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Empirical Inference Book Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond Schölkopf, B., Smola, A. 644, Adaptive Computation and Machine Learning, MIT Press, Cambridge, MA, USA, December 2002, Parts of this book, including an introduction to kernel methods, can be downloaded here.
In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs-kernels—for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics. Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.
Web DOI BibTeX
Empirical Inference Conference Paper Gender Classification of Human Faces Graf, A., Wichmann, F. In Biologically Motivated Computer Vision 2002, Biologically Motivated Computer Vision, 1-18, (Editors: Bülthoff, H. H., S.W. Lee, T. A. Poggio and C. Wallraven), Springer, Berlin, Germany, Second International Workshop on Biologically Motivated Computer Vision (BMCV 2002), November 2002
This paper addresses the issue of combining pre-processing methods—dimensionality reduction using Principal Component Analysis (PCA) and Locally Linear Embedding (LLE)—with Support Vector Machine (SVM) classification for a behaviorally important task in humans: gender classification. A processed version of the MPI head database is used as stimulus set. First, summary statistics of the head database are studied. Subsequently the optimal parameters for LLE and the SVM are sought heuristically. These values are then used to compare the original face database with its processed counterpart and to assess the behavior of a SVM with respect to changes in illumination and perspective of the face images. Overall, PCA was superior in classification performance and allowed linear separability.
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Empirical Inference Conference Paper Insect-Inspired Estimation of Self-Motion Franz, M., Chahl, J. In Proc. 2nd Workshop on Biologically Motivated Computer Vision 2002, BMCV 2002, Biologically Motivated Computer Vision, (2525)171-180, LNCS, (Editors: Bülthoff, H.H. , S.W. Lee, T.A. Poggio, C. Wallraven), Springer, Berlin, Germany, Second International Workshop on Biologically Motivated Computer Vision (BMCV 2002), November 2002
The tangential neurons in the fly brain are sensitive to the typical optic flow patterns generated during self-motion. In this study, we examine whether a simplified linear model of these neurons can be used to estimate self-motion from the optic flow. We present a theory for the construction of an optimal linear estimator incorporating prior knowledge about the environment. The optimal 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 turn out to be less reliable.
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Empirical Inference Poster Modelling Contrast Transfer in Spatial Vision Wichmann, F. Journal of Vision, 2(10):7, Second Annual Meeting of the Vision Sciences Society (VSS 2002), November 2002
Much of our information about spatial vision comes from detection experiments involving low-contrast stimuli. Contrast discrimination experiments provide one way to explore the visual system's response to stimuli of higher contrast, the results of which allow different models of contrast processing (e.g. energy versus gain-control models) to be critically assessed (Wichmann & Henning, 1999). Studies of detection and discrimination using pulse train stimuli in noise, on the other hand, make predictions about the number, position and properties of noise sources within the processing stream (Henning, Bird & Wichmann, 2002). Here I report modelling results combining data from both sinusoidal and pulse train experiments in and without noise to arrive at a more tightly constrained model of early spatial vision.
Web DOI BibTeX
Empirical Inference Poster Pulse train detection and discrimination in pink noise Henning, G., Wichmann, F., Bird, C. Journal of Vision, 2(7):229, Second Annual Meeting of the Vision Sciences Society (VSS 2002), November 2002
Much of our information about spatial vision comes from detection experiments involving low-contrast stimuli. Contrast discrimination experiments provide one way to explore the visual system's response to stimuli of higher contrast. We explored both detection and contrast discrimination performance with sinusoidal and "pulse-train" (or line) gratings. Both types of grating had a fundamental spatial frequency of 2.09-c/deg but the pulse-train, ideally, contains, in addition to its fundamental component, all the harmonics of the fundamental. Although the 2.09-c/deg pulse-train produced on the display was measured and shown to contain at least 8 harmonics at equal contrast, it was no more detectable than its most detectable component; no benefit from having additional information at the harmonics was measurable. The addition of broadband "pink" noise, designed to equalize the detectability of the components of the pulse train, made it about a factor of four more detectable than any of its components. However, in contrast-discrimination experiments, with an in-phase pedestal or masking grating of the same form and phase as the signal and 15% contrast, the noise did not improve the discrimination performance of the pulse train relative to that of its sinusoidal components. In contrast, a 2.09-c/deg "super train," constructed to have 8 equally detectable harmonics, was a factor of five more detectable than any of its components. We discuss the implications of these observations for models of early vision in particular the implications for possible sources of internal noise.
