized Hebbian algorithm, one can iteratively estimate the principal components in a reproducing kernel Hilbert space with only linear order memory complexity. The derivation of the method, a convergence proof, and preliminary applications in image hyperresolution are presented. In addition, we discuss the extension of the method to the online learning of kernel principal components.

ei

PDF [BibTex]

PDF [BibTex]


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Learning with Local and Global Consistency

Zhou, D., Bousquet, O., Lal, T., Weston, J., Schölkopf, B.

(112), Max Planck Institute for Biological Cybernetics, Tuebingen, Germany, June 2003 (techreport)

Abstract
We consider the learning problem in the transductive setting. Given a set of points of which only some are labeled, the goal is to predict the label of the unlabeled points. A principled clue to solve such a learning problem is the consistency assumption that a classifying function should be sufficiently smooth with respect to the structure revealed by these known labeled and unlabeled points. We present a simple algorithm to obtain such a smooth solution. Our method yields encouraging experimental results on a number of classification problems and demonstrates effective use of unlabeled data.

ei

[BibTex]

[BibTex]


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Dealing with large Diagonals in Kernel Matrices

Weston, J., Schölkopf, B., Eskin, E., Leslie, C., Noble, W.

Annals of the Institute of Statistical Mathematics, 55(2):391-408, June 2003 (article)

Abstract
In kernel methods, all the information about the training data is contained in the Gram matrix. If this matrix has large diagonal values, which arises for many types of kernels, then kernel methods do not perform well: We propose and test several methods for dealing with this problem by reducing the dynamic range of the matrix while preserving the positive definiteness of the Hessian of the quadratic programming problem that one has to solve when training a Support Vector Machine, which is a common kernel approach for pattern recognition.

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Implicit Wiener Series

Franz, M., Schölkopf, B.

(114), Max Planck Institute for Biological Cybernetics, June 2003 (techreport)

Abstract
The Wiener series is one of the standard methods to systematically characterize the nonlinearity of a neural system. The classical estimation method of the expansion coefficients via cross-correlation suffers from severe problems that prevent its application to high-dimensional and strongly nonlinear systems. We propose a new estimation method based on regression in a reproducing kernel Hilbert space that overcomes these problems. Numerical experiments show performance advantages in terms of convergence, interpretability and system size that can be handled.

ei

PDF [BibTex]

PDF [BibTex]


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Machine Learning approaches to protein ranking: discriminative, semi-supervised, scalable algorithms

Weston, J., Leslie, C., Elisseeff, A., Noble, W.

(111), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, June 2003 (techreport)

Abstract
A key tool in protein function discovery is the ability to rank databases of proteins given a query amino acid sequence. The most successful method so far is a web-based tool called PSI-BLAST which uses heuristic alignment of a profile built using the large unlabeled database. It has been shown that such use of global information via an unlabeled data improves over a local measure derived from a basic pairwise alignment such as performed by PSI-BLAST's predecessor, BLAST. In this article we look at ways of leveraging techniques from the field of machine learning for the problem of ranking. We show how clustering and semi-supervised learning techniques, which aim to capture global structure in data, can significantly improve over PSI-BLAST.

ei

PDF [BibTex]

PDF [BibTex]


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The em Algorithm for Kernel Matrix Completion with Auxiliary Data

Tsuda, K., Akaho, S., Asai, K.

Journal of Machine Learning Research, 4, pages: 67-81, May 2003 (article)

ei

PDF [BibTex]

PDF [BibTex]


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Constructing Descriptive and Discriminative Non-linear Features: Rayleigh Coefficients in Kernel Feature Spaces

Mika, S., Rätsch, G., Weston, J., Schölkopf, B., Smola, A., Müller, K.

IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(5):623-628, May 2003 (article)

Abstract
We incorporate prior knowledge to construct nonlinear algorithms for invariant feature extraction and discrimination. Employing a unified framework in terms of a nonlinearized variant of the Rayleigh coefficient, we propose nonlinear generalizations of Fisher‘s discriminant and oriented PCA using support vector kernel functions. Extensive simulations show the utility of our approach.

ei

DOI [BibTex]

DOI [BibTex]


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The Geometry Of Kernel Canonical Correlation Analysis

Kuss, M., Graepel, T.

