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2011


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High contrast magnetic and nonmagnetic sample current microscopy for bulk and transparent samples using soft X-rays

Nolle, D., Weigand, M., Schütz, G., Goering, E.

{Microscopy and Microanalysis}, 17, pages: 834-842, 2011 (article)

mms

DOI [BibTex]

2011


DOI [BibTex]


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Magnetic vortex core reversal by rotating magnetic fields generated on micrometer length scales

Curcic, M., Stoll, H., Weigand, M., Sackmann, V., Jüllig, P., Kammerer, M., Noske, M., Sproll, M., Van Waeyenberge, B., Vansteenkiste, A., Woltersdorf, G., Tyliszczak, T., Schütz, G.

{Physica Status Solidi B}, 248(10):2317-2322, 2011 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Operational Space Control of Constrained and Underactuated Systems

Mistry, M., Righetti, L.

In Proceedings of Robotics: Science and Systems, Los Angeles, CA, USA, June 2011 (inproceedings)

Abstract
The operational space formulation (Khatib, 1987), applied to rigid-body manipulators, describes how to decouple task-space and null-space dynamics, and write control equations that correspond only to forces at the end-effector or, alternatively, only to motion within the null-space. We would like to apply this useful theory to modern humanoids and other legged systems, for manipulation or similar tasks, however these systems present additional challenges due to their underactuated floating bases and contact states that can dynamically change. In recent work, Sentis et al. derived controllers for such systems by implementing a task Jacobian projected into a space consistent with the supporting constraints and underactuation (the so called "support consistent reduced Jacobian"). Here, we take a new approach to derive operational space controllers for constrained underactuated systems, by first considering the operational space dynamics within "projected inverse-dynamics" (Aghili, 2005), and subsequently resolving underactuation through the addition of dynamically consistent control torques. Doing so results in a simplified control solution compared with previous results, and importantly yields several new insights into the underlying problem of operational space control in constrained environments: 1) Underactuated systems, such as humanoid robots, cannot in general completely decouple task and null-space dynamics. However, 2) there may exist an infinite number of control solutions to realize desired task-space dynamics, and 3) these solutions involve the addition of dynamically consistent null-space motion or constraint forces (or combinations of both). In light of these findings, we present several possible control solutions, with varying optimization criteria, and highlight some of their practical consequences.

mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Nanomechanics of AFM based nanomanipulation

Xie, H., Onal, C., Régnier, S., Sitti, M.

In Atomic Force Microscopy Based Nanorobotics, pages: 87-143, Springer Berlin Heidelberg, 2011 (incollection)

pi

[BibTex]

[BibTex]


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Under-actuated tank-like climbing robot with various transitioning capabilities

Seo, T., Sitti, M.

In Robotics and Automation (ICRA), 2011 IEEE International Conference on, pages: 777-782, 2011 (inproceedings)

pi

[BibTex]

[BibTex]


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Enhancing adhesion of biologically inspired polymer microfibers with a viscous oil coating

Cheung, E., Sitti, M.

The Journal of Adhesion, 87(6):547-557, Taylor & Francis Group, 2011 (article)

pi

Project Page [BibTex]

Project Page [BibTex]


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Rotating magnetic micro-robots for versatile non-contact fluidic manipulation of micro-objects

Diller, E., Ye, Z., Sitti, M.

In Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, pages: 1291-1296, 2011 (inproceedings)

pi

Project Page [BibTex]

Project Page [BibTex]


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Formation of two amorphous phases in the Ni60Nb18Y22 alloy after high pressure torsion

Straumal, B. B., Mazilkin, A. A., Protasova, S. G., Goll, D., Baretzky, B., Bakai, A. S., Dobatkin, S. V.

{Kovove Materialy-Metallic Materials}, 49(1):17-22, 2011 (article)

mms

link (url) [BibTex]

link (url) [BibTex]


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Structure and properties of nanograined Fe-C alloys after severe plastic deformation

Straumal, B. B., Dobatkin, S. V., Rodin, A. O., Protasova, S. G., Mazilkin, A. A., Goll, D., Baretzky, B.