Web DOI BibTeX
Empirical Inference Poster Surface-slant-from-texture discrimination: Effects of slant level and texture type Rosas, P., Wichmann, F., Wagemans, J. Journal of Vision, 2(7):300, Second Annual Meeting of the Vision Sciences Society (VSS 2002), November 2002
The problem of surface-slant-from-texture was studied psychophysically by measuring the performances of five human subjects in a slant-discrimination task with a number of different types of textures: uniform lattices, randomly displaced lattices, polka dots, Voronoi tessellations, orthogonal sinusoidal plaid patterns, fractal or 1/f noise, “coherent” noise and a “diffusion-based” texture (leopard skin-like). The results show: (1) Improving performance with larger slants for all textures. (2) A “non-symmetrical” performance around a particular slant characterized by a psychometric function that is steeper in the direction of the more slanted orientation. (3) For sufficiently large slants (66 deg) there are no major differences in performance between any of the different textures. (4) For slants at 26, 37 and 53 degrees, however, there are marked differences between the different textures. (5) The observed differences in performance across textures for slants up to 53 degrees are systematic within subjects, and nearly so across them. This allows 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 surface. Polka dots tended to allow the best slant discrimination performance, noise patterns the worst up to the large slant of 66 degrees at which performance was almost independent of the particular texture chosen. Finally, our large number of 2AFC trials (approximately 2800 trials per texture across subjects) and associated tight confidence intervals may enable us to find out about which statistical properties of the textures could be responsible for surface-slant-from-texture estimation, with the ultimate goal of being able to predict observer performance for any arbitrary texture.
Web DOI BibTeX
Empirical Inference Conference Paper Combining sensory Information to Improve Visualization Ernst, M., Banks, M., Wichmann, F., Maloney, L., Bülthoff, H. In Proceedings of the Conference on Visualization ‘02 (VIS ‘02), 571-574, (Editors: Moorhead, R. , M. Joy), IEEE, Piscataway, NJ, USA, IEEE Conference on Visualization 2002 (VIS '02), October 2002
Seemingly effortlessly the human brain reconstructs the three-dimensional environment surrounding us from the light pattern striking the eyes. This seems to be true across almost all viewing and lighting conditions. One important factor for this apparent easiness is the redundancy of information provided by the sensory organs. For example, perspective distortions, shading, motion parallax, or the disparity between the two eyes' images are all, at least partly, redundant signals which provide us with information about the three-dimensional layout of the visual scene. Our brain uses all these different sensory signals and combines the available information into a coherent percept. In displays visualizing data, however, the information is often highly reduced and abstracted, which may lead to an altered perception and therefore a misinterpretation of the visualized data. In this panel we will discuss mechanisms involved in the combination of sensory information and their implications for simulations using computer displays, as well as problems resulting from current display technology such as cathode-ray tubes.
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Empirical Inference Article Constructing Boosting algorithms from SVMs: an application to one-class classification. Rätsch, G., Mika, S., Schölkopf, B., Müller, K. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(9):1184-1199, September 2002
We show via an equivalence of mathematical programs that a support vector (SV) algorithm can be translated into an equivalent boosting-like algorithm and vice versa. We exemplify this translation procedure for a new algorithm—one-class leveraging—starting from the one-class support vector machine (1-SVM). This is a first step toward unsupervised learning in a boosting framework. Building on so-called barrier methods known from the theory of constrained optimization, it returns a function, written as a convex combination of base hypotheses, that characterizes whether a given test point is likely to have been generated from the distribution underlying the training data. Simulations on one-class classification problems demonstrate the usefulness of our approach.
