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Modern Magnetic Systems Conference Paper Positron Annihilation Studies on Stable and Undercooled Metal Melts at the Stuttgart Pelletron Stoll, H., Siegle, A., Major, J. In Application of Accelerators in Research and Industry, 576:749-752, AIP Conference Proceedings, Denton, Texas, USA, 2001 BibTeX
Modern Magnetic Systems Article Positron annihilation in stable and supercooled metallic melts Seeger, A., Siegle, A., Stoll, H. {Zeitschrift f\"ur Metallkunde}, 92(7):632-644, 2001 BibTeX
Modern Magnetic Systems Conference Paper Positron-age-momentum correlation Stoll, H., Bandzuch, P., Siegle, A. In Positron Annihilation: Proceedings of the 12th International Conference on Positron Annihilation, 363-365:547-551, Materials Science Forum, Trans Tech Publications Ltd., München, 2001 BibTeX
Modern Magnetic Systems Article Soft X-ray microscopy to 25 nm with applications to biology and magnetic materials Denbeaux, G., Anderson, E., Chao, W., Eimüller, T., Johnson, L., Köhler, M., Larabell, C., Legros, M., Fischer, P., Pearson, A., Schütz, G., Yager, D., Attwood, D. {Nuclear Instruments and Methods in Physics Research A}, 467-468:841-844, 2001 BibTeX
Modern Magnetic Systems Article Spontaneous L12 order at Ni90Al10(110) surfaces: An X-ray and first-principles-calculation study Drautz, R., Reichert, H., Fähnle, M., Dosch, H., Sanchez, J. M. {Physical Review Letters}, 87(23), 2001 BibTeX
Modern Magnetic Systems Article Strain relaxation and internal friction in the range of the glass transition Ege, M., Ulfert, W., Kronmüller, H. {Zeitschrift f\"ur Metallkunde}, 92(7):690-694, 2001 BibTeX
Modern Magnetic Systems Article Structural vacancies in B2 CoAl and NiAl Meyer, B., Bester, G., Fähnle, M. {Scripta Materialia}, 44(10):2485-2488, 2001 BibTeX
Modern Magnetic Systems Article Structural vacancies in B2-CoAl and NiAl Meyer, B., Bester, G., Fähnle, M. {Scripta Materialia}, 44:2485-2488, 2001 BibTeX
Modern Magnetic Systems Article Structure of superconducting [BaCuOx]2/[CaCuO2]n superlattices on SrTiO3(001) investigated by x-ray scattering Aruta, C., Zegenhagen, J., Cowie, B., Balestrino, G., Pasquini, G., Medaglia, P. G., Ricci, F., Luebbert, D., Baumbach, T., Riedo, E., Ortega, L., Kremer, R., Albrecht, J. {Physica Status Solidi (A)}, 183:353-364, 2001 BibTeX
Modern Magnetic Systems Article Study of in-plane magnetic domains with magnetic transmission X-ray microscopy Fischer, P., Eimüller, T., Schütz, G., Köhler, M., Bayreuther, G., Denbeaux, G., Attwood, D. {Journal of Applied Physics}, 89:7159-7161, 2001 BibTeX
Modern Magnetic Systems Conference Paper Submicrometer spatially resolved measurements of mechanical properties and correlation to microstructure and composition Kunert, M., Baretzky, B., Baker, S. P., Mittemeijer, E. J. In Fundamentals of Nanoindentation and Nanotribology II, 649:Q3.2.1-Q3.2.6, Materials Research Society Symposium Proceedings, MRS, Boston, MA, USA, 2001 BibTeX
Modern Magnetic Systems Article The coercivity of the melt-spun Sm-Fe-Ga-C permanent magnets and the effect of additives (Nb, Cu and Zr) Zhang, J. X., Kleinschroth, I., Goll, D., Cuevas, F., Kronmüller, H. {Journal of Physics-Condensed Matter}, 13(46):10487-10496, 2001 BibTeX
Modern Magnetic Systems Conference Paper The six-jump diffusion cycles in B2-compounds Drautz, R., Meyer, B., Fähnle, M. In Proceedings of DIMAT 2000, the Fifth International Conference on Diffusion in Materials, 417-422, Defect and Diffusion Forum, Scitec Publications Ltd., Paris, France, 2001 BibTeX
Modern Magnetic Systems Article The six-jump diffusion cycles in B2-compounds Drautz, R., Meyer, B., Fähnle, M. {Defect and Diffusion Forum}, 194-199:417-422, 2001 BibTeX