{Advanced Engineering Materials}, 13(6):463-469, 2011 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Increased flux pinning in YBa2Cu3O7-δthin-film devices through embedding of Au nano crystals

Katzer, C., Schmidt, M., Michalowski, P., Kuhwald, D., Schmidl, F., Grosse, V., Treiber, S., Stahl, C., Albrecht, J., Hübner, U., Undisz, A., Rettenmayr, M., Schütz, G., Seidel, P.

{Europhysics Letters}, 95(6), 2011 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Signal transfer in a chain of stray-field coupled ferromagnetic squares

Vogel, A., Martens, M., Weigand, M., Meier, G.

{Applied Physics Letters}, 99, 2011 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Transmission electron microscopy investigation of boundaries between amorphous "grains" in Ni50Nb20Y30 alloy

Mazilkin, A. A., Abrosimova, G. E., Protasova, S. G., Straumal, B. B., Schütz, G., Dobatkin, S. V., Bakai, A. S.

In 46, pages: 4336-4342, Mie, Japan, 2011 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


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Electron theory of magnetoelectric effects in metallic ferromagnetic nanostructures

Subkow, S., Fähnle, M.

{Physical Review B}, 84, 2011 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Magnetic antivortex-core reversal by rotating magnetic fields

Kamionka, T., Martens, M., Chou, K., Drews, A., Tyliszczak, T., Stoll, H., Van Waeyenberge, B., Meier, G.

{Physical Review B}, 83, 2011 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Magnetic properties of exchange-spring composite films

Kronmüller, H., Goll, D.

{Physica Status Solidi B}, 248(10):2361-2367, 2011 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Wetting transition of grain boundaries in the Sn-rich part of the Sn-Bi phase diagram

Yeh, C.-H., Chang, L.-S., Straumal, B. B.

{Journal of Materials Science}, 46(5):1557-1562, 2011 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Online movement adaptation based on previous sensor experiences

Pastor, P., Righetti, L., Kalakrishnan, M., Schaal, S.

In 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages: 365-371, IEEE, San Francisco, USA, sep 2011 (inproceedings)

Abstract
Personal robots can only become widespread if they are capable of safely operating among humans. In uncertain and highly dynamic environments such as human households, robots need to be able to instantly adapt their behavior to unforseen events. In this paper, we propose a general framework to achieve very contact-reactive motions for robotic grasping and manipulation. Associating stereotypical movements to particular tasks enables our system to use previous sensor experiences as a predictive model for subsequent task executions. We use dynamical systems, named Dynamic Movement Primitives (DMPs), to learn goal-directed behaviors from demonstration. We exploit their dynamic properties by coupling them with the measured and predicted sensor traces. This feedback loop allows for online adaptation of the movement plan. Our system can create a rich set of possible motions that account for external perturbations and perception uncertainty to generate truly robust behaviors. As an example, we present an application to grasping with the WAM robot arm.

am mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Learning to grasp under uncertainty

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

In Robotics and Automation (ICRA), 2011 IEEE International Conference on, Shanghai, China, May 9-13, 2011, clmc (inproceedings)

Abstract
We present an approach that enables robots to learn motion primitives that are robust towards state estimation uncertainties. During reaching and preshaping, the robot learns to use fine manipulation strategies to maneuver the object into a pose at which closing the hand to perform the grasp is more likely to succeed. In contrast, common assumptions in grasp planning and motion planning for reaching are that these tasks can be performed independently, and that the robot has perfect knowledge of the pose of the objects in the environment. We implement our approach using Dynamic Movement Primitives and the probabilistic model-free reinforcement learning algorithm Policy Improvement with Path Integrals (PI2 ). The cost function that PI2 optimizes is a simple boolean that penalizes failed grasps. The key to acquiring robust motion primitives is to sample the actual pose of the object from a distribution that represents the state estimation uncertainty. During learning, the robot will thus optimize the chance of grasping an object from this distribution, rather than at one specific pose. In our empirical evaluation, we demonstrate how the motion primitives become more robust when grasping simple cylindrical objects, as well as more complex, non-convex objects. We also investigate how well the learned motion primitives generalize towards new object positions and other state estimation uncertainty distributions.