DOI BibTeX
Empirical Inference Conference Paper Incorporating Invariances in Non-Linear Support Vector Machines Chapelle, O., Schölkopf, B. In Advances in Neural Information Processing Systems, Advances in Neural Information Processing Systems 14, 609-616, (Editors: TG Dietterich and S Becker and Z Ghahramani), MIT Press, Cambridge, MA, USA, 15th Annual Neural Information Processing Systems Conference (NIPS 2001), September 2002
The choice of an SVM kernel corresponds to the choice of a representation of the data in a feature space and, to improve performance, it should therefore incorporate prior knowledge such as known transformation invariances. We propose a technique which extends earlier work and aims at incorporating invariances in nonlinear kernels. We show on a digit recognition task that the proposed approach is superior to the Virtual Support Vector method, which previously had been the method of choice.
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Autonomous Motion Article Forward models in visuomotor control Mehta, B., Schaal, S. J Neurophysiol, 88(2):942-53, August 2002, clmc
In recent years, an increasing number of research projects investigated whether the central nervous system employs internal models in motor control. While inverse models in the control loop can be identified more readily in both motor behavior and the firing of single neurons, providing direct evidence for the existence of forward models is more complicated. In this paper, we will discuss such an identification of forward models in the context of the visuomotor control of an unstable dynamic system, the balancing of a pole on a finger. Pole balancing imposes stringent constraints on the biological controller, as it needs to cope with the large delays of visual information processing while keeping the pole at an unstable equilibrium. We hypothesize various model-based and non-model-based control schemes of how visuomotor control can be accomplished in this task, including Smith Predictors, predictors with Kalman filters, tapped-delay line control, and delay-uncompensated control. Behavioral experiments with human participants allow exclusion of most of the hypothesized control schemes. In the end, our data support the existence of a forward model in the sensory preprocessing loop of control. As an important part of our research, we will provide a discussion of when and how forward models can be identified and also the possible pitfalls in the search for forward models in control.
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Empirical Inference Technical Report Kernel Dependency Estimation Weston, J., Chapelle, O., Elisseeff, A., Schölkopf, B., Vapnik, V. (98), Max Planck Institute for Biological Cybernetics, August 2002
We consider the learning problem of finding a dependency between a general class of objects and another, possibly different, general class of objects. The objects can be for example: vectors, images, strings, trees or graphs. Such a task is made possible by employing similarity measures in both input and output spaces using kernel functions, thus embedding the objects into vector spaces. Output kernels also make it possible to encode prior information and/or invariances in the loss function in an elegant way. We experimentally validate our approach on several tasks: mapping strings to strings, pattern recognition, and reconstruction from partial images.
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Empirical Inference Poster Phase information in the recognition of natural images Braun, D., Wichmann, F., Gegenfurtner, K. Perception, 31(ECVP Abstract Supplement):133, 25th European Conference on Visual Perception, August 2002
Fourier phase plays an important role in determining global image structure. For example, when the phase spectrum of an image of a flower is swapped with that of a tank, we usually perceive a tank, even though the amplitude spectrum is still that of the flower. Similarly, when the phase spectrum of an image is randomly swapped across frequencies, that is its Fourier energy is randomly distributed over the image, the resulting image becomes impossible to recognise. Our goal was to evaluate the effect of phase manipulations in a quantitative manner. Subjects viewed two images of natural scenes, one of which contained an animal (the target) embedded in the background. The spectra of the images were manipulated by adding random phase noise at each frequency. The phase noise was the independent variable, uniformly distributed between 0° and ±180°. Subjects were remarkably resistant to phase noise. Even with ±120° noise, subjects were still 75% correct. The proportion of correct answers closely followed the correlation between original and noise-distorted images. Thus it appears as if it was not the global phase information per se that determines our percept of natural images, but rather the effect of phase on local image features.