Modern Magnetic Systems Article Transmission X-ray microscopy using X-MCD Eimüller, T., Fischer, P., Köhler, M., Scholz, M., Guttmann, P., Denbeaux, G., Glück, S., Bayreuther, G., Schmahl, G., Attwood, D., Schütz, G. {Applied Physics A}, 73:697-701, 2001 BibTeX
Modern Magnetic Systems Article Uniaxial orientational order-disorder transitions in diammine magnesium halides, Mg(ND3)2Cl2 and Mg(ND3)2Br2, investigated by neutron diffraction Leineweber, A., Jacobs, H., Fischer, P., Böttger, G. {Journal of Solid State Chemistry}, 156(2):487-499, 2001 BibTeX
Modern Magnetic Systems Ph.D. Thesis Von der elektronischen Struktur zum makroskopischen Verhalten: Eine Multi-Skalen Analyse der Plastizität Kohlhammer, S. Universität Stuttgart, Stuttgart, 2001 BibTeX
Modern Magnetic Systems Article X-MCD study of mixed valence manganites Sikora, M., Kapusta, C., Zajac, D., Tokarz, W., Attenkofer, K., Fischer, P., Goering, E., Schütz, G. {Journal of Alloys and Compounds}, 328(1-2):100-104, 2001 DOI BibTeX
Modern Magnetic Systems Article X-ray magnetic circular dichroism - a universal tool for magnetic investigations Goering, E., Will, J., Geissler, J., Justen, M., Weigand, F., Schütz, G. {Journal of Alloys and Compounds}, 328:14-19, 2001 DOI BibTeX
Modern Magnetic Systems Article XMCD study of the Ruddlesden-Popper Phase La1.2Nd0.2Sr1.6Mn2O7 Weigand, F., Goering, E., Geissler, J., Justen, M., Dörr, K., Ruck, K., Schütz, G. {Journal of Synchrotron Radiation}, 8:431-433, 2001 DOI BibTeX
Autonomous Motion Conference Paper Reciprocal excitation between biological and robotic research Schaal, S., Sternad, D., Dean, W., Kotoska, S., Osu, R., Kawato, M. In Sensor Fusion and Decentralized Control in Robotic Systems III, Proceedings of SPIE, 4196:30-40, Boston, MA, Nov.5-8, 2000, November 2000, clmc
While biological principles have inspired researchers in computational and engineering research for a long time, there is still rather limited knowledge flow back from computational to biological domains. This paper presents examples of our work where research on anthropomorphic robots lead us to new insights into explaining biological movement phenomena, starting from behavioral studies up to brain imaging studies. Our research over the past years has focused on principles of trajectory formation with nonlinear dynamical systems, on learning internal models for nonlinear control, and on advanced topics like imitation learning. The formal and empirical analyses of the kinematics and dynamics of movements systems and the tasks that they need to perform lead us to suggest principles of motor control that later on we found surprisingly related to human behavior and even brain activity.
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Empirical Inference Book Advances in Large Margin Classifiers Smola, A., Bartlett, P., Schölkopf, B., Schuurmans, D. 422, Neural Information Processing, MIT Press, Cambridge, MA, USA, October 2000
The concept of large margins is a unifying principle for the analysis of many different approaches to the classification of data from examples, including boosting, mathematical programming, neural networks, and support vector machines. The fact that it is the margin, or confidence level, of a classification--that is, a scale parameter--rather than a raw training error that matters has become a key tool for dealing with classifiers. This book shows how this idea applies to both the theoretical analysis and the design of algorithms. The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. Among the contributors are Manfred Opper, Vladimir Vapnik, and Grace Wahba.
