Publications | Max Planck Institute for Intelligent Systems

161 results (View BibTeX file of all listed publications)

2004

On the representation, learning and transfer of spatio-temporal movement characteristics

Ilg, W., Bakir, GH., Mezger, J., Giese, M.

International Journal of Humanoid Robotics, 1(4):613-636, December 2004 (article)

2004

ei Ilg, W., Bakir, GH., Mezger, J., Giese, M. On the representation, learning and transfer of spatio-temporal movement characteristics International Journal of Humanoid Robotics, 1(4):613-636, December 2004 (article)

[BibTex]

Insect-inspired estimation of egomotion

Franz, MO., Chahl, JS., Krapp, HG.

Neural Computation, 16(11):2245-2260, November 2004 (article)

Abstract

Tangential neurons in the fly brain are sensitive to the typical optic flow patterns generated during egomotion. In this study, we examine whether a simplified linear model based on the organization principles in tangential neurons can be used to estimate egomotion from the optic flow. We present a theory for the construction of an estimator consisting of a linear combination of optic flow vectors that incorporates prior knowledge both about the distance distribution of the environment, and about the noise and egomotion statistics of the sensor. The estimator is tested on a gantry carrying an omnidirectional vision sensor. The experiments show that the proposed approach leads to accurate and robust estimates of rotation rates, whereas translation estimates are of reasonable quality, albeit less reliable.

PDF PostScript Web DOI [BibTex]

ei Franz, MO., Chahl, JS., Krapp, HG. Insect-inspired estimation of egomotion Neural Computation, 16(11):2245-2260, November 2004 (article)

PDF PostScript Web DOI [BibTex]

Efficient face detection by a cascaded support-vector machine expansion

Romdhani, S., Torr, P., Schölkopf, B., Blake, A.

Proceedings of The Royal Society of London A, 460(2501):3283-3297, A, November 2004 (article)

Abstract

We describe a fast system for the detection and localization of human faces in images using a nonlinear ‘support-vector machine‘. We approximate the decision surface in terms of a reduced set of expansion vectors and propose a cascaded evaluation which has the property that the full support-vector expansion is only evaluated on the face-like parts of the image, while the largest part of typical images is classified using a single expansion vector (a simpler and more efficient classifier). As a result, only three reduced-set vectors are used, on average, to classify an image patch. Hence, the cascaded evaluation, presented in this paper, offers a thirtyfold speed-up over an evaluation using the full set of reduced-set vectors, which is itself already thirty times faster than classification using all the support vectors.

PDF DOI [BibTex]

ei Romdhani, S., Torr, P., Schölkopf, B., Blake, A. Efficient face detection by a cascaded support-vector machine expansion Proceedings of The Royal Society of London A, 460(2501):3283-3297, A, November 2004 (article)

PDF DOI [BibTex]

Joint Kernel Maps

Weston, J., Schölkopf, B., Bousquet, O., Mann, .., Noble, W.

(131), Max-Planck-Institute for Biological Cybernetics, Tübingen, November 2004 (techreport)

PDF [BibTex]

ei Weston, J., Schölkopf, B., Bousquet, O., Mann, .., Noble, W. Joint Kernel Maps (131), Max-Planck-Institute for Biological Cybernetics, Tübingen, November 2004 (techreport)

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Semi-Supervised Induction

Yu, K., Tresp, V., Zhou, D.

(141), Max Planck Institute for Biological Cybernetics, Tuebingen, Germany, August 2004 (techreport)

Abstract

Considerable progress was recently achieved on semi-supervised learning, which differs from the traditional supervised learning by additionally exploring the information of the unlabelled examples. However, a disadvantage of many existing methods is that it does not generalize to unseen inputs. This paper investigates learning methods that effectively make use of both labelled and unlabelled data to build predictive functions, which are defined on not just the seen inputs but the whole space. As a nice property, the proposed method allows effcient training and can easily handle new test points. We validate the method based on both toy data and real world data sets.

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ei Yu, K., Tresp, V., Zhou, D. Semi-Supervised Induction (141), Max Planck Institute for Biological Cybernetics, Tuebingen, Germany, August 2004 (techreport)

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Learning kernels from biological networks by maximizing entropy

Tsuda, K., Noble, W.

Bioinformatics, 20(Suppl. 1):i326-i333, August 2004 (article)

Abstract

Motivation: The diffusion kernel is a general method for computing pairwise distances among all nodes in a graph, based on the sum of weighted paths between each pair of nodes. This technique has been used successfully, in conjunction with kernel-based learning methods, to draw inferences from several types of biological networks. Results: We show that computing the diffusion kernel is equivalent to maximizing the von Neumann entropy, subject to a global constraint on the sum of the Euclidean distances between nodes. This global constraint allows for high variance in the pairwise distances. Accordingly, we propose an alternative, locally constrained diffusion kernel, and we demonstrate that the resulting kernel allows for more accurate support vector machine prediction of protein functional classifications from metabolic and proteinprotein interaction networks.

PDF Web [BibTex]

ei Tsuda, K., Noble, W. Learning kernels from biological networks by maximizing entropy Bioinformatics, 20(Suppl. 1):i326-i333, August 2004 (article)

PDF Web [BibTex]

Masking effect produced by Mach bands on the detection of narrow bars of random polarity

Henning, GB., Hoddinott, KT., Wilson-Smith, ZJ., Hill, NJ.