Web BibTeX
Empirical Inference Article The contributions of color to recognition memory for natural scenes Wichmann, F., Sharpe, L., Gegenfurtner, K. Journal of Experimental Psychology: Learning, Memory and Cognition, 28(3):509-520, May 2002
The authors used a recognition memory paradigm to assess the influence of color information on visual memory for images of natural scenes. Subjects performed 5-10% better for colored than for black-and-white images independent of exposure duration. Experiment 2 indicated little influence of contrast once the images were suprathreshold, and Experiment 3 revealed that performance worsened when images were presented in color and tested in black and white, or vice versa, leading to the conclusion that the surface property color is part of the memory representation. Experiments 4 and 5 exclude the possibility that the superior recognition memory for colored images results solely from attentional factors or saliency. Finally, the recognition memory advantage disappears for falsely colored images of natural scenes: The improvement in recognition memory depends on the color congruence of presented images with learned knowledge about the color gamut found within natural scenes. The results can be accounted for within a multiple memory systems framework.
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Empirical Inference Poster Detection and discrimination in pink noise Wichmann, F., Henning, G. 5:100, 5. T{\"u}binger Wahrnehmungskonferenz (TWK 2002), February 2002
Much of our information about early spatial vision comes from detection experiments involving low-contrast stimuli, which are not, perhaps, particularly "natural" stimuli. Contrast discrimination experiments provide one way to explore the visual system's response to stimuli of higher contrast whilst keeping the number of unknown parameters comparatively small. We explored both detection and contrast discrimination performance with sinusoidal and "pulse-train" (or line) gratings. Both types of grating had a fundamental spatial frequency of 2.09-c/deg but the pulse-train, ideally, contains, in addition to its fundamental component, all the harmonics of the fundamental. Although the 2.09-c/deg pulse-train produced on our display was measured using a high-performance digital camera (Photometrics) and shown to contain at least 8 harmonics at equal contrast, it was no more detectable than its most detectable component; no benefit from having additional information at the harmonics was measurable. The addition of broadband 1-D "pink" noise made it about a factor of four more detectable than any of its components. However, in contrast-discrimination experiments, with an in-phase pedestal or masking grating of the same form and phase as the signal and 15% contrast, the noise did not improve the discrimination performance of the pulse train relative to that of its sinusoidal components. We discuss the implications of these observations for models of early vision in particular the implications for possible sources of internal noise.
Web BibTeX
Empirical Inference Article Training invariant support vector machines DeCoste, D., Schölkopf, B. Machine Learning, 46(1-3):161-190, January 2002
Practical experience has shown that in order to obtain the best possible performance, prior knowledge about invariances of a classification problem at hand ought to be incorporated into the training procedure. We describe and review all known methods for doing so in support vector machines, provide experimental results, and discuss their respective merits. One of the significant new results reported in this work is our recent achievement of the lowest reported test error on the well-known MNIST digit recognition benchmark task, with SVM training times that are also significantly faster than previous SVM methods.
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Empirical Inference Technical Report A compression approach to support vector model selection von Luxburg, U., Bousquet, O., Schölkopf, B. (101), Max Planck Institute for Biological Cybernetics, 2002, see more detailed JMLR version
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 some classification hypothesis. The main idea is to relate the coding precision of this hypothesis to the width of the margin of the SVM. The compression coefficients connect well known quantities such as the radius-margin ratio 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 several real world datasets. As a result we found that compression coefficients can fairly accurately predict the parameters for which the test error is minimized.