(108), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, May 2003 (techreport)

Abstract
Canonical correlation analysis (CCA) is a classical multivariate method concerned with describing linear dependencies between sets of variables. After a short exposition of the linear sample CCA problem and its analytical solution, the article proceeds with a detailed characterization of its geometry. Projection operators are used to illustrate the relations between canonical vectors and variates. The article then addresses the problem of CCA between spaces spanned by objects mapped into kernel feature spaces. An exact solution for this kernel canonical correlation (KCCA) problem is derived from a geometric point of view. It shows that the expansion coefficients of the canonical vectors in their respective feature space can be found by linear CCA in the basis induced by kernel principal component analysis. The effect of mappings into higher dimensional feature spaces is considered critically since it simplifies the CCA problem in general. Then two regularized variants of KCCA are discussed. Relations to other methods are illustrated, e.g., multicategory kernel Fisher discriminant analysis, kernel principal component regression and possible applications thereof in blind source separation.

ei

PDF [BibTex]

PDF [BibTex]


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The Kernel Mutual Information

Gretton, A., Herbrich, R., Smola, A.

Max Planck Institute for Biological Cybernetics, April 2003 (techreport)

Abstract
We introduce two new functions, the kernel covariance (KC) and the kernel mutual information (KMI), to measure the degree of independence of several continuous random variables. The former is guaranteed to be zero if and only if the random variables are pairwise independent; the latter shares this property, and is in addition an approximate upper bound on the mutual information, as measured near independence, and is based on a kernel density estimate. We show that Bach and Jordan‘s kernel generalised variance (KGV) is also an upper bound on the same kernel density estimate, but is looser. Finally, we suggest that the addition of a regularising term in the KGV causes it to approach the KMI, which motivates the introduction of this regularisation. The performance of the KC and KMI is verified in the context of instantaneous independent component analysis (ICA), by recovering both artificial and real (musical) signals following linear mixing.

ei

PostScript [BibTex]

PostScript [BibTex]


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Tractable Inference for Probabilistic Data Models

Csato, L., Opper, M., Winther, O.

Complexity, 8(4):64-68, April 2003 (article)

Abstract
We present an approximation technique for probabilistic data models with a large number of hidden variables, based on ideas from statistical physics. We give examples for two nontrivial applications. © 2003 Wiley Periodicals, Inc.

ei

PDF GZIP Web [BibTex]

PDF GZIP Web [BibTex]


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Feature selection and transduction for prediction of molecular bioactivity for drug design

Weston, J., Perez-Cruz, F., Bousquet, O., Chapelle, O., Elisseeff, A., Schölkopf, B.

Bioinformatics, 19(6):764-771, April 2003 (article)

Abstract
Motivation: In drug discovery a key task is to identify characteristics that separate active (binding) compounds from inactive (non-binding) ones. An automated prediction system can help reduce resources necessary to carry out this task. Results: Two methods for prediction of molecular bioactivity for drug design are introduced and shown to perform well in a data set previously studied as part of the KDD (Knowledge Discovery and Data Mining) Cup 2001. The data is characterized by very few positive examples, a very large number of features (describing three-dimensional properties of the molecules) and rather different distributions between training and test data. Two techniques are introduced specifically to tackle these problems: a feature selection method for unbalanced data and a classifier which adapts to the distribution of the the unlabeled test data (a so-called transductive method). We show both techniques improve identification performance and in conjunction provide an improvement over using only one of the techniques. Our results suggest the importance of taking into account the characteristics in this data which may also be relevant in other problems of a similar type.

ei

Web [BibTex]


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Use of the Zero-Norm with Linear Models and Kernel Methods

Weston, J., Elisseeff, A., Schölkopf, B., Tipping, M.

