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2014


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Magnetic reflectometry of heterostructures (Topical Review)

Macke, S., Goering, E.

{Journal of Physics: Condensed Matter}, 26(36), IOP Publishing, Bristol, 2014 (article)

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DOI [BibTex]

2014


DOI [BibTex]


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Optimizing the fabrication of diffractive optical elements using a focused ion beam system

Vijayakumar, A., Eigenthaler, U., Keskinbora, K., Sridharan, G. M., Pramitha, V., Hirscher, M., Spatz, J. P., Bhattacharya, S.

{Proceedings of SPIE}, 9130, 2014 (article)

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DOI [BibTex]

DOI [BibTex]


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Direct observation of internal vortex domain-wall dynamics

Stein, F.-U., Bocklage, L., Weigand, M., Meier, G.

{Physical Review B}, 89(2), American Physical Society, Woodbury, NY, 2014 (article)

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DOI [BibTex]

DOI [BibTex]


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Synchronous precessional motion of multiple domain walls in a ferromagnetic nanowire by perpendicular field pulses

Kim, J., Mawass, M., Bisig, A., Krüger, B., Reeve, R. M., Schulz, T., Büttner, F., Yoon, J., You, C., Weigand, M., Stoll, H., Schütz, G., Swagten, H. J. M., Koopmans, B., Eisebitt, S., Kläui, M.

{Nature Communications}, 5, Nature Publishing Group, London, 2014 (article)

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DOI [BibTex]

DOI [BibTex]


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An autonomous manipulation system based on force control and optimization

Righetti, L., Kalakrishnan, M., Pastor, P., Binney, J., Kelly, J., Voorhies, R. C., Sukhatme, G. S., Schaal, S.

Autonomous Robots, 36(1-2):11-30, January 2014 (article)

Abstract
In this paper we present an architecture for autonomous manipulation. Our approach is based on the belief that contact interactions during manipulation should be exploited to improve dexterity and that optimizing motion plans is useful to create more robust and repeatable manipulation behaviors. We therefore propose an architecture where state of the art force/torque control and optimization-based motion planning are the core components of the system. We give a detailed description of the modules that constitute the complete system and discuss the challenges inherent to creating such a system. We present experimental results for several grasping and manipulation tasks to demonstrate the performance and robustness of our approach.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Occam’s Razor in sensorimotor learning

Genewein, T, Braun, D

Proceedings of the Royal Society of London B, 281(1783):1-7, May 2014 (article)

Abstract
A large number of recent studies suggest that the sensorimotor system uses probabilistic models to predict its environment and makes inferences about unobserved variables in line with Bayesian statistics. One of the important features of Bayesian statistics is Occam's Razor—an inbuilt preference for simpler models when comparing competing models that explain some observed data equally well. Here, we test directly for Occam's Razor in sensorimotor control. We designed a sensorimotor task in which participants had to draw lines through clouds of noisy samples of an unobserved curve generated by one of two possible probabilistic models—a simple model with a large length scale, leading to smooth curves, and a complex model with a short length scale, leading to more wiggly curves. In training trials, participants were informed about the model that generated the stimulus so that they could learn the statistics of each model. In probe trials, participants were then exposed to ambiguous stimuli. In probe trials where the ambiguous stimulus could be fitted equally well by both models, we found that participants showed a clear preference for the simpler model. Moreover, we found that participants’ choice behaviour was quantitatively consistent with Bayesian Occam's Razor. We also show that participants’ drawn trajectories were similar to samples from the Bayesian predictive distribution over trajectories and significantly different from two non-probabilistic heuristics. In two control experiments, we show that the preference of the simpler model cannot be simply explained by a difference in physical effort or by a preference for curve smoothness. Our results suggest that Occam's Razor is a general behavioural principle already present during sensorimotor processing.

ei

DOI [BibTex]

DOI [BibTex]


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Generalized Thompson sampling for sequential decision-making and causal inference

Ortega, PA, Braun, DA

Complex Adaptive Systems Modeling, 2(2):1-23, March 2014 (article)