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Autonomous Motion Conference Paper Nonlinear dynamical systems as movement primitives Schaal, S., Kotosaka, S., Sternad, D. In Humanoids2000, First IEEE-RAS International Conference on Humanoid Robots, CD-Proceedings, Cambridge, MA, September 2000, clmc
This paper explores the idea to create complex human-like movements from movement primitives based on nonlinear attractor dynamics. Each degree-of-freedom of a limb is assumed to have two independent abilities to create movement, one through a discrete dynamic system, and one through a rhythmic system. The discrete system creates point-to-point movements based on internal or external target specifications. The rhythmic system can add an additional oscillatory movement relative to the current position of the discrete system. In the present study, we develop appropriate dynamic systems that can realize the above model, motivate the particular choice of the systems from a biological and engineering point of view, and present simulation results of the performance of such movement primitives. The model was implemented for a drumming task on a humanoid robot
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Autonomous Motion Conference Paper Real Time Learning in Humanoids: A challenge for scalability of Online Algorithms Vijayakumar, S., Schaal, S. In Humanoids2000, First IEEE-RAS International Conference on Humanoid Robots, CD-Proceedings, Cambridge, MA, September 2000, clmc
While recent research in neural networks and statistical learning has focused mostly on learning from finite data sets without stringent constraints on computational efficiency, there is an increasing number of learning problems that require real-time performance from an essentially infinite stream of incrementally arriving data. This paper demonstrates how even high-dimensional learning problems of this kind can successfully be dealt with by techniques from nonparametric regression and locally weighted learning. As an example, we describe the application of one of the most advanced of such algorithms, Locally Weighted Projection Regression (LWPR), to the on-line learning of the inverse dynamics model of an actual seven degree-of-freedom anthropomorphic robot arm. LWPR's linear computational complexity in the number of input dimensions, its inherent mechanisms of local dimensionality reduction, and its sound learning rule based on incremental stochastic leave-one-out cross validation allows -- to our knowledge for the first time -- implementing inverse dynamics learning for such a complex robot with real-time performance. In our sample task, the robot acquires the local inverse dynamics model needed to trace a figure-8 in only 60 seconds of training.
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Autonomous Motion Conference Paper Synchronized robot drumming by neural oscillator Kotosaka, S., Schaal, S. In The International Symposium on Adaptive Motion of Animals and Machines, Montreal, Canada, August 2000, clmc
Sensory-motor integration is one of the key issues in robotics. In this paper, we propose an approach to rhythmic arm movement control that is synchronized with an external signal based on exploiting a simple neural oscillator network. Trajectory generation by the neural oscillator is a biologically inspired method that can allow us to generate a smooth and continuous trajectory. The parameter tuning of the oscillators is used to generate a synchronized movement with wide intervals. We adopted the method for the drumming task as an example task. By using this method, the robot can realize synchronized drumming with wide drumming intervals in real time. The paper also shows the experimental results of drumming by a humanoid robot.
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Autonomous Motion Article A brachiating robot controller Nakanishi, J., Fukuda, T., Koditschek, D. E. IEEE Transactions on Robotics and Automation, 16(2):109-123, 2000, clmc
We report on our empirical studies of a new controller for a two-link brachiating robot. Motivated by the pendulum-like motion of an apeâ??s brachiation, we encode this task as the output of a â??target dynamical system.â? Numerical simulations indicate that the resulting controller solves a number of brachiation problems that we term the â??ladder,â? â??swing-up,â? and â??ropeâ? problems. Preliminary analysis provides some explanation for this success. The proposed controller is implemented on a physical system in our laboratory. The robot achieves behaviors including â??swing locomotionâ? and â??swing upâ? and is capable of continuous locomotion over several rungs of a ladder. We discuss a number of formal questions whose answers will be required to gain a full understanding of the strengths and weaknesses of this approach.
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Theory of Inhomogeneous Condensed Matter Article A vacancy-related muon species in crystalline silicon Schefzik, M., Scheuermann, R., Schimmele, L., Seeger, A., Herlach, D., Kormann, O., Major, J., Röck, A. Physica B, 289-290:511-515, 2000 BibTeX
Micro, Nano, and Molecular Systems Article Ab initio investigation of the sum-frequency hyperpolarizability of small chiral molecules Champagne, B., Fischer, P., Buckingham, A. CHEMICAL PHYSICS LETTERS, 331(1):83-88, 2000
Using a sum-over-states procedure based on configuration interaction singles /6-311++G{*}{*}, we have computed the sum-frequency hyperpolarizability beta (ijk)(-3 omega; 2 omega, omega) Of two small chiral molecules, R-monofluoro-oxirane and R-(+)-propylene oxide. Excitation energies were scaled to fit experimental UV-absorption data and checked with ab initio values from time-dependent density functional theory. The isotropic part of the computed hyperpolarizabilities, beta(-3 omega; 2 omega, omega), is much smaller than that reported previously from sum-frequency generation experiments on aqueous solutions of arabinose. Comparison is made with a single-centre chiral model. (C) 2000 Elsevier Science B.V. All rights reserved.