BibTeX
Empirical Inference Conference Paper A kernel approach for learning from almost orthogonal patterns Schölkopf, B., Weston, J., Eskin, E., Leslie, C., Noble, W. In 13th European Conference on Machine Learning (ECML 2002) and 6th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'2002), Helsinki, Principles of Data Mining and Knowledge Discovery, Lecture Notes in Computer Science, 2430/2431:511-528, Lecture Notes in Computer Science, (Editors: T Elomaa and H Mannila and H Toivonen), Springer, Berlin, Germany, 13th European Conference on Machine Learning (ECML 2002) and 6th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'2002), 2002 PostScript DOI BibTeX
Autonomous Motion Conference Paper A locally weighted learning composite adaptive controller with structure adaptation Nakanishi, J., Farrell, J. A., Schaal, S. In IEEE International Conference on Intelligent Robots and Systems (IROS 2002), Lausanne, Sept.30-Oct.4 2002, 2002, clmc
This paper introduces a provably stable adaptive learning controller which employs nonlinear function approximation with automatic growth of the learning network according to the nonlinearities and the working domain of the control system. The unknown function in the dynamical system is approximated by piecewise linear models using a nonparametric regression technique. Local models are allocated as necessary and their parameters are optimized on-line. Inspired by composite adaptive control methods, the pro-posed learning adaptive control algorithm uses both the tracking error and the estimation error to up-date the parameters. We provide Lyapunov analyses that demonstrate the stability properties of the learning controller. Numerical simulations illustrate rapid convergence of the tracking error and the automatic structure adaptation capability of the function approximator. This paper introduces a provably stable adaptive learning controller which employs nonlinear function approximation with automatic growth of the learning network according to the nonlinearities and the working domain of the control system. The unknown function in the dynamical system is approximated by piecewise linear models using a nonparametric regression technique. Local models are allocated as necessary and their parameters are optimized on-line. Inspired by composite adaptive control methods, the pro-posed learning adaptive control algorithm uses both the tracking error and the estimation error to up-date the parameters. We provide Lyapunov analyses that demonstrate the stability properties of the learning controller. Numerical simulations illustrate rapid convergence of the tracking error and the automatic structure adaptation capability of the function approximator
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Physical Intelligence Article A micromechanical flying insect thorax Fearing, R., Avadhanula, S., Campolo, D., Sitti, M., Yan, J., Wood, R. Neurotechnology for Biomimetic Robots, 469-480, The MIT Press Cambridge, MA, 2002 BibTeX
Theory of Inhomogeneous Condensed Matter Article A novel technique for measuring diffusivities of short-lived radioisotopes in solids Voss, T., Strohm, A., Matics, S., Scharwaechter, P., Frank, W. Zeitschrift f\"ur Metallkunde, 93(10):1077-1082, 2002 BibTeX
Empirical Inference Poster Application of Monte Carlo Methods to Psychometric Function Fitting Wichmann, F. Proceedings of the 33rd European Conference on Mathematical Psychology, 44, 2002
The psychometric function relates an observer's performance to an independent variable, usually some physical quantity of a stimulus in a psychophysical task. Here I describe methods to (1) fitting psychometric functions, (2) assessing goodness-of-fit, and (3) providing confidence intervals for the function's parameters and other estimates derived from them. First I describe a constrained maximum-likelihood method for parameter estimation. Using Monte-Carlo simulations I demonstrate that it is important to have a fitting method that takes stimulus-independent errors (or "lapses") into account. Second, a number of goodness-of-fit tests are introduced. Because psychophysical data sets are usually rather small I advocate the use of Monte Carlo resampling techniques that do not rely on asymptotic theory for goodness-of-fit assessment. Third, a parametric bootstrap is employed to estimate the variability of fitted parameters and derived quantities such as thresholds and slopes. I describe how the bootstrap bridging assumption, on which the validity of the procedure depends, can be tested without incurring too high a cost in computation time. Finally I describe how the methods can be extended to test hypotheses concerning the form and shape of several psychometric functions. Software describing the methods is available (http://www.bootstrap-software.com/psignifit/), as well as articles describing the methods in detail (Wichmann&Hill, Perception&Psychophysics, 2001a,b).
BibTeX
Autonomous Motion Book Chapter Arm and hand movement control Schaal, S. In The handbook of brain theory and neural networks, 2nd Edition, 110-113, 2, (Editors: Arbib, M. A.), MIT Press, Cambridge, MA, 2002, clmc
This is a review article on computational and biological research on arm and hand control.