Abstract
Purpose Sampling an action according to the probability that the action is believed to be the optimal one is sometimes called Thompson sampling. Methods Although mostly applied to bandit problems, Thompson sampling can also be used to solve sequential adaptive control problems, when the optimal policy is known for each possible environment. The predictive distribution over actions can then be constructed by a Bayesian superposition of the policies weighted by their posterior probability of being optimal. Results Here we discuss two important features of this approach. First, we show in how far such generalized Thompson sampling can be regarded as an optimal strategy under limited information processing capabilities that constrain the sampling complexity of the decision-making process. Second, we show how such Thompson sampling can be extended to solve causal inference problems when interacting with an environment in a sequential fashion. Conclusion In summary, our results suggest that Thompson sampling might not merely be a useful heuristic, but a principled method to address problems of adaptive sequential decision-making and causal inference.

ei

DOI [BibTex]

DOI [BibTex]


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Liftoff of a Motor-Driven, Flapping-Wing Microaerial Vehicle Capable of Resonance

Hines, L., Campolo, D., Sitti, M.

IEEE Trans. on Robotics, 30(1):220-232, IEEE, 2014 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Untethered micro-robotic coding of three-dimensional material composition

Tasoglu, S, Diller, E, Guven, S, Sitti, M, Demirci, U

Nature Communications, 5, pages: DOI-10, Nature Publishing Group, 2014 (article)

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Project Page [BibTex]

Project Page [BibTex]


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The optimal shape of elastomer mushroom-like fibers for high and robust adhesion

Aksak, B., Sahin, K., Sitti, M.

Beilstein journal of nanotechnology, 5(1):630-638, Beilstein-Institut, 2014 (article)

pi

Project Page [BibTex]

Project Page [BibTex]


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Mechanically Switchable Elastomeric Microfibrillar Adhesive Surfaces for Transfer Printing

Sariola, V., Sitti, M.

Advanced Materials Interfaces, 1(4):1300159, 2014 (article)

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[BibTex]

[BibTex]


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MultiMo-Bat: A biologically inspired integrated jumping–gliding robot

Woodward, M. A., Sitti, M.

The International Journal of Robotics Research, 33(12):1511-1529, SAGE Publications Sage UK: London, England, 2014 (article)

pi

Project Page [BibTex]

Project Page [BibTex]


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Learning of grasp selection based on shape-templates

Herzog, A., Pastor, P., Kalakrishnan, M., Righetti, L., Bohg, J., Asfour, T., Schaal, S.

Autonomous Robots, 36(1-2):51-65, January 2014 (article)

Abstract
The ability to grasp unknown objects still remains an unsolved problem in the robotics community. One of the challenges is to choose an appropriate grasp configuration, i.e., the 6D pose of the hand relative to the object and its finger configuration. In this paper, we introduce an algorithm that is based on the assumption that similarly shaped objects can be grasped in a similar way. It is able to synthesize good grasp poses for unknown objects by finding the best matching object shape templates associated with previously demonstrated grasps. The grasp selection algorithm is able to improve over time by using the information of previous grasp attempts to adapt the ranking of the templates to new situations. We tested our approach on two different platforms, the Willow Garage PR2 and the Barrett WAM robot, which have very different hand kinematics. Furthermore, we compared our algorithm with other grasp planners and demonstrated its superior performance. The results presented in this paper show that the algorithm is able to find good grasp configurations for a large set of unknown objects from a relatively small set of demonstrations, and does improve its performance over time.

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link (url) DOI [BibTex]


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Magnetic field distribution and characteristic fields of the vortex lattice for a clean superconducting niobium sample in an external field applied along a three-fold axis

Yaouanc, A., Maisuradze, A., Nakai, N., Machida, K., Khasanov, R., Amato, A., Biswas, P. K., Baines, C., Herlach, D., Henes, Rolf, Keppler, P., Keller, H.

{Physical Review B}, 89(18), American Physical Society, Woodbury, NY, 2014 (article)

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DOI [BibTex]

DOI [BibTex]


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Experimental assessment of Physical upper limit for hydrogen storage capacity at 20 K in densified MIL-101 monoliths

Oh, H., Lupu, D., Blanita, G., Hirscher, M.