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Empirical Inference Book Chapter An Introduction to Kernel-Based Learning Algorithms Müller, K., Mika, S., Rätsch, G., Tsuda, K., Schölkopf, B. In Handbook of Neural Network Signal Processing, 4, (Editors: Yu Hen Hu and Jang-Neng Hwang), CRC Press, 2000 (Published) BibTeX
Autonomous Motion Book Chapter Biomimetic gaze stabilization Shibata, T., Schaal, S. In Robot learning: an Interdisciplinary approach, 31-52, (Editors: Demiris, J.;Birk, A.), World Scientific, 2000, clmc
Accurate oculomotor control is one of the essential pre-requisites for successful visuomotor coordination. In this paper, we suggest a biologically inspired control system for learning gaze stabilization with a biomimetic robotic oculomotor system. In a stepwise fashion, we develop a control circuit for the vestibulo-ocular reflex (VOR) and the opto-kinetic response (OKR), and add a nonlinear learning network to allow adaptivity. We discuss the parallels and differences of our system with biological oculomotor control and suggest solutions how to deal with nonlinearities and time delays in the control system. In simulation and actual robot studies, we demonstrate that our system can learn gaze stabilization in real time in only a few seconds with high final accuracy.
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Empirical Inference Conference Paper Choosing nu in support vector regression with different noise models — theory and experiments Chalimourda, A., Schölkopf, B., Smola, A. In International Joint Conference on Neural Networks, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, IJCNN 2000, Neural Computing: New Challenges and Perspectives for the New Millennium, IEEE, International Joint Conference on Neural Networks, 2000 BibTeX
Physical Intelligence Article Controlled pushing of nanoparticles: modeling and experiments Sitti, M., Hashimoto, H. IEEE/ASME transactions on mechatronics, 5(2):199-211, IEEE, 2000 BibTeX
Theory of Inhomogeneous Condensed Matter Article Diffusion of 71Ge in the amorphous ceramic Si28C36N36 Matics, S., Frank, W. Journal of Non-Crystalline Solids, 266-269:830-834, 2000 BibTeX
Autonomous Motion Article Dynamics of a bouncing ball in human performance Sternad, D., Duarte, M., Katsumata, H., Schaal, S. Physical Review E, 63(011902):1-8, 2000, clmc
On the basis of a modified bouncing-ball model, we investigated whether human movements utilize principles of dynamic stability in their performance of a similar movement task. Stability analyses of the model provided predictions about conditions indicative of a dynamically stable period-one regime. In a series of experiments, human subjects bounced a ball rhythmically on a racket and displayed these conditions supporting that they attuned to and exploited the dynamic stability properties of the task.
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Autonomous Motion Conference Paper Fast and efficient incremental learning for high-dimensional movement systems Vijayakumar, S., Schaal, S. In International Conference on Robotics and Automation (ICRA2000), San Francisco, April 2000, 2000, clmc
We introduce a new algorithm, Locally Weighted Projection Regression (LWPR), for incremental real-time learning of nonlinear functions, as particularly useful for problems of autonomous real-time robot control that re-quires internal models of dynamics, kinematics, or other functions. At its core, LWPR uses locally linear models, spanned by a small number of univariate regressions in selected directions in input space, to achieve piecewise linear function approximation. The most outstanding properties of LWPR are that it i) learns rapidly with second order learning methods based on incremental training, ii) uses statistically sound stochastic cross validation to learn iii) adjusts its local weighting kernels based on only local information to avoid interference problems, iv) has a computational complexity that is linear in the number of inputs, and v) can deal with a large number ofâ??possibly redundant and/or irrelevantâ??inputs, as shown in evaluations with up to 50 dimensional data sets for learning the inverse dynamics of an anthropomorphic robot arm. To our knowledge, this is the first incremental neural network learning method to combine all these properties and that is well suited for complex on-line learning problems in robotics.
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Autonomous Motion Conference Paper Fast learning of biomimetic oculomotor control with nonparametric regression networks Shibata, T., Schaal, S. In International Conference on Robotics and Automation (ICRA2000), 3847-3854, San Francisco, April 2000, 2000, clmc
Accurate oculomotor control is one of the essential pre-requisites of successful visuomotor coordination. Given the variable nonlinearities of the geometry of binocular vision as well as the possible nonlinearities of the oculomotor plant, it is desirable to accomplish accurate oculomotor control through learning approaches. In this paper, we investigate learning control for a biomimetic active vision system mounted on a humanoid robot. By combining a biologically inspired cerebellar learning scheme with a state-of-the-art statistical learning network, our robot system is able to acquire high performance visual stabilization reflexes after about 40 seconds of learning despite significant nonlinearities and processing delays in the system.