Journal of Machine Learning Research, 3, pages: 1439-1461, March 2003 (article)

Abstract
We explore the use of the so-called zero-norm of the parameters of linear models in learning. Minimization of such a quantity has many uses in a machine learning context: for variable or feature selection, minimizing training error and ensuring sparsity in solutions. We derive a simple but practical method for achieving these goals and discuss its relationship to existing techniques of minimizing the zero-norm. The method boils down to implementing a simple modification of vanilla SVM, namely via an iterative multiplicative rescaling of the training data. Applications we investigate which aid our discussion include variable and feature selection on biological microarray data, and multicategory classification.

ei

PDF PostScript PDF [BibTex]

PDF PostScript PDF [BibTex]


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An Introduction to Variable and Feature Selection.

Guyon, I., Elisseeff, A.

Journal of Machine Learning, 3, pages: 1157-1182, 2003 (article)

ei

[BibTex]

[BibTex]


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A Note on Parameter Tuning for On-Line Shifting Algorithms

Bousquet, O.

Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 2003 (techreport)

Abstract
In this short note, building on ideas of M. Herbster [2] we propose a method for automatically tuning the parameter of the FIXED-SHARE algorithm proposed by Herbster and Warmuth [3] in the context of on-line learning with shifting experts. We show that this can be done with a memory requirement of $O(nT)$ and that the additional loss incurred by the tuning is the same as the loss incurred for estimating the parameter of a Bernoulli random variable.

ei

PDF PostScript [BibTex]

PDF PostScript [BibTex]


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New Approaches to Statistical Learning Theory

Bousquet, O.

Annals of the Institute of Statistical Mathematics, 55(2):371-389, 2003 (article)

Abstract
We present new tools from probability theory that can be applied to the analysis of learning algorithms. These tools allow to derive new bounds on the generalization performance of learning algorithms and to propose alternative measures of the complexity of the learning task, which in turn can be used to derive new learning algorithms.

ei

PostScript [BibTex]

PostScript [BibTex]


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Interactive Images

Toyama, K., Schölkopf, B.

(MSR-TR-2003-64), Microsoft Research, Cambridge, UK, 2003 (techreport)

Abstract
Interactive Images are a natural extension of three recent developments: digital photography, interactive web pages, and browsable video. An interactive image is a multi-dimensional image, displayed two dimensions at a time (like a standard digital image), but with which a user can interact to browse through the other dimensions. One might consider a standard video sequence viewed with a video player as a simple interactive image with time as the third dimension. Interactive images are a generalization of this idea, in which the third (and greater) dimensions may be focus, exposure, white balance, saturation, and other parameters. Interaction is handled via a variety of modes including those we call ordinal, pixel-indexed, cumulative, and comprehensive. Through exploration of three novel forms of interactive images based on color, exposure, and focus, we will demonstrate the compelling nature of interactive images.

ei

Web [BibTex]

Web [BibTex]


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New electro-optic effect: Sum-frequency generation from optically active liquids in the presence of a dc electric field

Fischer, P., Buckingham, A., Beckwitt, K., Wiersma, D., Wise, F.

PHYSICAL REVIEW LETTERS, 91(17), 2003 (article)

Abstract
We report the observation of sum-frequency signals that depend linearly on an applied electrostatic field and that change sign with the handedness of an optically active solute. This recently predicted chiral electro-optic effect exists in the electric-dipole approximation. The static electric field gives rise to an electric-field-induced sum-frequency signal (an achiral third-order process) that interferes with the chirality-specific sum-frequency at second order. The cross-terms linear in the electrostatic field constitute the effect and may be used to determine the absolute sign of second- and third-order nonlinear-optical susceptibilities in isotropic media.

pf

DOI [BibTex]

DOI [BibTex]


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Chiral and achiral contributions to sum-frequency generation from optically active solutions of binaphthol

Fischer, P., Wise, F., Albrecht, A.

JOURNAL OF PHYSICAL CHEMISTRY A, 107(40):8232-8238, 2003 (article)

Abstract
The nonlinear sum- and difference-frequency generation spectroscopies can be probes of molecular chirality in optically active systems. We present a tensorial analysis of the chirality-specific electric-dipolar sum-frequency-generation susceptibility and the achiral electric-quadrupolar and magnetic-dipolar nonlinearities at second order in isotropic media. The chiral and achiral contributions to the sum-frequency signal from the bulk of optically active solutions of 1,1'-bi-2-naphthol (2,2'-dehydroxy-1,1'-binaphthyl) can be distinguished, and the former dominates. Ab initio computations reveal the dramatic resonance enhancement that the isotropic component of the electric-dipolar three-wave mixing hyperpolarizability experiences. Away from resonance its magnitude rapidly decreases, as-unlike the vector component-it is zero in the static limit. The dispersion of the first hyperpolarizability is computed by a configuration interaction singles sum-over-states approach with explicit regard to the Franck-Condon active vibrational substructure for all resonant electronic states.

pf

DOI [BibTex]

DOI [BibTex]


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Synthetic gecko foot-hair micro/nano-structures as dry adhesives

Sitti, M., Fearing, R. S.

