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2010


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Learning, planning, and control for quadruped locomotion over challenging terrain

Kalakrishnan, M., Buchli, J., Pastor, P., Mistry, M., Schaal, S.

International Journal of Robotics Research, 30(2):236-258, 2010, clmc (article)

Abstract
We present a control architecture for fast quadruped locomotion over rough terrain. We approach the problem by decomposing it into many sub-systems, in which we apply state-of-the-art learning, planning, optimization, and control techniques to achieve robust, fast locomotion. Unique features of our control strategy include: (1) a system that learns optimal foothold choices from expert demonstration using terrain templates, (2) a body trajectory optimizer based on the Zero- Moment Point (ZMP) stability criterion, and (3) a floating-base inverse dynamics controller that, in conjunction with force control, allows for robust, compliant locomotion over unperceived obstacles. We evaluate the performance of our controller by testing it on the LittleDog quadruped robot, over a wide variety of rough terrains of varying difficulty levels. The terrain that the robot was tested on includes rocks, logs, steps, barriers, and gaps, with obstacle sizes up to the leg length of the robot. We demonstrate the generalization ability of this controller by presenting results from testing performed by an independent external test team on terrain that has never been shown to us.

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link (url) Project Page [BibTex]

2010


link (url) Project Page [BibTex]


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Teleoperated 3-D force feedback from the nanoscale with an atomic force microscope

Onal, C. D., Sitti, M.

IEEE Transactions on nanotechnology, 9(1):46-54, IEEE, 2010 (article)

pi

[BibTex]

[BibTex]


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Roll and pitch motion analysis of a biologically inspired quadruped water runner robot

Park, H. S., Floyd, S., Sitti, M.

The International Journal of Robotics Research, 29(10):1281-1297, SAGE Publications Sage UK: London, England, 2010 (article)

pi

[BibTex]

[BibTex]


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Microstructured elastomeric surfaces with reversible adhesion and examples of their use in deterministic assembly by transfer printing

Kim, Seok, Wu, Jian, Carlson, Andrew, Jin, Sung Hun, Kovalsky, Anton, Glass, Paul, Liu, Zhuangjian, Ahmed, Numair, Elgan, Steven L, Chen, Weiqiu, others

Proceedings of the National Academy of Sciences, 107(40):17095-17100, National Acad Sciences, 2010 (article)

pi

Project Page [BibTex]

Project Page [BibTex]


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Tankbot: A palm-size, tank-like climbing robot using soft elastomer adhesive treads

Unver, O., Sitti, M.

The International Journal of Robotics Research, 29(14):1761-1777, SAGE Publications Sage UK: London, England, 2010 (article)

pi

[BibTex]

[BibTex]


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Playful Machines: Tutorial

Der, R., Martius, G.

\urlhttp://robot.informatik.uni-leipzig.de/tutorial?lang=en, 2010 (misc)

al

[BibTex]

[BibTex]


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Entnetzung verspannter Filme

Reindl, A.

Universität Stuttgart, Stuttgart, 2010 (mastersthesis)

mms

[BibTex]

[BibTex]


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Advanced ferromagnetic nanostructures

Goll, D.

Universität Stuttgart, Stuttgart, 2010 (phdthesis)

mms

[BibTex]

[BibTex]


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Wasserstoff in funktionellen Dünnschichtsystemen

Honert, J.

Universität Stuttgart, Stuttgart, 2010 (mastersthesis)

mms

[BibTex]

[BibTex]


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Hydrogen spillover measurements of unbridged and bridged metal-organic frameworks - revisited

Campesi, R., Cuevas, F., Latroche, M., Hirscher, M.

{Physical Chemistry Chemical Physics}, 12, pages: 10457-10459, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Relating Gilbert damping and ultrafast laser-induced demagnetization

Fähnle, M., Seib, J., Illg, C.

{Physical Review B}, 82, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Ferromagnetic properties of the Mn-doped nanograined ZnO films

Straumal, B. B., Protasova, S. G., Mazilkin, A. A., Myatiev, A. A., Straumal, P. B., Schütz, G., Goering, E., Baretzky, B.

{Journal of Applied Physics}, 108, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Unusual super-ductility at room temperature in an ultrafine-grained aluminum alloy

Valiev, R. Z., Murashkin, M. Y., Kilmametov, A., Straumal, B., Chinh, N. Q., Langdon, T.

In 45, pages: 4718-4724, Seattle, WA, USA, 2010 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


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Demagnetization on the fs time-scale by the Elliott-Yafet mechanism

Steiauf, D., Illg, C., Fähnle, M.

In 200, Karlsruhe, Germany, 2010 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


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Ubiquity of ferromagnetic signals in common diamagnetic oxide crystals

Khalid, M., Setzer, A., Ziese, M., Esquinazi, P., Spemann, D., Pöppl, A., Goering, E.