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Autonomous Motion Conference Paper Humanoid Robot DB Kotosaka, S., Shibata, T., Schaal, S. In Proceedings of the International Conference on Machine Automation (ICMA2000), 21-26, 2000, clmc BibTeX
Autonomous Motion Article Interaction of rhythmic and discrete pattern generators in single joint movements Sternad, D., Dean, W. J., Schaal, S. Human Movement Science, 19(4):627-665, 2000, clmc
The study investigates a single-joint movement task that combines a translatory and cyclic component with the objective to investigate the interaction of discrete and rhythmic movement elements. Participants performed an elbow movement in the horizontal plane, oscillating at a prescribed frequency around one target and shifting to a second target upon a trigger signal, without stopping the oscillation. Analyses focused on extracting the mutual influences of the rhythmic and the discrete component of the task. Major findings are: (1) The onset of the discrete movement was confined to a limited phase window in the rhythmic cycle. (2) Its duration was influenced by the period of oscillation. (3) The rhythmic oscillation was "perturbed" by the discrete movement as indicated by phase resetting. On the basis of these results we propose a model for the coordination of discrete and rhythmic actions (K. Matsuoka, Sustained oscillations generated by mutually inhibiting neurons with adaptations, Biological Cybernetics 52 (1985) 367-376; Mechanisms of frequency and pattern control in the neural rhythm generators, Biological Cybernetics 56 (1987) 345-353). For rhythmic movements an oscillatory pattern generator is developed following models of half-center oscillations (D. Bullock, S. Grossberg, The VITE model: a neural command circuit for generating arm and articulated trajectories, in: J.A.S. Kelso, A.J. Mandel, M. F. Shlesinger (Eds.), Dynamic Patterns in Complex Systems. World Scientific. Singapore. 1988. pp. 305-326). For discrete movements a point attractor dynamics is developed close to the VITE model For each joint degree of freedom both pattern generators co-exist but exert mutual inhibition onto each other. The suggested modeling framework provides a unified account for both discrete and rhythmic movements on the basis of neuronal circuitry. Simulation results demonstrated that the effects observed in human performance can be replicated using the two pattern generators with a mutually inhibiting coupling.
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Autonomous Motion Conference Paper Inverse kinematics for humanoid robots Tevatia, G., Schaal, S. In International Conference on Robotics and Automation (ICRA2000), 294-299, San Fransisco, April 24-28, 2000, 2000, clmc
Real-time control of the endeffector of a humanoid robot in external coordinates requires computationally efficient solutions of the inverse kinematics problem. In this context, this paper investigates methods of resolved motion rate control (RMRC) that employ optimization criteria to resolve kinematic redundancies. In particular we focus on two established techniques, the pseudo inverse with explicit optimization and the extended Jacobian method. We prove that the extended Jacobian method includes pseudo-inverse methods as a special solution. In terms of computational complexity, however, pseudo-inverse and extended Jacobian differ significantly in favor of pseudo-inverse methods. Employing numerical estimation techniques, we introduce a computationally efficient version of the extended Jacobian with performance comparable to the original version . Our results are illustrated in simulation studies with a multiple degree-of-freedom robot, and were tested on a 30 degree-of-freedom robot. 
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Physical Intelligence Article Investigation of Virtual Reality Interface for AFM-based Nano Manipulation Horiguchi, S., Sitti, M., Hashimoto, H. IEEJ Transactions on Electronics, Information and Systems, 120(12):1948-1956, The Institute of Electrical Engineers of Japan, 2000 BibTeX
Autonomous Motion Conference Paper Locally weighted projection regression: An O(n) algorithm for incremental real time learning in high dimensional spaces Vijayakumar, S., Schaal, S. In Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), 1:288-293, Stanford, CA, 2000, clmc
Locally weighted projection regression is a new algorithm that achieves nonlinear function approximation in high dimensional spaces with redundant and irrelevant input dimensions. At its core, it uses locally linear models, spanned by a small number of univariate regressions in selected directions in input space. This paper evaluates different methods of projection regression and derives a nonlinear function approximator based on them. This nonparametric local learning system i) learns rapidly with second order learning methods based on incremental training, ii) uses statistically sound stochastic cross validation to learn iii) adjusts its weighting kernels based on local information only, iv) has a computational complexity that is linear in the number of inputs, and v) can deal with a large number of - possibly redundant - inputs, as shown in evaluations with up to 50 dimensional data sets. To our knowledge, this is the first truly incremental spatially localized learning method to combine all these properties.