{RSC Advances}, 4(6):2648-2651, Royal Society of Chemistry, Cambridge, UK, 2014 (article)

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DOI [BibTex]

DOI [BibTex]


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Strengthening zones in the Co matrix of WC-Co cemented carbides

Konyashin, I., Lachmann, F., Ries, B., Mazilkin, A. A., Straumal, B. B., Kübel, C., Llanes, L., Baretzky, B.

{Scripta Materialia}, 83, pages: 17-20, Pergamon, Tarrytown, NY, 2014 (article)

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DOI [BibTex]

DOI [BibTex]


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Multilayer Fresnel zone plates for high energy radiation resolve 21 nm features at 1.2 keV

Keskinbora, K., Robisch, A., Mayer, M., Sanli, U., Grévent, C., Wolter, C., Weigand, M., Szeghalmi, A., Knez, M., Salditt, T., Schütz, G.

{Optics Express}, 22(15):18440-18453, Optical Society of America, Washington, DC, 2014 (article)

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DOI [BibTex]

DOI [BibTex]


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Interplay of linker functionalization and hydrogen adsorption in the metal-organic framework MIL-101

Szilágyi, P. A., Weinrauch, I., Oh, H., Hirscher, M., Juan-Alcaniz, J., Serra-Crespo, P., de Respinis, M., Trzesniewski, B. J., Kapteijn, F., Geerlings, H., Gascon, J., Dam, B., Grzech, A., van de Krol, R.

{The Journal of Physical Chemistry C}, 118(34):19572-19579, American Chemical Society, Washington DC, 2014 (article)

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DOI [BibTex]

DOI [BibTex]


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Application of magneto-optical Kerr effect to first-order reversal curve measurements

Gräfe, J., Schmidt, M., Audehm, P., Schütz, G., Goering, E.

{Review of Scientific Instruments}, 85, American Institute of Physics, Woodbury, N.Y. [etc.], 2014 (article)

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Efficient focusing of 8 keV X-rays with multilayer Fresnel zone plates fabricated by atomic layer deposition and focused ion beam milling. Erratum

Mayer, M., Keskinbora, K., Grévent, C., Szeghalmi, A., Knez, M., Weigand, M., Snigirev, A., Snigireva, I., Schütz, G.

{Journal of Synchrotron Radiation}, 640, pages: 640-640, Published for the International Union of Crystallography by Munksgaard, Copenhagen, Denmark, 2014 (article)

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DOI [BibTex]

DOI [BibTex]


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Low-amplitude magnetic vortex core reversal by non-linear interaction between azimuthal spin waves and the vortex gyromode

Sproll, M., Noske, M., Bauer, H., Kammerer, M., Gangwar, A., Dieterle, G., Weigand, M., Stoll, H., Woltersdorf, G., Back, C. H., Schütz, G.

{Applied Physics Letters}, 104(1), American Institute of Physics, Melville, NY, 2014 (article)

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DOI [BibTex]

DOI [BibTex]


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A Quantitative Analysis of Current Practices in Optical Flow Estimation and the Principles behind Them

Sun, D., Roth, S., Black, M. J.

International Journal of Computer Vision (IJCV), 106(2):115-137, 2014 (article)

Abstract
The accuracy of optical flow estimation algorithms has been improving steadily as evidenced by results on the Middlebury optical flow benchmark. The typical formulation, however, has changed little since the work of Horn and Schunck. We attempt to uncover what has made recent advances possible through a thorough analysis of how the objective function, the optimization method, and modern implementation practices influence accuracy. We discover that "classical'' flow formulations perform surprisingly well when combined with modern optimization and implementation techniques. One key implementation detail is the median filtering of intermediate flow fields during optimization. While this improves the robustness of classical methods it actually leads to higher energy solutions, meaning that these methods are not optimizing the original objective function. To understand the principles behind this phenomenon, we derive a new objective function that formalizes the median filtering heuristic. This objective function includes a non-local smoothness term that robustly integrates flow estimates over large spatial neighborhoods. By modifying this new term to include information about flow and image boundaries we develop a method that can better preserve motion details. To take advantage of the trend towards video in wide-screen format, we further introduce an asymmetric pyramid downsampling scheme that enables the estimation of longer range horizontal motions. The methods are evaluated on Middlebury, MPI Sintel, and KITTI datasets using the same parameter settings.