{Physical Review B}, 81(21), 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Calculation of the Gilbert damping matrix at low scattering rates in Gd

Seib, J., Fähnle, M.

{Physical Review B}, 82, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Adsorption technologies

Schmitz, B., Hirscher, M.

In Hydrogen and Fuel Cells, pages: 431-445, WILEY-VCH, Weinheim, 2010 (incollection)

mms

[BibTex]

[BibTex]


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Swift heavy ions for controlled modification of soft magnetic properties of Fe0.85N0.15 thin film

Gupta, R., Gupta, A., Bhatt, R., Rüffer, R., Avasthi, D. K.

{Journal of Physics: Condensed Matter}, 22(22), 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Constrained Accelerations for Controlled Geometric Reduction: Sagittal-Plane Decoupling for Bipedal Locomotion

Gregg, R., Righetti, L., Buchli, J., Schaal, S.

In 2010 10th IEEE-RAS International Conference on Humanoid Robots, pages: 1-7, IEEE, Nashville, USA, 2010 (inproceedings)

Abstract
Energy-shaping control methods have produced strong theoretical results for asymptotically stable 3D bipedal dynamic walking in the literature. In particular, geometric controlled reduction exploits robot symmetries to control momentum conservation laws that decouple the sagittal-plane dynamics, which are easier to stabilize. However, the associated control laws require high-dimensional matrix inverses multiplied with complicated energy-shaping terms, often making these control theories difficult to apply to highly-redundant humanoid robots. This paper presents a first step towards the application of energy-shaping methods on real robots by casting controlled reduction into a framework of constrained accelerations for inverse dynamics control. By representing momentum conservation laws as constraints in acceleration space, we construct a general expression for desired joint accelerations that render the constraint surface invariant. By appropriately choosing an orthogonal projection, we show that the unconstrained (reduced) dynamics are decoupled from the constrained dynamics. Any acceleration-based controller can then be used to stabilize this planar subsystem, including passivity-based methods. The resulting control law is surprisingly simple and represents a practical way to employ control theoretic stability results in robotic platforms. Simulated walking of a 3D compass-gait biped show correspondence between the new and original controllers, and simulated motions of a 16-DOF humanoid demonstrate the applicability of this method.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Variable impedance control - a reinforcement learning approach

Buchli, J., Theodorou, E., Stulp, F., Schaal, S.

In Robotics Science and Systems (2010), Zaragoza, Spain, June 27-30, 2010, clmc (inproceedings)

Abstract
One of the hallmarks of the performance, versatility, and robustness of biological motor control is the ability to adapt the impedance of the overall biomechanical system to different task requirements and stochastic disturbances. A transfer of this principle to robotics is desirable, for instance to enable robots to work robustly and safely in everyday human environments. It is, however, not trivial to derive variable impedance controllers for practical high DOF robotic tasks. In this contribution, we accomplish such gain scheduling with a reinforcement learning approach algorithm, PI2 (Policy Improvement with Path Integrals). PI2 is a model-free, sampling based learning method derived from first principles of optimal control. The PI2 algorithm requires no tuning of algorithmic parameters besides the exploration noise. The designer can thus fully focus on cost function design to specify the task. From the viewpoint of robotics, a particular useful property of PI2 is that it can scale to problems of many DOFs, so that RL on real robotic systems becomes feasible. We sketch the PI2 algorithm and its theoretical properties, and how it is applied to gain scheduling. We evaluate our approach by presenting results on two different simulated robotic systems, a 3-DOF Phantom Premium Robot and a 6-DOF Kuka Lightweight Robot. We investigate tasks where the optimal strategy requires both tuning of the impedance of the end-effector, and tuning of a reference trajectory. The results show that we can use path integral based RL not only for planning but also to derive variable gain feedback controllers in realistic scenarios. Thus, the power of variable impedance control is made available to a wide variety of robotic systems and practical applications.

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link (url) [BibTex]

link (url) [BibTex]


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Note: Aligned deposition and modal characterization of micron and submicron poly (methyl methacyrlate) fiber cantilevers

Nain, A. S., Filiz, S., Burak Ozdoganlar, O., Sitti, M., Amon, C.

Review of Scientific Instruments, 81(1):016102, AIP, 2010 (article)

pi

[BibTex]

[BibTex]


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Surface tension driven water strider robot using circular footpads

Ozcan, O., Wang, H., Taylor, J. D., Sitti, M.

In Robotics and Automation (ICRA), 2010 IEEE International Conference on, pages: 3799-3804, 2010 (inproceedings)

pi

[BibTex]

[BibTex]


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Atomic-Force-Microscopy-Based Nanomanipulation Systems

Onal, C. D., Ozcan, O., Sitti, M.