Journal of the Optical Society of America, 21(8):1379-1387, A, August 2004 (article)

[BibTex]

ei Henning, GB., Hoddinott, KT., Wilson-Smith, ZJ., Hill, NJ. Masking effect produced by Mach bands on the detection of narrow bars of random polarity Journal of the Optical Society of America, 21(8):1379-1387, A, August 2004 (article)

[BibTex]

Object categorization with SVM: kernels for local features

Eichhorn, J., Chapelle, O.

(137), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, July 2004 (techreport)

Abstract

In this paper, we propose to combine an efficient image representation based on local descriptors with a Support Vector Machine classifier in order to perform object categorization. For this purpose, we apply kernels defined on sets of vectors. After testing different combinations of kernel / local descriptors, we have been able to identify a very performant one.

PDF [BibTex]

ei Eichhorn, J., Chapelle, O. Object categorization with SVM: kernels for local features (137), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, July 2004 (techreport)

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Hilbertian Metrics and Positive Definite Kernels on Probability Measures

Hein, M., Bousquet, O.

(126), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, July 2004 (techreport)

Abstract

We investigate the problem of defining Hilbertian metrics resp. positive definite kernels on probability measures, continuing previous work. This type of kernels has shown very good results in text classification and has a wide range of possible applications. In this paper we extend the two-parameter family of Hilbertian metrics of Topsoe such that it now includes all commonly used Hilbertian metrics on probability measures. This allows us to do model selection among these metrics in an elegant and unified way. Second we investigate further our approach to incorporate similarity information of the probability space into the kernel. The analysis provides a better understanding of these kernels and gives in some cases a more efficient way to compute them. Finally we compare all proposed kernels in two text and one image classification problem.

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ei Hein, M., Bousquet, O. Hilbertian Metrics and Positive Definite Kernels on Probability Measures (126), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, July 2004 (techreport)

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Kernels, Associated Structures and Generalizations

Hein, M., Bousquet, O.

(127), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, July 2004 (techreport)

Abstract

This paper gives a survey of results in the mathematical literature on positive definite kernels and their associated structures. We concentrate on properties which seem potentially relevant for Machine Learning and try to clarify some results that have been misused in the literature. Moreover we consider different lines of generalizations of positive definite kernels. Namely we deal with operator-valued kernels and present the general framework of Hilbertian subspaces of Schwartz which we use to introduce kernels which are distributions. Finally indefinite kernels and their associated reproducing kernel spaces are considered.

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ei Hein, M., Bousquet, O. Kernels, Associated Structures and Generalizations (127), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, July 2004 (techreport)

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Support Vector Channel Selection in BCI

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

IEEE Transactions on Biomedical Engineering, 51(6):1003-1010, June 2004 (article)

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 and Zero-Norm Optimization which are based on the training of Support Vector Machines (SVM). These algorithms can provide more accurate solutions than standard filter methods for feature selection. 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.

DOI [BibTex]

ei Lal, T., Schröder, M., Hinterberger, T., Weston, J., Bogdan, M., Birbaumer, N., Schölkopf, B. Support Vector Channel Selection in BCI IEEE Transactions on Biomedical Engineering, 51(6):1003-1010, June 2004 (article)

DOI [BibTex]

Distance-Based Classification with Lipschitz Functions

von Luxburg, U., Bousquet, O.

Journal of Machine Learning Research, 5, pages: 669-695, June 2004 (article)

Abstract

The goal of this article is to develop a framework for large margin classification in metric spaces. We want to find a generalization of linear decision functions for metric spaces and define a corresponding notion of margin such that the decision function separates the training points with a large margin. It will turn out that using Lipschitz functions as decision functions, the inverse of the Lipschitz constant can be interpreted as the size of a margin. In order to construct a clean mathematical setup we isometrically embed the given metric space into a Banach space and the space of Lipschitz functions into its dual space. To analyze the resulting algorithm, we prove several representer theorems. They state that there always exist solutions of the Lipschitz classifier which can be expressed in terms of distance functions to training points. We provide generalization bounds for Lipschitz classifiers in terms of the Rademacher complexities of some Lipschitz function classes. The generality of our approach can be seen from the fact that several well-known algorithms are special cases of the Lipschitz classifier, among them the support vector machine, the linear programming machine, and the 1-nearest neighbor classifier.

PDF PostScript PDF [BibTex]

ei von Luxburg, U., Bousquet, O. Distance-Based Classification with Lipschitz Functions Journal of Machine Learning Research, 5, pages: 669-695, June 2004 (article)

PDF PostScript PDF [BibTex]

cDNA-Microarray Technology in Cartilage Research - Functional Genomics of Osteoarthritis [in German]

Aigner, T., Finger, F., Zien, A., Bartnik, E.

Zeitschrift f{\"u}r Orthop{\"a}die und ihre Grenzgebiete, 142(2):241-247, April 2004 (article)

Abstract

Functional genomics represents a new challenging approach in order to analyze complex diseases such as osteoarthritis on a molecular level. The characterization of the molecular changes of the cartilage cells, the chondrocytes, enables a better understanding of the pathomechanisms of the disease. In particular, the identification and characterization of new target molecules for therapeutic intervention is of interest. Also, potential molecular markers for diagnosis and monitoring of osteoarthritis contribute to a more appropriate patient management. The DNA-microarray technology complements (but does not replace) biochemical and biological research in new disease-relevant genes. Large-scale functional genomics will identify molecular networks such as yet identified players in the anabolic-catabolic balance of articular cartilage as well as disease-relevant intracellular signaling cascades so far rather unknown in articular chondrocytes. However, at the moment it is also important to recognize the limitations of the microarray technology in order to avoid over-interpretation of the results. This might lead to misleading results and prevent to a significant extent a proper use of the potential of this technology in the field of osteoarthritis.