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Physical Intelligence Article Macro to Nano Tele-Manipulation Towards Nanoelectromec hanical Systems Sitti, M., Hashimoto, H. Journal of Robotics and Mechatronics, 12(3):209-217, FUJI TECHNOLOGY PRESS LTD., 2000 BibTeX
Autonomous Motion Conference Paper On-line learning for humanoid robot systems Conradt, J., Tevatia, G., Vijayakumar, S., Schaal, S. In Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), 1:191-198, Stanford, CA, 2000, clmc
Humanoid robots are high-dimensional movement systems for which analytical system identification and control methods are insufficient due to unknown nonlinearities in the system structure. As a way out, supervised learning methods can be employed to create model-based nonlinear controllers which use functions in the control loop that are estimated by learning algorithms. However, internal models for humanoid systems are rather high-dimensional such that conventional learning algorithms would suffer from slow learning speed, catastrophic interference, and the curse of dimensionality. In this paper we explore a new statistical learning algorithm, locally weighted projection regression (LWPR), for learning internal models in real-time. LWPR is a nonparametric spatially localized learning system that employs the less familiar technique of partial least squares regression to represent functional relationships in a piecewise linear fashion. The algorithm can work successfully in very high dimensional spaces and detect irrelevant and redundant inputs while only requiring a computational complexity that is linear in the number of input dimensions. We demonstrate the application of the algorithm in learning two classical internal models of robot control, the inverse kinematics and the inverse dynamics of an actual seven degree-of-freedom anthropomorphic robot arm. For both examples, LWPR can achieve excellent real-time learning results from less than one hour of actual training data.
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Theory of Inhomogeneous Condensed Matter Article Oxygen-related muon species in crystalline silicon Schefzik, M., Schimmele, L., Seeger, A., Herlach, D., Kormann, O., Major, J., Röck, A. Physica B, 289-290:521-524, 2000 BibTeX
Micro, Nano, and Molecular Systems Article Phenomenological damping in optical response tensors Buckingham, A., Fischer, P. PHYSICAL REVIEW A, 61(3), 2000
Although perturbation theory applied to the optical response of a molecule or material system is only strictly valid far from resonances, it is often applied to ``near-resonance{''} conditions by means of complex energies incorporating damping. Inconsistent signs of the damping in optical response tensors have appeared in the recent literature, as have errors in the treatment of the perturbation by a static held. The ``equal-sign{''} convention used in a recent publication yields an unphysical material response, and Koroteev's intimation that linear electro-optical circular dichroism may exist in an optically active liquid under resonance conditions is also flawed. We show that the isotropic part of the Pockels tensor vanishes.
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Theory of Inhomogeneous Condensed Matter Article Radio-frequency \muSR investigations on paramagnetic muonium centres in crystalline silicon Kormann, O., Major, J., Reid, I. D., Röck, A., Schefzik, M., Schimmele, L., Seeger, A., Herlach, D. Physica B, 289-290:530-533, 2000 BibTeX
Autonomous Motion Conference Paper Real-time robot learning with locally weighted statistical learning Schaal, S., Atkeson, C. G., Vijayakumar, S. In International Conference on Robotics and Automation (ICRA2000), San Francisco, April 2000, 2000, 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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Theory of Inhomogeneous Condensed Matter Ph.D. Thesis Selbst- und Fremddiffusion in amorphem Si28C36N36 und Si3N4 Matics, S. Universität Stuttgart, Stuttgart, 2000 URL BibTeX
Theory of Inhomogeneous Condensed Matter Article The interaction of positive muons with photogenerated charge carriers in crystalline silicon Scheuermann, R., Major, J., Seeger, A., Schimmele, L., Schmidl, J., Herlach, D. Physica B, 289-290:534-537, 2000 BibTeX
Micro, Nano, and Molecular Systems Article Three-wave mixing in chiral liquids Fischer, P., Wiersma, D., Righini, R., Champagne, B., Buckingham, A. PHYSICAL REVIEW LETTERS, 85(20):4253-4256, 2000
Second-order nonlinear optical frequency conversion in isotropic systems is only dipole allowed for sum- and difference-frequency generation in chiral media. We develop a single-center chiral model of the three-wave mixing (sum:frequency generation) nonlinearity and estimate its magnitude. We also report results from ab initio calculations and from three- and four-wave mixing experiments in support of the theoretical estimates. We show that the second-order susceptibility in chiral liquids is much smaller than previously thought.
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