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pdf full text code [BibTex]

pdf full text code [BibTex]


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Assessing randomness and complexity in human motion trajectories through analysis of symbolic sequences

Peng, Z, Genewein, T, Braun, DA

Frontiers in Human Neuroscience, 8(168):1-13, March 2014 (article)

Abstract
Complexity is a hallmark of intelligent behavior consisting both of regular patterns and random variation. To quantitatively assess the complexity and randomness of human motion, we designed a motor task in which we translated subjects' motion trajectories into strings of symbol sequences. In the first part of the experiment participants were asked to perform self-paced movements to create repetitive patterns, copy pre-specified letter sequences, and generate random movements. To investigate whether the degree of randomness can be manipulated, in the second part of the experiment participants were asked to perform unpredictable movements in the context of a pursuit game, where they received feedback from an online Bayesian predictor guessing their next move. We analyzed symbol sequences representing subjects' motion trajectories with five common complexity measures: predictability, compressibility, approximate entropy, Lempel-Ziv complexity, as well as effective measure complexity. We found that subjects’ self-created patterns were the most complex, followed by drawing movements of letters and self-paced random motion. We also found that participants could change the randomness of their behavior depending on context and feedback. Our results suggest that humans can adjust both complexity and regularity in different movement types and contexts and that this can be assessed with information-theoretic measures of the symbolic sequences generated from movement trajectories.

ei

DOI [BibTex]

DOI [BibTex]


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Rotating Magnetic Miniature Swimming Robots With Multiple Flexible Flagella

Ye, Z., Régnier, S., Sitti, M.

IEEE Trans. on Robotics, 30(1):3-13, 2014 (article)

pi

[BibTex]

[BibTex]


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Three-Dimensional Programmable Assembly by Untethered Magnetic Robotic Micro-Grippers

Diller, E., Sitti, M.

Advanced Functional Materials, 24, pages: 4397-4404, 2014 (article)

pi

Project Page [BibTex]

Project Page [BibTex]


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Mechanics of Load–Drag–Unload Contact Cleaning of Gecko-Inspired Fibrillar Adhesives

Abusomwan, U. A., Sitti, M.

Langmuir, 30(40):11913-11918, American Chemical Society, 2014 (article)

pi

Project Page [BibTex]

Project Page [BibTex]


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Nanoporous Materials for Hydrogen Storage and H2/D2 Isotope Separation

Oh, H.

Universität Stuttgart, Stuttgart, 2014 (phdthesis)

mms

link (url) [BibTex]

link (url) [BibTex]


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The local magnetic properties of [MnIII6 CrIII]3+ and [FeIII6 CrIII]3+ single-molecule magnets deposited on surfaces studied by spin-polarized photoemission and XMCD with circularly polarized synchrotron radiation

Heinzmann, U., Helmstedt, A., Dohmeier, N., Müller, N., Gryzia, A., Brechling, A., Hoeke, V., Krickemeyer, E., Glaser, T., Fonin, M., Bouvron, S., Leicht, P., Tietze, T., Goering, E., Kuepper, K.

{Journal of Physics: Conference Series}, 488(13), IOP Publishing, Bristol, 2014 (article)

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DOI [BibTex]

DOI [BibTex]


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A fluorene based covalent triazine framework with high CO2 and H2 capture and storage capacities

Hug, S., Mesch, M. B., Oh, H., Popp, N., Hirscher, M., Senker, J., Lotsch, B. V.

{Journal of Materials Chemistry A}, 2(16):5928-5936, Royal Society of Chemistry, Cambridge, UK, 2014 (article)

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DOI [BibTex]

DOI [BibTex]


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Ab-initio calculations and atomistic calculations on the magnetoelectric effects in metallic nanostructures

Fähnle, M., Subkow, S.

{Physica Status Solidi C}, 11(2):185-191, Wiley-VCH, Weinheim, 2014 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Role of electron-magnon scatterings in ultrafast demagnetization

Haag, M., Illg, C., Fähnle, M.