[BibTex]

ei Aigner, T., Finger, F., Zien, A., Bartnik, E. cDNA-Microarray Technology in Cartilage Research - Functional Genomics of Osteoarthritis [in German] Zeitschrift f{\"u}r Orthop{\"a}die und ihre Grenzgebiete, 142(2):241-247, April 2004 (article)

[BibTex]

A Compression Approach to Support Vector Model Selection

von Luxburg, U., Bousquet, O., Schölkopf, B.

Journal of Machine Learning Research, 5, pages: 293-323, April 2004 (article)

Abstract

In this paper we investigate connections between statistical learning theory and data compression on the basis of support vector machine (SVM) model selection. Inspired by several generalization bounds we construct "compression coefficients" for SVMs which measure the amount by which the training labels can be compressed by a code built from the separating hyperplane. The main idea is to relate the coding precision to geometrical concepts such as the width of the margin or the shape of the data in the feature space. The so derived compression coefficients combine well known quantities such as the radius-margin term R^2/rho^2, the eigenvalues of the kernel matrix, and the number of support vectors. To test whether they are useful in practice we ran model selection experiments on benchmark data sets. As a result we found that compression coefficients can fairly accurately predict the parameters for which the test error is minimized.

PDF [BibTex]

ei von Luxburg, U., Bousquet, O., Schölkopf, B. A Compression Approach to Support Vector Model Selection Journal of Machine Learning Research, 5, pages: 293-323, April 2004 (article)

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Kamerakalibrierung und Tiefenschätzung: Ein Vergleich von klassischer Bündelblockausgleichung und statistischen Lernalgorithmen

Sinz, FH.

Wilhelm-Schickard-Institut für Informatik, Universität Tübingen, Tübingen, Germany, March 2004 (techreport)

Abstract

Die Arbeit verleicht zwei Herangehensweisen an das Problem der Sch{\"a}tzung der r{\"a}umliche Position eines Punktes aus den Bildkoordinaten in zwei verschiedenen Kameras. Die klassische Methode der B{\"u}ndelblockausgleichung modelliert zwei Einzelkameras und sch{\"a}tzt deren {\"a}ußere und innere Orientierung mit einer iterativen Kalibrationsmethode, deren Konvergenz sehr stark von guten Startwerten abh{\"a}ngt. Die Tiefensch{\"a}tzung eines Punkts geschieht durch die Invertierung von drei der insgesamt vier Projektionsgleichungen der Einzalkameramodelle. Die zweite Methode benutzt Kernel Ridge Regression und Support Vector Regression, um direkt eine Abbildung von den Bild- auf die Raumkoordinaten zu lernen. Die Resultate zeigen, daß der Ansatz mit maschinellem Lernen, neben einer erheblichen Vereinfachung des Kalibrationsprozesses, zu h{\"o}heren Positionsgenaugikeiten f{\"u}hren kann.

PDF [BibTex]

ei Sinz, FH. Kamerakalibrierung und Tiefenschätzung: Ein Vergleich von klassischer Bündelblockausgleichung und statistischen Lernalgorithmen Wilhelm-Schickard-Institut für Informatik, Universität Tübingen, Tübingen, Germany, March 2004 (techreport)

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Experimentally optimal v in support vector regression for different noise models and parameter settings

Chalimourda, A., Schölkopf, B., Smola, A.

Neural Networks, 17(1):127-141, January 2004 (article)

Abstract

In Support Vector (SV) regression, a parameter ν controls the number of Support Vectors and the number of points that come to lie outside of the so-called var epsilon-insensitive tube. For various noise models and SV parameter settings, we experimentally determine the values of ν that lead to the lowest generalization error. We find good agreement with the values that had previously been predicted by a theoretical argument based on the asymptotic efficiency of a simplified model of SV regression. As a side effect of the experiments, valuable information about the generalization behavior of the remaining SVM parameters and their dependencies is gained. The experimental findings are valid even for complex real-world data sets. Based on our results on the role of the ν-SVM parameters, we discuss various model selection methods.

PDF DOI [BibTex]

ei Chalimourda, A., Schölkopf, B., Smola, A. Experimentally optimal v in support vector regression for different noise models and parameter settings Neural Networks, 17(1):127-141, January 2004 (article)

PDF DOI [BibTex]

Protein ranking: from local to global structure in the protein similarity network

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

Proceedings of the National Academy of Science, 101(17):6559-6563, 2004 (article)

Abstract

Biologists regularly search databases of DNA or protein sequences for evolutionary or functional relationships to a given query sequence. We describe a ranking algorithm that exploits the entire network structure of similarity relationships among proteins in a sequence database by performing a diffusion operation on a pre-computed, weighted network. The resulting ranking algorithm, evaluated using a human-curated database of protein structures, is efficient and provides significantly better rankings than a local network search algorithm such as PSI-BLAST.