Journal of adhesion science and technology, 17(8):1055-1073, Taylor & Francis Group, 2003 (article)

pi

Project Page [BibTex]

Project Page [BibTex]


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Teleoperated touch feedback from the surfaces at the nanoscale: modeling and experiments

Sitti, M., Hashimoto, H.

IEEE/ASME transactions on mechatronics, 8(2):287-298, IEEE, 2003 (article)

pi

[BibTex]

[BibTex]


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Mixing in Cu/Ge system by swift heavy ions

Kumar, S., Chauhan, R. S., Singh, R. P., Kabiraj, D., Sahoo, P. K., Rumbolz, C., Srivastava, S. K., Bolse, W., Avasthi, D. K.

{Nuclear Instruments \& Methods in Physics Research Section B-Beam Interactions with Materials and Atoms}, 212, pages: 242-245, 2003 (article)

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[BibTex]

[BibTex]


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Magnetic properties of [NdFeBx/Nbz]n multilayer films

Tsai, J. L., Chin, T. S., Yao, Y. D., Melsheimer, A., Fischer, S. F., Dragon, T., Kelsch, M., Kronmüller, H.

{Journal of Applied Physics}, 93(10):6915-6917, 2003 (article)

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[BibTex]

[BibTex]


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Analysis of the temperature dependence of the coercive field of Sm2Co17 based magnets

Kronmüller, H., Goll, D.

{Scripta Materialia}, 48(7):833-838, 2003 (article)

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[BibTex]

[BibTex]


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NMR studies of hydrogen motion in nanostructured hydrogen-graphite systems

Majer, G., Stanik, E., Orimo, S.

{Journal of Alloys and Compounds}, 356-357, pages: 617-621, 2003 (article)

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[BibTex]

[BibTex]


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Hydrogen diffusion in metallic and nanostructured materials

Majer, G., Eberle, U., Kimmerle, F., Stanik, E., Orimo, S.

{Physica B}, 328, pages: 81-89, 2003 (article)

mms

[BibTex]

[BibTex]


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Electron density-of-states and the metal-insulator transition in LaHx

Barnes, R. G., Chang, C. T., Majer, G., Kaess, U.

{Journal of Alloys and Compounds}, 356-357, pages: 137-141, 2003 (article)

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[BibTex]

[BibTex]


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Electronic sputtering from HOPG: A study of angular dependence

Tripathi, A., Khan, S. A., Srivastava, S. K., Kumar, M., Kumar, S., Rao, S. V. S. N., Lakshmi, G. B. V. S., Siddiqui, A. M., Bajwa, N., Nagaraja, H. S., Mittal, V. K., Szökefalvi, A., Kurth, M., Pandey, A. C., Avasthi, D. K., Carstanjen, H. D.

{Nuclear Instruments and Methods B}, 212, pages: 402-406, 2003 (article)

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[BibTex]

[BibTex]


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Stress-induced relaxation mechanisms in single-crystalline titanomagnetites

Walz, F., Brabers, V. A. M., Brabers, J. H. V. J., Kronmüller, H.

{Journal of Physics-Condensed Matter}, 15(41):7029-7045, 2003 (article)

mms

[BibTex]

[BibTex]


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Morphology and interdiffusion behavior of evaporated metal films on crystalline diindenoperylene thin films

Dürr, A. C., Schreiber, F., Kelsch, M., Carstanjen, H. D., Dosch, H., Seeck, O. H.