In Handbook of Nanophysics: Nanomedicine and Nanorobotics, pages: 1-15, CRC Press, 2010 (incollection)

pi

[BibTex]

[BibTex]


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Enhanced adhesion of dopamine methacrylamide elastomers via viscoelasticity tuning

Chung, H., Glass, P., Pothen, J. M., Sitti, M., Washburn, N. R.

Biomacromolecules, 12(2):342-347, American Chemical Society, 2010 (article)

pi

Project Page [BibTex]

Project Page [BibTex]


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Taming the Beast: Guided Self-organization of Behavior in Autonomous Robots

Martius, G., Herrmann, J. M.

In From Animals to Animats 11, 6226, pages: 50-61, LNCS, Springer, 2010 (incollection)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Inverse dynamics with optimal distribution of ground reaction forces for legged robot

Righetti, L., Buchli, J., Mistry, M., Schaal, S.

In Proceedings of the 13th International Conference on Climbing and Walking Robots (CLAWAR), pages: 580-587, Nagoya, Japan, sep 2010 (inproceedings)

Abstract
Contact interaction with the environment is crucial in the design of locomotion controllers for legged robots, to prevent slipping for example. Therefore, it is of great importance to be able to control the effects of the robots movements on the contact reaction forces. In this contribution, we extend a recent inverse dynamics algorithm for floating base robots to optimize the distribution of contact forces while achieving precise trajectory tracking. The resulting controller is algorithmically simple as compared to other approaches. Numerical simulations show that this result significantly increases the range of possible movements of a humanoid robot as compared to the previous inverse dynamics algorithm. We also present a simplification of the result where no inversion of the inertia matrix is needed which is particularly relevant for practical use on a real robot. Such an algorithm becomes interesting for agile locomotion of robots on difficult terrains where the contacts with the environment are critical, such as walking over rough or slippery terrain.

am mg

DOI [BibTex]

DOI [BibTex]


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Laterally driven interfaces in the three-dimensional Ising lattice gas

Smith, T. H. R., Vasilyev, O., Maciolek, A., Schmidt, M.

{Physical Review E}, 82(2), 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Handbook of Hydrogen Storage

Hirscher, M.

pages: 353 p., Wiley-VCH, Weinheim, 2010 (book)

mms

[BibTex]

[BibTex]


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Samarium-cobalt 2:17 magnets: identifying Smn+1Co5n-1 phases stabilized by Zr

Stadelmaier, H. H., Kronmüller, H., Goll, D.

{Scripta Materialia}, 63, pages: 843-846, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Planar metamaterial analogue of electromagnetically induced transparancy for plasmonic sensing

Liu, N., Weiss, T., Mesch, M., Langguth, L., Eigenthaler, U., Hirscher, M., Sönnichsen, C., Giessen, H.

{Nano Letters}, 10, pages: 1103-1107, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Explaining the paradoxical diversity of ultrafast last-induced demagnetization

Koopmans, B., Malinowski, G., Dalla Longa, F., Steiauf, D., Fähnle, M., Roth, T., Cinchetti, M., Aeschlimann, M.

{Nature Materials}, 9, pages: 259-265, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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A high heat of adsorption for hydrogen in magnesium formate

Schmitz, B., Krkljus, I., Leung, E., Höffken, H. W., Müller, U., Hirscher, M.

{ChemSusChem}, 3, pages: 758-761, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Force induced destabilization of adhesion complexes at defined integrin spacings on nanostructured surfaces

de Beer, A. G. F., Cavalcanti-Adam, E. A., Majer, G., López-Garc\’\ia, M., Kessler, H., Spatz, J. P.

{Physical Review E}, 81, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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The X-ray microscopy beamline UE46-PGM2 at BESSY

Follath, R., Schmidt, J. S., Weigand, M., Fauth, K.

In 10th International Conference on Synchrotron Radiation Instrumentation, 1234, pages: 323-326, AIP Conference Proceedings, American Institute of Physics, Melbourne, Australia, 2010 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


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Anisotropic damping of the magnetization dynamics in Ni, Co, and Fe

Gilmore, K., Stiles, M. D., Seib, J., Steiauf, D., Fähnle, M.

{Physical Review B}, 81, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Influence of [Mo6Br8F6]2- cluster inclusion within the mesoporous solid MIL-101 on hydrogen storage performance

Dybtsev, D., Serre, C., Schmitz, B., Panella, B., Hirscher, M., Latroche, M., Llewellyn, P. L., Cordier, S., Molard, Y., Haouas, M., Taulelle, F., Férey, G.

{Langmuir}, 26(13):11283-11290, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Grain boundary layers in nanocrystalline ferromagnetic zinc oxide

Straumal, B. B., Myatiev, A. A., Straumal, P. B., Mazilkin, A. A., Protasova, S. G., Goering, E., Baretzky, B.