Web [BibTex]

ei Weston, J., Elisseeff, A., Zhou, D., Leslie, C., Noble, W. Protein ranking: from local to global structure in the protein similarity network Proceedings of the National Academy of Science, 101(17):6559-6563, 2004 (article)

Web [BibTex]

Multivariate Regression with Stiefel Constraints

Bakir, G., Gretton, A., Franz, M., Schölkopf, B.

(128), MPI for Biological Cybernetics, Spemannstr 38, 72076, Tuebingen, 2004 (techreport)

Abstract

We introduce a new framework for regression between multi-dimensional spaces. Standard methods for solving this problem typically reduce the problem to one-dimensional regression by choosing features in the input and/or output spaces. These methods, which include PLS (partial least squares), KDE (kernel dependency estimation), and PCR (principal component regression), select features based on different a-priori judgments as to their relevance. Moreover, loss function and constraints are chosen not primarily on statistical grounds, but to simplify the resulting optimisation. By contrast, in our approach the feature construction and the regression estimation are performed jointly, directly minimizing a loss function that we specify, subject to a rank constraint. A major advantage of this approach is that the loss is no longer chosen according to the algorithmic requirements, but can be tailored to the characteristics of the task at hand; the features will then be optimal with respect to this objective. Our approach also allows for the possibility of using a regularizer in the optimization. Finally, by processing the observations sequentially, our algorithm is able to work on large scale problems.

PDF [BibTex]

ei Bakir, G., Gretton, A., Franz, M., Schölkopf, B. Multivariate Regression with Stiefel Constraints (128), MPI for Biological Cybernetics, Spemannstr 38, 72076, Tuebingen, 2004 (techreport)

PDF [BibTex]

Statistical Performance of Support Vector Machines

Blanchard, G., Bousquet, O., Massart, P.

2004 (article)

PostScript [BibTex]

ei Blanchard, G., Bousquet, O., Massart, P. Statistical Performance of Support Vector Machines 2004 (article)

PostScript [BibTex]

Asymptotic Properties of the Fisher Kernel

Tsuda, K., Akaho, S., Kawanabe, M., Müller, K.

Neural Computation, 16(1):115-137, 2004 (article)

PDF [BibTex]

ei Tsuda, K., Akaho, S., Kawanabe, M., Müller, K. Asymptotic Properties of the Fisher Kernel Neural Computation, 16(1):115-137, 2004 (article)

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Some observations on the effects of slant and texture type on slant-from-texture

Rosas, P., Wichmann, F., Wagemans, J.

Vision Research, 44(13):1511-1535, 2004 (article)

Abstract

We measure the performance of five subjects in a slant-discrimination task for differently textured planes. As textures we used uniform lattices, randomly displaced lattices, circles (polka dots), Voronoi tessellations, plaids, 1/f noise, coherent noise and a leopard skin-like texture. Our results show: (1) Improving performance with larger slants for all textures. (2) Thus, following from (1), cases of non-symmetrical performance around a particular orientation. (3) For orientations sufficiently slanted, the different textures do not elicit major differences in performance, (4) while for orientations closer to the vertical plane there are marked differences between them. (5) These differences allow a rank-order of textures to be formed according to their helpfulness that is, how easy the discrimination task is when a particular texture is mapped on the plane. Polka dots tend to allow the best slant discrimination performance, noise patterns the worst. Two additional experiments were conducted to test the generality of the obtained rank-order. First, the tilt of the planes was rotated to break the axis of gravity present in the original discrimination experiment. Second, the task was changed to a slant report task via probe adjustment. The results of both control experiments confirmed the texture-based rank-order previously obtained. We comment on the importance of these results for depth perception research in general, and in particular the implications our results have for studies of cue combination (sensor fusion) using texture as one of the cues involved.

PDF [BibTex]

ei Rosas, P., Wichmann, F., Wagemans, J. Some observations on the effects of slant and texture type on slant-from-texture Vision Research, 44(13):1511-1535, 2004 (article)

PDF [BibTex]

Learning from Labeled and Unlabeled Data Using Random Walks

Zhou, D., Schölkopf, B.

Max Planck Institute for Biological Cybernetics, 2004 (techreport)

Abstract

We consider the general problem of learning from labeled and unlabeled data. Given a set of points, some of them are labeled, and the remaining points are unlabeled. The goal is to predict the labels of the unlabeled points. Any supervised learning algorithm can be applied to this problem, for instance, Support Vector Machines (SVMs). The problem of our interest is if we can implement a classifier which uses the unlabeled data information in some way and has higher accuracy than the classifiers which use the labeled data only. Recently we proposed a simple algorithm, which can substantially benefit from large amounts of unlabeled data and demonstrates clear superiority to supervised learning methods. In this paper we further investigate the algorithm using random walks and spectral graph theory, which shed light on the key steps in this algorithm.

PDF PostScript [BibTex]

ei Zhou, D., Schölkopf, B. Learning from Labeled and Unlabeled Data Using Random Walks Max Planck Institute for Biological Cybernetics, 2004 (techreport)

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Minimizing the Cross Validation Error to Mix Kernel Matrices of Heterogeneous Biological Data

Tsuda, K., Uda, S., Kin, T., Asai, K.

Neural Processing Letters, 19, pages: 63-72, 2004 (article)

PDF [BibTex]

ei Tsuda, K., Uda, S., Kin, T., Asai, K. Minimizing the Cross Validation Error to Mix Kernel Matrices of Heterogeneous Biological Data Neural Processing Letters, 19, pages: 63-72, 2004 (article)

PDF [BibTex]

A Tutorial on Support Vector Regression

Smola, A., Schölkopf, B.