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link (url) [BibTex]

link (url) [BibTex]


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Instrumentation Issues of an AFM Based Nanorobotic System

Xie, H., Onal, C., Régnier, S., Sitti, M.

In Atomic Force Microscopy Based Nanorobotics, pages: 31-86, Springer Berlin Heidelberg, 2011 (incollection)

pi

[BibTex]

[BibTex]


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Piezoelectric polymer fiber arrays for tactile sensing applications

Sümer, B., Aksak, B., Şsahin, K., Chuengsatiansup, K., Sitti, M.

Sensor Letters, 9(2):457-463, American Scientific Publishers, 2011 (article)

pi

Project Page [BibTex]

Project Page [BibTex]


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Assembly and disassembly of magnetic mobile micro-robots towards deterministic 2-D reconfigurable micro-systems

Pawashe, C., Diller, E., Floyd, S., Sitti, M.

In Robotics and Automation (ICRA), 2011 IEEE International Conference on, pages: 261-266, 2011 (inproceedings)

pi

[BibTex]

[BibTex]


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Stochastic dynamics of bacteria propelled spherical micro-robots

Arabagi, V., Behkam, B., Sitti, M.

In Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on, pages: 3937-3942, 2011 (inproceedings)

pi

[BibTex]

[BibTex]


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Control methodologies for a heterogeneous group of untethered magnetic micro-robots

Floyd, S., Diller, E., Pawashe, C., Sitti, M.

The International Journal of Robotics Research, 30(13):1553-1565, SAGE Publications, 2011 (article)

pi

[BibTex]

[BibTex]


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Projected Newton-type methods in machine learning

Schmidt, M., Kim, D., Sra, S.

In Optimization for Machine Learning, pages: 305-330, MIT Press, Cambridge, MA, USA, 2011 (incollection)

Abstract
{We consider projected Newton-type methods for solving large-scale optimization problems arising in machine learning and related fields. We first introduce an algorithmic framework for projected Newton-type methods by reviewing a canonical projected (quasi-)Newton method. This method, while conceptually pleasing, has a high computation cost per iteration. Thus, we discuss two variants that are more scalable, namely, two-metric projection and inexact projection methods. Finally, we show how to apply the Newton-type framework to handle non-smooth objectives. Examples are provided throughout the chapter to illustrate machine learning applications of our framework.}

mms

link (url) [BibTex]

link (url) [BibTex]


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Study of krypton/xenon storage and separation in microporous frameworks

Soleimani Dorcheh, A.

Universität Darmstadt, Darmstadt, 2011 (mastersthesis)

mms

[BibTex]

[BibTex]


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Influence of dot size and annealing on the magnetic properties of large-area L10-FePt nanopatterns

Bublat, T., Goll, D.

{Journal of Applied Physics}, 110(7), 2011 (article)

mms

DOI [BibTex]


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The temperature-dependent magnetization profile across an epitaxial bilayer of ferromagnetic La2/3Ca1/3MnO3 and superconducting YBa2Cu3O7-δ

Brück, S., Treiber, S., Macke, S., Audehm, P., Christiani, G., Soltan, S., Habermeier, H., Goering, E., Albrecht, J.

{New Journal of Physics}, 13(3), 2011 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Spin interactions in bcc and fcc Fe beyond the Heisenberg model

Singer, R., Dietermann, F., Fähnle, M.

{Physical Review Letters}, 107, 2011 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Route to a family of robust, non-interpenetrated metal-organic frameworks with pto-like topology

Klein, N., Senkovska, I., Baburin, I. A., Grünker, R., Stoeck, U., Schlichtenmayer, M., Streppel, B., Mueller, U., Leoni, S., Hirscher, M., Kaskel, S.

{Chemistry - A European Journal}, 17(46):13007-13016, 2011 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Initial stages of growth of iron on silicon for spin injection through Schottky barrier

Dash, S. P., Carstanjen, H. D.