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Theory of Inhomogeneous Condensed Matter Conference Paper Capture-Numbers and Island Size-Distributions in Irreversible Homoepitaxial Growth: A Rate-Equation Approach Popescu, M. N., Family, F., Amar, J. G. In Atomistic Aspects of Epitaxial Growth, 99-110, NATO Science Series: Series 2, Mathematics, Physics, and Chemistry, Kluwer Academic Publishers, Dassia [Korfu, Greece], 2002 BibTeX
Theory of Inhomogeneous Condensed Matter Book Chapter Characterizing the Morphology of Disordered Materials Arns, C. H., Knackstedt, M. A., Mecke, K. In Morphology of Condensed Matter, 600:37-74, Lecture Notes in Physics, Springer, Berlin [et al.], 2002 BibTeX
Micro, Nano, and Molecular Systems Article Chirality-specific nonlinear spectroscopies in isotropic media Fischer, P., Albrecht, A. BULLETIN OF THE CHEMICAL SOCIETY OF JAPAN, 75(5):1119-1124, 2002, 10th International Conference on Time-Resolved Vibrational Spectroscopy (TRVS 2001), OKAZZAKI, JAPAN, MAY 21-25, 2001
Sum or difference frequency generation (SFG or DFG) in isotropic media is in the electric-dipole approximation only symmetry allowed for optically active systems. The hyperpolarizability giving rise to these three-wave mixing processes features only one isotropic component. It factorizes into two terms, an energy (denominator) factor and a triple product of transition moments. These forbid degenerate SFG, i.e., second harmonic generation, as well as the existence of the linear electrooptic effect (Pockels effect) in isotropic media. This second order response also has no static limit, which leads to particularly strong resonance phenomena that are qualitatively different from those usually seen in the ubiquitous even-wave mixing spectroscopies. In particular, the participation of two (not the usual one) excited states is essential to achieve dramatic resonance enhancement, We report our first efforts to see such resonantly enhanced chirality specific SFG.
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Theory of Inhomogeneous Condensed Matter Article Cluster-Computing and Computational Science mit der Wuppertaler Alpha-Linux-Cluster-Engine ALiCE Arndt, H., Arnold, G., Eicker, N., Fliegner, D., Frommer, A., Hentschke, R., Isalia, F., Kabrede, H., Krech, M., Lippert, T. H., Neff, H., Orth, B., Schilling, K., Schroers, W., Tichy, W. Praxis der Informationsverarbeitung und Kommunikation, 25(1):21-38, 2002 BibTeX
Theory of Inhomogeneous Condensed Matter Article Colloid aggregation induced by oppositely charged polyions Harnau, L., Hansen, J. P. Journal of Chemical Physics, 116(20):9051-9057, 2002 BibTeX
Theory of Inhomogeneous Condensed Matter Article Conformal map modeling of the pinning transition in Laplacian growth Hentschel, H. G. E., Popescu, M. N., Family, F. Physical Review E, 65(3), 2002 BibTeX
Empirical Inference Article Contrast discrimination with pulse-trains in pink noise Henning, G., Bird, C., Wichmann, F. Journal of the Optical Society of America A, 19(7):1259-1266, 2002
Detection performance was measured with sinusoidal and pulse-train gratings. Although the 2.09-c/deg pulse-train, or line gratings, contained at least 8 harmonics all at equal contrast, they were no more detectable than their most detectable component. The addition of broadband pink noise designed to equalize the detectability of the components of the pulse train made the pulse train about a factor of four more detectable than any of its components. However, in contrast-discrimination experiments, with a pedestal or masking grating of the same form and phase as the signal and 15% contrast, the noise did not affect the discrimination performance of the pulse train relative to that obtained with its sinusoidal components. We discuss the implications of these observations for models of early vision in particular the implications for possible sources of internal noise.
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Empirical Inference Article Contrast discrimination with sinusoidal gratings of different spatial frequency Bird, C., Henning, G., Wichmann, F. Journal of the Optical Society of America A, 19(7):1267-1273, 2002
The detectability of contrast increments was measured as a function of the contrast of a masking or “pedestal” grating at a number of different spatial frequencies ranging from 2 to 16 cycles per degree of visual angle. The pedestal grating always had the same orientation, spatial frequency and phase as the signal. The shape of the contrast increment threshold versus pedestal contrast (TvC) functions depend of the performance level used to define the “threshold,” but when both axes are normalized by the contrast corresponding to 75% correct detection at each frequency, the (TvC) functions at a given performance level are identical. Confidence intervals on the slope of the rising part of the TvC functions are so wide that it is not possible with our data to reject Weber’s Law.