Statistics and Computing, 14(3):199-222, 2004 (article)

Web [BibTex]

ei Smola, A., Schölkopf, B. A Tutorial on Support Vector Regression Statistics and Computing, 14(3):199-222, 2004 (article)

Web [BibTex]

Behaviour and Convergence of the Constrained Covariance

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

(130), MPI for Biological Cybernetics, 2004 (techreport)

Abstract

We discuss reproducing kernel Hilbert space (RKHS)-based measures of statistical dependence, with emphasis on constrained covariance (COCO), a novel criterion to test dependence of random variables. We show that COCO is a test for independence if and only if the associated RKHSs are universal. That said, no independence test exists that can distinguish dependent and independent random variables in all circumstances. Dependent random variables can result in a COCO which is arbitrarily close to zero when the source densities are highly non-smooth, which can make dependence hard to detect empirically. All current kernel-based independence tests share this behaviour. Finally, we demonstrate exponential convergence between the population and empirical COCO, which implies that COCO does not suffer from slow learning rates when used as a dependence test.

PDF [BibTex]

ei Gretton, A., Smola, A., Bousquet, O., Herbrich, R., Schölkopf, B., Logothetis, N. Behaviour and Convergence of the Constrained Covariance (130), MPI for Biological Cybernetics, 2004 (techreport)

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Bayesian analysis of the Scatterometer Wind Retrieval Inverse Problem: Some New Approaches

Cornford, D., Csato, L., Evans, D., Opper, M.

Journal of the Royal Statistical Society B, 66, pages: 1-17, 3, 2004 (article)

Abstract

The retrieval of wind vectors from satellite scatterometer observations is a non-linear inverse problem.A common approach to solving inverse problems is to adopt a Bayesian framework and to infer the posterior distribution of the parameters of interest given the observations by using a likelihood model relating the observations to the parameters, and a prior distribution over the parameters.We show how Gaussian process priors can be used efficiently with a variety of likelihood models, using local forward (observation) models and direct inverse models for the scatterometer.We present an enhanced Markov chain Monte Carlo method to sample from the resulting multimodal posterior distribution.We go on to show how the computational complexity of the inference can be controlled by using a sparse, sequential Bayes algorithm for estimation with Gaussian processes.This helps to overcome the most serious barrier to the use of probabilistic, Gaussian process methods in remote sensing inverse problems, which is the prohibitively large size of the data sets.We contrast the sampling results with the approximations that are found by using the sparse, sequential Bayes algorithm.

PDF [BibTex]

ei Cornford, D., Csato, L., Evans, D., Opper, M. Bayesian analysis of the Scatterometer Wind Retrieval Inverse Problem: Some New Approaches Journal of the Royal Statistical Society B, 66, pages: 1-17, 3, 2004 (article)

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Feature Selection for Support Vector Machines Using Genetic Algorithms

Fröhlich, H., Chapelle, O., Schölkopf, B.

International Journal on Artificial Intelligence Tools (Special Issue on Selected Papers from the 15th IEEE International Conference on Tools with Artificial Intelligence 2003), 13(4):791-800, 2004 (article)

Web [BibTex]

ei Fröhlich, H., Chapelle, O., Schölkopf, B. Feature Selection for Support Vector Machines Using Genetic Algorithms International Journal on Artificial Intelligence Tools (Special Issue on Selected Papers from the 15th IEEE International Conference on Tools with Artificial Intelligence 2003), 13(4):791-800, 2004 (article)

Web [BibTex]

Confidence Sets for Ratios: A Purely Geometric Approach To Fieller’s Theorem

von Luxburg, U., Franz, V.

(133), Max Planck Institute for Biological Cybernetics, 2004 (techreport)

Abstract

We present a simple, geometric method to construct Fieller's exact confidence sets for ratios of jointly normally distributed random variables. Contrary to previous geometric approaches in the literature, our method is valid in the general case where both sample mean and covariance are unknown. Moreover, not only the construction but also its proof are purely geometric and elementary, thus giving intuition into the nature of the confidence sets.

PDF [BibTex]

ei von Luxburg, U., Franz, V. Confidence Sets for Ratios: A Purely Geometric Approach To Fieller’s Theorem (133), Max Planck Institute for Biological Cybernetics, 2004 (techreport)

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Transductive Inference with Graphs

Zhou, D., Schölkopf, B.

Max Planck Institute for Biological Cybernetics, 2004, See the improved version Regularization on Discrete Spaces. (techreport)

Abstract

We propose a general regularization framework for transductive inference. The given data are thought of as a graph, where the edges encode the pairwise relationships among data. We develop discrete analysis and geometry on graphs, and then naturally adapt the classical regularization in the continuous case to the graph situation. A new and effective algorithm is derived from this general framework, as well as an approach we developed before.

[BibTex]

ei Zhou, D., Schölkopf, B. Transductive Inference with Graphs Max Planck Institute for Biological Cybernetics, 2004, See the improved version Regularization on Discrete Spaces. (techreport)

[BibTex]

Phenotypic Characterization of Human Chondrocyte Cell Line C-20/A4: A Comparison between Monolayer and Alginate Suspension Culture

Finger, F., Schorle, C., Söder, S., Zien, A., Goldring, M., Aigner, T.