{JETP Letters}, 92(6):396-400, 2010 (article)

mms

DOI [BibTex]

DOI [BibTex]

2005


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Kernel Methods for Measuring Independence

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

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

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

ei

PDF PostScript PDF [BibTex]

2005


PDF PostScript PDF [BibTex]


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Kernel ICA for Large Scale Problems

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

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

ei

Web [BibTex]

Web [BibTex]


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Some thoughts about Gaussian Processes

Chapelle, O.

NIPS Workshop on Open Problems in Gaussian Processes for Machine Learning, December 2005 (talk)

ei

PDF Web [BibTex]

PDF Web [BibTex]


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A Unifying View of Sparse Approximate Gaussian Process Regression

Quinonero Candela, J., Rasmussen, C.

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

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

ei

PDF [BibTex]

PDF [BibTex]


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Popper, Falsification and the VC-dimension

Corfield, D., Schölkopf, B., Vapnik, V.

(145), Max Planck Institute for Biological Cybernetics, November 2005 (techreport)

ei

PDF [BibTex]

PDF [BibTex]


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Extension to Kernel Dependency Estimation with Applications to Robotics

BakIr, G.

Biologische Kybernetik, Technische Universität Berlin, Berlin, November 2005 (phdthesis)

Abstract
Kernel Dependency Estimation(KDE) is a novel technique which was designed to learn mappings between sets without making assumptions on the type of the involved input and output data. It learns the mapping in two stages. In a first step, it tries to estimate coordinates of a feature space representation of elements of the set by solving a high dimensional multivariate regression problem in feature space. Following this, it tries to reconstruct the original representation given the estimated coordinates. This thesis introduces various algorithmic extensions to both stages in KDE. One of the contributions of this thesis is to propose a novel linear regression algorithm that explores low-dimensional subspaces during learning. Furthermore various existing strategies for reconstructing patterns from feature maps involved in KDE are discussed and novel pre-image techniques are introduced. In particular, pre-image techniques for data-types that are of discrete nature such as graphs and strings are investigated. KDE is then explored in the context of robot pose imitation where the input is a an image with a human operator and the output is the robot articulated variables. Thus, using KDE, robot pose imitation is formulated as a regression problem.

ei

PDF PDF [BibTex]

PDF PDF [BibTex]


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Kernel methods for dependence testing in LFP-MUA

Gretton, A., Belitski, A., Murayama, Y., Schölkopf, B., Logothetis, N.

35(689.17), 35th Annual Meeting of the Society for Neuroscience (Neuroscience), November 2005 (poster)

Abstract
A fundamental problem in neuroscience is determining whether or not particular neural signals are dependent. The correlation is the most straightforward basis for such tests, but considerable work also focuses on the mutual information (MI), which is capable of revealing dependence of higher orders that the correlation cannot detect. That said, there are other measures of dependence that share with the MI an ability to detect dependence of any order, but which can be easier to compute in practice. We focus in particular on tests based on the functional covariance, which derive from work originally accomplished in 1959 by Renyi. Conceptually, our dependence tests work by computing the covariance between (infinite dimensional) vectors of nonlinear mappings of the observations being tested, and then determining whether this covariance is zero - we call this measure the constrained covariance (COCO). When these vectors are members of universal reproducing kernel Hilbert spaces, we can prove this covariance to be zero only when the variables being tested are independent. The greatest advantage of these tests, compared with the mutual information, is their simplicity – when comparing two signals, we need only take the largest eigenvalue (or the trace) of a product of two matrices of nonlinearities, where these matrices are generally much smaller than the number of observations (and are very simple to construct). We compare the mutual information, the COCO, and the correlation in the context of finding changes in dependence between the LFP and MUA signals in the primary visual cortex of the anaesthetized macaque, during the presentation of dynamic natural stimuli. We demonstrate that the MI and COCO reveal dependence which is not detected by the correlation alone (which we prove by artificially removing all correlation between the signals, and then testing their dependence with COCO and the MI); and that COCO and the MI give results consistent with each other on our data.

ei

Web [BibTex]

Web [BibTex]


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Training Support Vector Machines with Multiple Equality Constraints

Kienzle, W., Schölkopf, B.

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

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

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Geometrical aspects of statistical learning theory

Hein, M.

Biologische Kybernetik, Darmstadt, Darmstadt, November 2005 (phdthesis)

ei

PDF [BibTex]

PDF [BibTex]


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Measuring Statistical Dependence with Hilbert-Schmidt Norms

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

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

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

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Maximal Margin Classification for Metric Spaces

Hein, M., Bousquet, O., Schölkopf, B.

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

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

ei

PDF PDF DOI [BibTex]

PDF PDF DOI [BibTex]


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

Kowalczyk, A., Chapelle, O.

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

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

ei

PDF [BibTex]

PDF [BibTex]