{Physica Status Solidi B}, 248(10):2300-2304, 2011 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Fe3O4/ZnO: A high-quality magnetic oxide-semiconductor heterostructure by reactive deposition

Paul, M., Kufer, D., Müller, A., Brück, S., Goering, E., Kamp, M., Verbeeck, J., Tian, H., Van Tendeloo, G., Ingle, N. J. C., Sing, M., Claessen, R.

{Applied Physics Letters}, 98, 2011 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Influence of texture on the ferromagnetic properties of nanograined ZnO films

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

{Physica Status Solidi B}, 248(7):1581-1586, 2011 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Control of spin configuration in half-metallic La0.7Sr0.3MnO3 nano-structures

Rhensius, J., Vaz, C. A. F., Bisig, A., Schweitzer, S., Heidler, J., Körner, H. S., Locatelli, A., Niño, M. A., Weigand, M., Méchin, L., Gaucher, F., Goering, E., Heyderman, L. J., Kläui, M.

{Applied Physics Letters}, 99(6), 2011 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Comparison of various sol-gel derived metal oxide layers for inverted organic solar cells

Oh, H., Krantz, J., Litzov, I., Stubhan, T., Pinna, L., Brabec, C. J.

{Solar Energy Materials \& Solar Cells}, 95(8):2194-2199, 2011 (article)

mms

DOI [BibTex]

DOI [BibTex]

2009


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Learning an Interactive Segmentation System

Nickisch, H., Kohli, P., Rother, C.

Max Planck Institute for Biological Cybernetics, December 2009 (techreport)

Abstract
Many successful applications of computer vision to image or video manipulation are interactive by nature. However, parameters of such systems are often trained neglecting the user. Traditionally, interactive systems have been treated in the same manner as their fully automatic counterparts. Their performance is evaluated by computing the accuracy of their solutions under some fixed set of user interactions. This paper proposes a new evaluation and learning method which brings the user in the loop. It is based on the use of an active robot user - a simulated model of a human user. We show how this approach can be used to evaluate and learn parameters of state-of-the-art interactive segmentation systems. We also show how simulated user models can be integrated into the popular max-margin method for parameter learning and propose an algorithm to solve the resulting optimisation problem.

ei

Web [BibTex]

2009


Web [BibTex]


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Machine Learning for Brain-Computer Interfaces

Hill, NJ.

Mini-Symposia on Assistive Machine Learning for People with Disabilities at NIPS (AMD), December 2009 (talk)

Abstract
Brain-computer interfaces (BCI) aim to be the ultimate in assistive technology: decoding a user‘s intentions directly from brain signals without involving any muscles or peripheral nerves. Thus, some classes of BCI potentially offer hope for users with even the most extreme cases of paralysis, such as in late-stage Amyotrophic Lateral Sclerosis, where nothing else currently allows communication of any kind. Other lines in BCI research aim to restore lost motor function in as natural a way as possible, reconnecting and in some cases re-training motor-cortical areas to control prosthetic, or previously paretic, limbs. Research and development are progressing on both invasive and non-invasive fronts, although BCI has yet to make a breakthrough to widespread clinical application. The high-noise high-dimensional nature of brain-signals, particularly in non-invasive approaches and in patient populations, make robust decoding techniques a necessity. Generally, the approach has been to use relatively simple feature extraction techniques, such as template matching and band-power estimation, coupled to simple linear classifiers. This has led to a prevailing view among applied BCI researchers that (sophisticated) machine-learning is irrelevant since "it doesn‘t matter what classifier you use once you‘ve done your preprocessing right and extracted the right features." I shall show a few examples of how this runs counter to both the empirical reality and the spirit of what needs to be done to bring BCI into clinical application. Along the way I‘ll highlight some of the interesting problems that remain open for machine-learners.

ei

PDF Web Web [BibTex]

PDF Web Web [BibTex]


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Efficient Subwindow Search: A Branch and Bound Framework for Object Localization

Lampert, C., Blaschko, M., Hofmann, T.

IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(12):2129-2142, December 2009 (article)

Abstract
Most successful object recognition systems rely on binary classification, deciding only if an object is present or not, but not providing information on the actual object location. To estimate the object‘s location, one can take a sliding window approach, but this strongly increases the computational cost because the classifier or similarity function has to be evaluated over a large set of candidate subwindows. In this paper, we propose a simple yet powerful branch and bound scheme that allows efficient maximization of a large class of quality functions over all possible subimages. It converges to a globally optimal solution typically in linear or even sublinear time, in contrast to the quadratic scaling of exhaustive or sliding window search. We show how our method is applicable to different object detection and image retrieval scenarios. The achieved speedup allows the use of classifiers for localization that formerly were considered too slow for this task, such as SVMs with a spatial pyramid kernel or nearest-neighbor classifiers based on the chi^2 distance. We demonstrate state-of-the-art localization performance of the resulting systems on the UIUC Cars data set, the PASCAL VOC 2006 data set, and in the PASCAL VOC 2007 competition.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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A computational model of human table tennis for robot application

Mülling, K., Peters, J.

In AMS 2009, pages: 57-64, (Editors: Dillmann, R. , J. Beyerer, C. Stiller, M. Zöllner, T. Gindele), Springer, Berlin, Germany, Autonome Mobile Systeme, December 2009 (inproceedings)

Abstract
Table tennis is a difficult motor skill which requires all basic components of a general motor skill learning system. In order to get a step closer to such a generic approach to the automatic acquisition and refinement of table tennis, we study table tennis from a human motor control point of view. We make use of the basic models of discrete human movement phases, virtual hitting points, and the operational timing hypothesis. Using these components, we create a computational model which is aimed at reproducing human-like behavior. We verify the functionality of this model in a physically realistic simulation of a BarrettWAM.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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PAC-Bayesian Approach to Formulation of Clustering Objectives

Seldin, Y.

NIPS Workshop on "Clustering: Science or Art? Towards Principled Approaches", December 2009 (talk)

Abstract
Clustering is a widely used tool for exploratory data analysis. However, the theoretical understanding of clustering is very limited. We still do not have a well-founded answer to the seemingly simple question of "how many clusters are present in the data?", and furthermore a formal comparison of clusterings based on different optimization objectives is far beyond our abilities. The lack of good theoretical support gives rise to multiple heuristics that confuse the practitioners and stall development of the field. We suggest that the ill-posed nature of clustering problems is caused by the fact that clustering is often taken out of its subsequent application context. We argue that one does not cluster the data just for the sake of clustering it, but rather to facilitate the solution of some higher level task. By evaluation of the clustering‘s contribution to the solution of the higher level task it is possible to compare different clusterings, even those obtained by different optimization objectives. In the preceding work it was shown that such an approach can be applied to evaluation and design of co-clustering solutions. Here we suggest that this approach can be extended to other settings, where clustering is applied.

ei

PDF Web Web [BibTex]

PDF Web Web [BibTex]


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Generation of three-dimensional random rotations in fitting and matching problems

Habeck, M.

Computational Statistics, 24(4):719-731, December 2009 (article)

Abstract
An algorithm is developed to generate random rotations in three-dimensional space that follow a probability distribution arising in fitting and matching problems. The rotation matrices are orthogonally transformed into an optimal basis and then parameterized using Euler angles. The conditional distributions of the three Euler angles have a very simple form: the two azimuthal angles can be decoupled by sampling their sum and difference from a von Mises distribution; the cosine of the polar angle is exponentially distributed and thus straighforward to generate. Simulation results are shown and demonstrate the effectiveness of the method. The algorithm is compared to other methods for generating random rotations such as a random walk Metropolis scheme and a Gibbs sampling algorithm recently introduced by Green and Mardia. Finally, the algorithm is applied to a probabilistic version of the Procrustes problem of fitting two point sets and applied in the context of protein structure superposition.

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Semi-supervised Kernel Canonical Correlation Analysis of Human Functional Magnetic Resonance Imaging Data

Shelton, JA.