Cells Tissues Organs, 178(2):65-77, 2004 (article)

Abstract

DNA microarray analysis was used to investigate the molecular phenotype of one of the first human chondrocyte cell lines, C-20/A4, derived from juvenile costal chondrocytes by immortalization with origin-defective simian virus 40 large T antigen. Clontech Human Cancer Arrays 1.2 and quantitative PCR were used to examine gene expression profiles of C-20/A4 cells cultured in the presence of serum in monolayer and alginate beads. In monolayer cultures, genes involved in cell proliferation were strongly upregulated compared to those expressed by human adult articular chondrocytes in primary culture. Of the cell cycle-regulated genes, only two, the CDK regulatory subunit and histone H4, were downregulated after culture in alginate beads, consistent with the ability of these cells to proliferate in suspension culture. In contrast, the expression of several genes that are involved in pericellular matrix formation, including MMP-14, COL6A1, fibronectin, biglycan and decorin, was upregulated when the C-20/A4 cells were transferred to suspension culture in alginate. Also, nexin-1, vimentin, and IGFBP-3, which are known to be expressed by primary chondrocytes, were differentially expressed in our study. Consistent with the proliferative phenotype of this cell line, few genes involved in matrix synthesis and turnover were highly expressed in the presence of serum. These results indicate that immortalized chondrocyte cell lines, rather than substituting for primary chondrocytes, may serve as models for extending findings on chondrocyte function not achievable by the use of primary chondrocytes.

[BibTex]

ei Finger, F., Schorle, C., Söder, S., Zien, A., Goldring, M., Aigner, T. Phenotypic Characterization of Human Chondrocyte Cell Line C-20/A4: A Comparison between Monolayer and Alginate Suspension Culture Cells Tissues Organs, 178(2):65-77, 2004 (article)

[BibTex]

Kernel Methods and their Potential Use in Signal Processing

Perez-Cruz, F., Bousquet, O.

IEEE Signal Processing Magazine, (Special issue on Signal Processing for Mining), 2004 (article) Accepted

PostScript [BibTex]

ei Perez-Cruz, F., Bousquet, O. Kernel Methods and their Potential Use in Signal Processing IEEE Signal Processing Magazine, (Special issue on Signal Processing for Mining), 2004 (article) Accepted

PostScript [BibTex]

E. Coli Inspired Propulsion for Swimming Microrobots

Behkam, Bahareh, Sitti, Metin

pages: 1037–1041, 2004 (article)

Abstract

Medical applications are among the most fascinating areas of microrobotics. For long, scientists have dreamed of miniature smart devices that can travel inside the human body and carry out a host of complex operations such as minimally invasive surgery (MIS), highly localized drug delivery, and screening for diseases that are in their very early stages. Still a distant dream, significant progress in micro and nanotechnology brings us closer to materializing it. For such a miniature device to be injected into the body, it has to be 800 μm or smaller in diameter. Miniature, safe and energy efficient propulsion systems hold the key to maturing this technology but they pose significant challenges. Scaling the macroscale natation mechanisms to micro/nano length scales is unfeasible. It has been estimated that a vibrating-fin driven swimming robot shorter than 6 mm can not overcome the viscous drag forces in water. In this paper, the authors propose a new type of propulsion inspired by the motility mechanism of bacteria with peritrichous flagellation, such as Escherichia coli, Salmonella typhimurium and Serratia marcescens. The perfomance of the propulsive mechanism is estimated by modeling the dynamics of the motion. The motion of the moving organelle is simulated and key parameters such as velocity, distribution of force and power requirments for different configurations of the tail are determined theoretically. In order to validate the theoretical result, a scaled up model of the swimming robot is fabricated and characterized in silicone oil using the Buckingham PI theorem for scaling. The results are compared with the theoretically computed values. These robots are intended to swim in stagnation/low velocity biofluid and reach currently inaccessible areas of the human body for disease inspection and possibly treatment. Potential target regions to use these robots include eyeball cavity, cerebrospinal fluid and the urinary system.

link (url) DOI [BibTex]

pi Behkam, Bahareh, Sitti, Metin E. Coli Inspired Propulsion for Swimming Microrobots pages: 1037–1041, 2004 (article)

link (url) DOI [BibTex]

Discovering optimal imitation strategies

Billard, A., Epars, Y., Calinon, S., Cheng, G., Schaal, S.

Robotics and Autonomous Systems, 47(2-3):68-77, 2004, clmc (article)

Abstract

This paper develops a general policy for learning relevant features of an imitation task. We restrict our study to imitation of manipulative tasks or of gestures. The imitation process is modeled as a hierarchical optimization system, which minimizes the discrepancy between two multi-dimensional datasets. To classify across manipulation strategies, we apply a probabilistic analysis to data in Cartesian and joint spaces. We determine a general metric that optimizes the policy of task reproduction, following strategy determination. The model successfully discovers strategies in six different imitative tasks and controls task reproduction by a full body humanoid robot.

[BibTex]

am Billard, A., Epars, Y., Calinon, S., Cheng, G., Schaal, S. Discovering optimal imitation strategies Robotics and Autonomous Systems, 47(2-3):68-77, 2004, clmc (article)

[BibTex]

Rhythmic movement is not discrete

Schaal, S., Sternad, D., Osu, R., Kawato, M.