{Journal of Applied Physics}, 93(9):5201-5209, 2003 (article)

mms

[BibTex]

[BibTex]


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Recent progress with high resolution X-ray microscopy at the XM-1

Denbeaux, G., Schneider, G., Pearson, A., Chao, W., Bates, B., Harteneck, B., Olynick, D., Anderson, E., Fischer, P., Juenger, M.

{Journal de Physique IV}, 104, pages: 9-9, 2003 (article)

mms

[BibTex]

[BibTex]


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Comment on the analysis of angle-dependent X-ray magnetic circular dichroism in systems with reduced dimensionality

Ederer, C., Komelj, M., Davenport, J. W., Fähnle, M.

{Journal of Electron Spectroscopy and Related Phenomena}, 130(1-3):97-100, 2003 (article)

mms

[BibTex]

[BibTex]


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The electron theory of magnetism in monoatomic nanowires

Komelj, M., Ederer, C., Fähnle, M.

{Advances in Solid State Science}, 43, pages: 781-788, 2003 (article)

mms

[BibTex]

[BibTex]


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Nuclear relaxation in the dideuteride of hafnium and titanium

Majer, G., Gottwald, J., Peterson, D. T., Barnes, R. G.

{Physical Review B}, 68, 2003 (article)

mms

[BibTex]

[BibTex]


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Magnetism in systems with various dimensionalities: A comparison between Fe and Co

Ederer, C., Komelj, M., Fähnle, M.

{Physical Review B}, 68, 2003 (article)

mms

[BibTex]

[BibTex]


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Scaled teleoperation system for nano-scale interaction and manipulation

Sitti, M., Aruk, B., Shintani, H., Hashimoto, H.

Advanced Robotics, 17(3):275-291, Taylor & Francis Group, 2003 (article)

pi

[BibTex]

[BibTex]


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Atomic force microscope probe based controlled pushing for nano-tribological characterization

Sitti, M.

IEEE/ASME Transactions on Mechatronics, 8(3), 2003 (article)

pi

[BibTex]


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Characterization of free volumes in amorphous and nanostructured Pr2Fe14B using positron lifetime spectroscopy

Wu, Y. C., Ye, F., Barbe, V., Sprengel, W., Reimann, K., Reichle, K. J., Goll, D., Würschum, R., Schaefer, H. E.

{Physica Status Solidi A-Applied Research}, 198(1):204-209, 2003 (article)

mms

[BibTex]

[BibTex]


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The magnetization behavior of nanocrystalline permanent magnets based on the Stoner-Wohlfarth model

Zhang, H. W., Zhang, S. Y., Shen, B. G., Kronmüller, H.

{Journal of Magnetism and Magnetic Materials}, 260(3):352-360, 2003 (article)

mms

[BibTex]

[BibTex]


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X-ray magnetic microscopy for correlations between magnetic domains and crystal structure

Denbeaux, G., Anderson, E., Bates, B., Chao, W., Liddle, J. A., Harteneck, B., Pearson, A., Salmassi, F., Schneider, G., Fischer, P., Eimüller, T., Taylor, S., Chang, H., Kusinski, G. J.

{Journal de Physique IV}, 104, pages: 477-481, 2003 (article)

mms

[BibTex]

[BibTex]


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Statistical mechanics of inhomogeneous model colloid-polymer mixtures

Brader, J. M., Evans, R., Schmidt, M.

{Molecular Physics}, 101, pages: 3349-3384, 2003 (article)

mms

[BibTex]

[BibTex]


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Cluster expansion technique: An efficient tool to search for ground-state configurations of adatoms on plane surfaces

Drautz, R., Singer, R., Fähnle, M.

{Physical Review B}, 67, 2003 (article)

mms

[BibTex]


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Hydrogen strorage in carbon nanotubes

Becher, M., Haluska, M., Hirscher, M., Quintel, A., Skakalova, V., Dettlaff-Weglikovska, U., Chen, X., Hulman, M., Choi, Y., Roth, S., Meregalli, V., Parrinello, M., Ströbel, R., Jörissen, L., Kappes, M., Fink, J., Züttel, A., Stepanek, I., Bernier, P.

{Comptes Rendus Physique}, 4, pages: 1055-1062, 2003 (article)

mms

[BibTex]

[BibTex]