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Theory of Inhomogeneous Condensed Matter Article Crossover between strong- and weak-field critical adsorption and the determination of the universal exponent η⊥ Nickel, B., Schlesener, F., Donner, W., Detlefs, C., Dosch, H. Journal of Chemical Physics, 117(2):902-908, 2002 BibTeX
Theory of Inhomogeneous Condensed Matter Ph.D. Thesis Diffusion in amorphen Vorstufen von Si-(B-)C-N-Keramiken und verwandten Materialien Voss, L. T. Universität Stuttgart, Stuttgart, 2002 BibTeX
Theory of Inhomogeneous Condensed Matter Article Dynamic surface critical behavior of isotropic Heisenberg ferromagnets: boundary conditions, renormalized field theory, and computer simulation results Diehl, H. W., Krech, M., Karl, H. Physical Review B, 66, 2002 BibTeX
Theory of Inhomogeneous Condensed Matter Article Effective forces in colloidal mixtures: From depletion attraction to accumulation repulsion Louis, A. A., Allahyarov, E., Löwen, H., Roth, R. Physical Review E, 65(6), 2002 BibTeX
Theory of Inhomogeneous Condensed Matter Article Entropic torque Roth, R., van Roij, R., Andrienko, D., Mecke, K. R., Dietrich, S. Physical Review Letters, 89(8):088301, 2002 DOI BibTeX
Physical Intelligence Article Evidence for van der Waals adhesion in gecko setae Autumn, K., Sitti, M., Liang, Y. A., Peattie, A. M., Hansen, W. R., Sponberg, S., Kenny, T. W., Fearing, R., Israelachvili, J. N., Full, R. J. Proceedings of the National Academy of Sciences, 99(19):12252-12256, National Acad Sciences, 2002 BibTeX
Theory of Inhomogeneous Condensed Matter Article Fluids of platelike particles near a hard wall Harnau, L., Dietrich, S. Physical Review E, 65(2):021505, 2002 DOI BibTeX
Theory of Inhomogeneous Condensed Matter Article Fundamental measure theory for hard-sphere mixtures revisited: the White Bear version Roth, R., Evans, R., Lang, A., Kahl, G. Journal of Physics-Condensed Matter, 14(46):12063-12078, 2002 BibTeX
Theory of Inhomogeneous Condensed Matter Article Geometrically-controlled twist transitions in nematic cells Patricio, P., Telo da Gama, M. M., Dietrich, S. Physical Review Letters, 88(24):245502, 2002 DOI BibTeX
Theory of Inhomogeneous Condensed Matter Article Grenzflächenstrukturen von Fluiden Dietrich, S. Physik Journal, 1(7/8):57-61, 2002 BibTeX
Theory of Inhomogeneous Condensed Matter Article Kinetics of submonolayer epitaxial growth Amar, J. G., Family, F., Popescu, M. N. Computer Physics Communications, 146(1):1-8, 2002 BibTeX
Autonomous Motion Conference Paper Learning rhythmic movements by demonstration using nonlinear oscillators Ijspeert, J. A., Nakanishi, J., Schaal, S. In IEEE International Conference on Intelligent Robots and Systems (IROS 2002), 958-963, Piscataway, NJ: IEEE, Lausanne, Sept.30-Oct.4 2002, 2002, clmc
Locally weighted learning (LWL) is a class of statistical learning techniques that provides useful representations and training algorithms for learning about complex phenomena during autonomous adaptive control of robotic systems. This paper introduces several LWL algorithms that have been tested successfully in real-time learning of complex robot tasks. We discuss two major classes of LWL, memory-based LWL and purely incremental LWL that does not need to remember any data explicitly. In contrast to the traditional beliefs that LWL methods cannot work well in high-dimensional spaces, we provide new algorithms that have been tested in up to 50 dimensional learning problems. The applicability of our LWL algorithms is demonstrated in various robot learning examples, including the learning of devil-sticking, pole-balancing of a humanoid robot arm, and inverse-dynamics learning for a seven degree-of-freedom robot.