Nature Neuroscience, 7(10):1137-1144, 2004, clmc (article)

Abstract

Rhythmic movements, like walking, chewing, or scratching, are phylogenetically old mo-tor behaviors found in many organisms, ranging from insects to primates. In contrast, discrete movements, like reaching, grasping, or kicking, are behaviors that have reached sophistication primarily in younger species, particularly in primates. Neurophysiological and computational research on arm motor control has focused almost exclusively on dis-crete movements, essentially assuming similar neural circuitry for rhythmic tasks. In con-trast, many behavioral studies focused on rhythmic models, subsuming discrete move-ment as a special case. Here, using a human functional neuroimaging experiment, we show that in addition to areas activated in rhythmic movement, discrete movement in-volves several higher cortical planning areas, despite both movement conditions were confined to the same single wrist joint. These results provide the first neuroscientific evi-dence that rhythmic arm movement cannot be part of a more general discrete movement system, and may require separate neurophysiological and theoretical treatment.

link (url) [BibTex]

am Schaal, S., Sternad, D., Osu, R., Kawato, M. Rhythmic movement is not discrete Nature Neuroscience, 7(10):1137-1144, 2004, clmc (article)

link (url) [BibTex]

Uncompensated spins in a micro-patterned CoFeB / MnIr exchange bias system

Eimüller, T., Kato, T., Mizuno, T., Tsunashima, S., Quitmann, C., Ramsvik, T., Iwata, S., Schütz, G.

{Applied Physics Letters}, 85(12):2310-2312, 2004 (article)

mms

[BibTex]

mms Eimüller, T., Kato, T., Mizuno, T., Tsunashima, S., Quitmann, C., Ramsvik, T., Iwata, S., Schütz, G. Uncompensated spins in a micro-patterned CoFeB / MnIr exchange bias system {Applied Physics Letters}, 85(12):2310-2312, 2004 (article)

[BibTex]

Comparative study of magnetization reversal in isolated and strayfield coupled microcontacts

Meier, G., Eiselt, R., Bolte, M., Barthelmess, M., Eimüller, T., Fischer, P.

{Applied Physics Letters}, 85(7):1193-1195, 2004 (article)

mms

[BibTex]

mms Meier, G., Eiselt, R., Bolte, M., Barthelmess, M., Eimüller, T., Fischer, P. Comparative study of magnetization reversal in isolated and strayfield coupled microcontacts {Applied Physics Letters}, 85(7):1193-1195, 2004 (article)

[BibTex]

Grain boundary faceting close to the \Sigma3 coincidence misorientation in copper

Straumal, B., Polyakov, S., Bischoff, E., Mittemeijer, E.

{Zeitschrift f\"ur Metallkunde}, 95, pages: 939-944, 2004 (article)

mms

[BibTex]

mms Straumal, B., Polyakov, S., Bischoff, E., Mittemeijer, E. Grain boundary faceting close to the \Sigma3 coincidence misorientation in copper {Zeitschrift f\"ur Metallkunde}, 95, pages: 939-944, 2004 (article)

[BibTex]

Photoelectron spectroscopy on Pt atoms and clusters deposited on C(0001)

Fauth, K., Schneider, N., He\ssler, M., Schütz, G.

{European Physical Journal D}, 29(1):57-61, 2004 (article)

mms

[BibTex]

mms Fauth, K., Schneider, N., He\ssler, M., Schütz, G. Photoelectron spectroscopy on Pt atoms and clusters deposited on C(0001) {European Physical Journal D}, 29(1):57-61, 2004 (article)

[BibTex]

Enhanced flux line pinning by substrate induced defects in YBCO thin films

Albrecht, J., Leonhardt, S., Habermeier, H.-U., Brück, S., Spolenak, R., Kronmüller, H.

{Physica C}, 404, pages: 18-21, 2004 (article)

mms

[BibTex]

mms Albrecht, J., Leonhardt, S., Habermeier, H.-U., Brück, S., Spolenak, R., Kronmüller, H. Enhanced flux line pinning by substrate induced defects in YBCO thin films {Physica C}, 404, pages: 18-21, 2004 (article)

[BibTex]

Amorphous carbon nanotubes produced by a temperature controlled DC arc discharge

Liu, Y., Song, X., Zhao, T., Zhu, J., Hirscher, M., Phillipp, F.

{Carbon}, 42(8-9):1852-1855, 2004 (article)

mms

[BibTex]

mms Liu, Y., Song, X., Zhao, T., Zhu, J., Hirscher, M., Phillipp, F. Amorphous carbon nanotubes produced by a temperature controlled DC arc discharge {Carbon}, 42(8-9):1852-1855, 2004 (article)

[BibTex]

Initial oxidation of quasicrystals - an investigation by high-resolution RBS and ERDA

Plachke, D., Khellaf, A., Kurth, M., Szökefalvy-Nagy, A., Carstanjen, H. D.

{Journal of Non-Crystalline Solids}, 334-335, pages: 524-531, 2004 (article)

mms

[BibTex]

mms Plachke, D., Khellaf, A., Kurth, M., Szökefalvy-Nagy, A., Carstanjen, H. D. Initial oxidation of quasicrystals - an investigation by high-resolution RBS and ERDA {Journal of Non-Crystalline Solids}, 334-335, pages: 524-531, 2004 (article)

[BibTex]

First-principles modeling of magnetism and phase equilibria in binary alloys

Diaz-Ortiz, A., Drautz, R., Fähnle, M., Dosch, H.