Women in Machine Learning Workshop (WiML), December 2009 (talk)

Abstract
Kernel Canonical Correlation Analysis (KCCA) is a general technique for subspace learning that incorporates principal components analysis (PCA) and Fisher linear discriminant analysis (LDA) as special cases. By finding directions that maximize correlation, KCCA learns representations tied more closely to underlying process generating the the data and can ignore high-variance noise directions. However, for data where acquisition in a given modality is expensive or otherwise limited, KCCA may suffer from small sample effects. We propose to use semi-supervised Laplacian regularization to utilize data that are present in only one modality. This manifold learning approach is able to find highly correlated directions that also lie along the data manifold, resulting in a more robust estimate of correlated subspaces. Functional magnetic resonance imaging (fMRI) acquired data are naturally amenable to subspace techniques as data are well aligned and such data of the human brain are a particularly interesting candidate. In this study we implemented various supervised and semi-supervised versions of KCCA on human fMRI data, with regression to single and multivariate labels (corresponding to video content subjects viewed during the image acquisition). In each variate condition, Laplacian regularization improved performance whereas the semi-supervised variants of KCCA yielded the best performance. We additionally analyze the weights learned by the regression in order to infer brain regions that are important during different types of visual processing.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Adaptive Importance Sampling for Value Function Approximation in Off-policy Reinforcement Learning

Hachiya, H., Akiyama, T., Sugiyama, M., Peters, J.

Neural Networks, 22(10):1399-1410, December 2009 (article)

Abstract
Off-policy reinforcement learning is aimed at efficiently using data samples gathered from a policy that is different from the currently optimized policy. A common approach is to use importance sampling techniques for compensating for the bias of value function estimators caused by the difference between the data-sampling policy and the target policy. However, existing off-policy methods often do not take the variance of the value function estimators explicitly into account and therefore their performance tends to be unstable. To cope with this problem, we propose using an adaptive importance sampling technique which allows us to actively control the trade-off between bias and variance. We further provide a method for optimally determining the trade-off parameter based on a variant of cross-validation. We demonstrate the usefulness of the proposed approach through simulations.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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A PAC-Bayesian Approach to Formulation of Clustering Objectives

Seldin, Y., Tishby, N.

In Proceedings of the NIPS 2009 Workshop "Clustering: Science or Art? Towards Principled Approaches", pages: 1-4, NIPS Workshop "Clustering: Science or Art? Towards Principled Approaches", December 2009 (inproceedings)

Abstract
Clustering is a widely used tool for exploratory data analysis. However, the theoretical understanding of clustering is very limited. We still do not have a well-founded answer to the seemingly simple question of “how many clusters are present in the data?”, and furthermore a formal comparison of clusterings based on different optimization objectives is far beyond our abilities. The lack of good theoretical support gives rise to multiple heuristics that confuse the practitioners and stall development of the field. We suggest that the ill-posed nature of clustering problems is caused by the fact that clustering is often taken out of its subsequent application context. We argue that one does not cluster the data just for the sake of clustering it, but rather to facilitate the solution of some higher level task. By evaluation of the clustering’s contribution to the solution of the higher level task it is possible to compare different clusterings, even those obtained by different optimization objectives. In the preceding work it was shown that such an approach can be applied to evaluation and design of co-clustering solutions. Here we suggest that this approach can be extended to other settings, where clustering is applied.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Notes on Graph Cuts with Submodular Edge Weights

Jegelka, S., Bilmes, J.

In pages: 1-6, NIPS Workshop on Discrete Optimization in Machine Learning: Submodularity, Sparsity & Polyhedra (DISCML), December 2009 (inproceedings)

Abstract
Generalizing the cost in the standard min-cut problem to a submodular cost function immediately makes the problem harder. Not only do we prove NP hardness even for nonnegative submodular costs, but also show a lower bound of (|V |1/3) on the approximation factor for the (s, t) cut version of the problem. On the positive side, we propose and compare three approximation algorithms with an overall approximation factor of O(min{|V |,p|E| log |V |}) that appear to do well in practice.

ei

PDF Web [BibTex]

PDF Web [BibTex]