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Autonomous Motion Book Chapter Learning robot control Schaal, S. In The handbook of brain theory and neural networks, 2nd Edition, 983-987, 2, (Editors: Arbib, M. A.), MIT Press, Cambridge, MA, 2002, clmc
This is a review article on learning control in robots.
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Empirical Inference Conference Paper Luminance Artifacts on CRT Displays Wichmann, F. In IEEE Visualization, 571-574, (Editors: Moorhead, R.; Gross, M.; Joy, K. I.), IEEE Visualization, 2002
Most visualization panels today are still built around cathode-ray tubes (CRTs), certainly on personal desktops at work and at home. Whilst capable of producing pleasing images for common applications ranging from email writing to TV and DVD presentation, it is as well to note that there are a number of nonlinear transformations between input (voltage) and output (luminance) which distort the digital and/or analogue images send to a CRT. Some of them are input-independent and hence easy to fix, e.g. gamma correction, but others, such as pixel interactions, depend on the content of the input stimulus and are thus harder to compensate for. CRT-induced image distortions cause problems not only in basic vision research but also for applications where image fidelity is critical, most notably in medicine (digitization of X-ray images for diagnostic purposes) and in forms of online commerce, such as the online sale of images, where the image must be reproduced on some output device which will not have the same transfer function as the customer's CRT. I will present measurements from a number of CRTs and illustrate how some of their shortcomings may be problematic for the aforementioned applications.
BibTeX
Theory of Inhomogeneous Condensed Matter Book Chapter Mark Correlations: Relating Physical Properties to Spatial Distributions Beisbart, C., Kerscher, M., Mecke, K. In Morphology of Condensed Matter, 600:358-390, Lecture Notes in Physics, Springer, Berlin [et al.], 2002 BibTeX
Theory of Inhomogeneous Condensed Matter Article Microscopic theory of solvent-mediated long-range forces: Influence of wetting Archer, A. J., Evans, R., Roth, R. Europhysics Letters, 59(4):526-532, 2002 BibTeX
Theory of Inhomogeneous Condensed Matter Book Morphology of Condensed Matter - Physics and Geometry of Spatially Complex Systems 600:439 p., Lecture Notes in Physics, Springer, Berlin [et al.], 2002 BibTeX
Autonomous Motion Conference Paper Movement imitation with nonlinear dynamical systems in humanoid robots Ijspeert, J. A., Nakanishi, J., Schaal, S. In International Conference on Robotics and Automation (ICRA2002), Washinton, May 11-15 2002, 2002, clmc
Locally weighted learning (LWL) is a class of statistical learning techniques that provides useful representations and training algorithms for learning about complex phenomena during autonomous adaptive control of robotic systems. This paper introduces several LWL algorithms that have been tested successfully in real-time learning of complex robot tasks. We discuss two major classes of LWL, memory-based LWL and purely incremental LWL that does not need to remember any data explicitly. In contrast to the traditional beliefs that LWL methods cannot work well in high-dimensional spaces, we provide new algorithms that have been tested in up to 50 dimensional learning problems. The applicability of our LWL algorithms is demonstrated in various robot learning examples, including the learning of devil-sticking, pole-balancing of a humanoid robot arm, and inverse-dynamics learning for a seven degree-of-freedom robot.
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Physical Intelligence Conference Paper Nanomolding based fabrication of synthetic gecko foot-hairs Sitti, M., Fearing, R. S. In Nanotechnology, 2002. IEEE-NANO 2002. Proceedings of the 2002 2nd IEEE Conference on, 137-140, 2002 BibTeX
Theory of Inhomogeneous Condensed Matter Conference Paper Non-Gaussian morphology of galaxy-cluster distribution: Minkowski functionals of the REFLEX catalogue Kerscher, M., Mecke, K., Schücker, P., Collaboration, R. In Tracing Cosmic Evolution with Galaxy Clusters. Proceedings of the Sesto-2001 Workshop, 268:60-62, Astronomical Society Pacific Conference Series, Alto Adige/Südtirol, 2002 BibTeX