{Journal of Alloys and Compounds}, 369, pages: 27-32, 2004 (article)

mms

[BibTex]

mms Diaz-Ortiz, A., Drautz, R., Fähnle, M., Dosch, H. First-principles modeling of magnetism and phase equilibria in binary alloys {Journal of Alloys and Compounds}, 369, pages: 27-32, 2004 (article)

[BibTex]

Critical thicknesses of domain formations in cubic particles and thin films

Kronmüller, H., Goll, D., Hertel, R., Schütz, G.

{Physica B}, 343(1-4):229-235, 2004 (article)

mms

[BibTex]

mms Kronmüller, H., Goll, D., Hertel, R., Schütz, G. Critical thicknesses of domain formations in cubic particles and thin films {Physica B}, 343(1-4):229-235, 2004 (article)

[BibTex]

Learning from demonstration and adaptation of biped locomotion

Nakanishi, J., Morimoto, J., Endo, G., Cheng, G., Schaal, S., Kawato, M.

Robotics and Autonomous Systems, 47(2-3):79-91, 2004, clmc (article)

Abstract

In this paper, we introduce a framework for learning biped locomotion using dynamical movement primitives based on non-linear oscillators. Our ultimate goal is to establish a design principle of a controller in order to achieve natural human-like locomotion. We suggest dynamical movement primitives as a central pattern generator (CPG) of a biped robot, an approach we have previously proposed for learning and encoding complex human movements. Demonstrated trajectories are learned through movement primitives by locally weighted regression, and the frequency of the learned trajectories is adjusted automatically by a novel frequency adaptation algorithmbased on phase resetting and entrainment of coupled oscillators. Numerical simulations and experimental implementation on a physical robot demonstrate the effectiveness of the proposed locomotioncontroller.

link (url) [BibTex]

am Nakanishi, J., Morimoto, J., Endo, G., Cheng, G., Schaal, S., Kawato, M. Learning from demonstration and adaptation of biped locomotion Robotics and Autonomous Systems, 47(2-3):79-91, 2004, clmc (article)

link (url) [BibTex]

Critical sizes for ferromagnetic spherical hollow nanoparticles

Goll, D., Berkowitz, A. E., Bertram, H. N.

{Physical Review B}, 70(18), 2004 (article)

mms

[BibTex]

mms Goll, D., Berkowitz, A. E., Bertram, H. N. Critical sizes for ferromagnetic spherical hollow nanoparticles {Physical Review B}, 70(18), 2004 (article)

[BibTex]

Grain boundary wetting by a solid phase; microstructural development in a Zn-5 wt\textpercent Al alloy

Lopez, G. A., Mittemeijer, E. J., Straumal, B. B.

{Acta Materialia}, 52(15):4537-4545, 2004 (article)

mms

[BibTex]

mms Lopez, G. A., Mittemeijer, E. J., Straumal, B. B. Grain boundary wetting by a solid phase; microstructural development in a Zn-5 wt\textpercent Al alloy {Acta Materialia}, 52(15):4537-4545, 2004 (article)

[BibTex]

Probing composition and interfacial interaction in oxide passivated coreshell iron nanoparticles by combining x-ray absorption and magnetic circular dichroism

Fauth, K., Goering, E. J., Schütz, G., Theil-Kuhn, L.

{Journal of Applied Physics}, 96(1):399-402, 2004 (article)

mms

[BibTex]

mms Fauth, K., Goering, E. J., Schütz, G., Theil-Kuhn, L. Probing composition and interfacial interaction in oxide passivated coreshell iron nanoparticles by combining x-ray absorption and magnetic circular dichroism {Journal of Applied Physics}, 96(1):399-402, 2004 (article)

[BibTex]

Electronic correlations, magnetism, and structure of Fe-Al subsystems: An LDA+U study

Lechermann, F., Fähnle, M., Meyer, B., Elsässer, C.

{Physical Review B}, 69, 2004 (article)

mms

[BibTex]

mms Lechermann, F., Fähnle, M., Meyer, B., Elsässer, C. Electronic correlations, magnetism, and structure of Fe-Al subsystems: An LDA+U study {Physical Review B}, 69, 2004 (article)

[BibTex]

Interaction of hydrogen isotopes with carbon nanostructures

Haluska, M., Hirscher, M., Becher, M., Dettlaff-Weglikowska, U., Chen, X., Roth, S.

{Materials Science and Engineering B}, 108, pages: 130-133, 2004 (article)

mms

[BibTex]

mms Haluska, M., Hirscher, M., Becher, M., Dettlaff-Weglikowska, U., Chen, X., Roth, S. Interaction of hydrogen isotopes with carbon nanostructures {Materials Science and Engineering B}, 108, pages: 130-133, 2004 (article)

[BibTex]

Formation of nanograined structure and decomposition of supersaturated solid solution during high pressure torsion of Al-Zn and Al-Mg alloys

Straumal, B. B., Baretzky, B., Mazilkin, A. A., Phillipp, F., Kogtenkova, O. A., Volkov, M. N., Valiev, R. Z.

{Acta Materialia}, 52, pages: 4469-4478, 2004 (article)

mms

[BibTex]

mms Straumal, B. B., Baretzky, B., Mazilkin, A. A., Phillipp, F., Kogtenkova, O. A., Volkov, M. N., Valiev, R. Z. Formation of nanograined structure and decomposition of supersaturated solid solution during high pressure torsion of Al-Zn and Al-Mg alloys {Acta Materialia}, 52, pages: 4469-4478, 2004 (article)

[BibTex]

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