{Physical Review B}, 90(1), American Physical Society, Woodbury, NY, 2014 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Element specific monolayer depth profiling

Macke, S., Radi, A., Hamann-Borrero, J. E., Verna, A., Bluschke, M., Brück, S., Goering, E., Sutarto, R., He, F., Cristiani, G., Wu, M., Benckiser, E., Habermeier, H., Logvenov, G., Gauquelin, N., Botton, G. A., Kajdos, A. P., Stemmer, S., Sawatzky, G. A., Haverkort, M. W., Keimer, B., Hinkov, V.

{Advanced Materials}, 26(38):6554-6559, Wiley VCH, Weinheim, 2014 (article)

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DOI [BibTex]

DOI [BibTex]


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Local modification of the magnetic vortex-core velocity by gallium implantation

Langner, H. H., Vogel, A., Beyersdorff, B., Weigand, M., Frömter, R., Oepen, H. P., Meier, G.

{Journal of Applied Physcis}, (10), American Institute of Physics, New York, NY, 2014 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Influence of magnetic fields on spin-mixing in transition metals

Haag, M., Illg, C., Fähnle, M.

{Physical Review B}, 90(13), American Physical Society, Woodbury, NY, 2014 (article)

mms

DOI [BibTex]

DOI [BibTex]

2010


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Causal relationships between frequency bands of extracellular signals in visual cortex revealed by an information theoretic analysis

Besserve, M., Schölkopf, B., Logothetis, N., Panzeri, S.

Journal of Computational Neuroscience, 29(3):547-566, December 2010 (article)

ei

PDF DOI [BibTex]

2010


PDF DOI [BibTex]


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Tackling Box-Constrained Optimization via a New Projected Quasi-Newton Approach

Kim, D., Sra, S., Dhillon, I.

SIAM Journal on Scientific Computing, 32(6):3548-3563 , December 2010 (article)

Abstract
Numerous scientific applications across a variety of fields depend on box-constrained convex optimization. Box-constrained problems therefore continue to attract research interest. We address box-constrained (strictly convex) problems by deriving two new quasi-Newton algorithms. Our algorithms are positioned between the projected-gradient [J. B. Rosen, J. SIAM, 8 (1960), pp. 181–217] and projected-Newton [D. P. Bertsekas, SIAM J. Control Optim., 20 (1982), pp. 221–246] methods. We also prove their convergence under a simple Armijo step-size rule. We provide experimental results for two particular box-constrained problems: nonnegative least squares (NNLS), and nonnegative Kullback–Leibler (NNKL) minimization. For both NNLS and NNKL our algorithms perform competitively as compared to well-established methods on medium-sized problems; for larger problems our approach frequently outperforms the competition.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Algorithmen zum Automatischen Erlernen von Motorfähigkeiten

Peters, J., Kober, J., Schaal, S.

at - Automatisierungstechnik, 58(12):688-694, December 2010 (article)

Abstract
Robot learning methods which allow autonomous robots to adapt to novel situations have been a long standing vision of robotics, artificial intelligence, and cognitive sciences. However, to date, learning techniques have yet to fulfill this promise as only few methods manage to scale into the high-dimensional domains of manipulator robotics, or even the new upcoming trend of humanoid robotics. If possible, scaling was usually only achieved in precisely pre-structured domains. In this paper, we investigate the ingredients for a general approach policy learning with the goal of an application to motor skill refinement in order to get one step closer towards human-like performance. For doing so, we study two major components for such an approach, i. e., firstly, we study policy learning algorithms which can be applied in the general setting of motor skill learning, and, secondly, we study a theoretically well-founded general approach to representing the required control structures for task representation and execution.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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PAC-Bayesian Analysis of Co-clustering and Beyond

Seldin, Y., Tishby, N.

Journal of Machine Learning Research, 11, pages: 3595-3646, December 2010 (article)

ei

PDF PDF [BibTex]

PDF PDF [BibTex]


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Gaussian Processes for Machine Learning (GPML) Toolbox

Rasmussen, C., Nickisch, H.

Journal of Machine Learning Research, 11, pages: 3011-3015, November 2010 (article)

Abstract
The GPML toolbox provides a wide range of functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean and covariance functions; we offer a library of simple mean and covariance functions and mechanisms to compose more complex ones. Several likelihood functions are supported including Gaussian and heavy-tailed for regression as well as others suitable for classification. Finally, a range of inference methods is provided, including exact and variational inference, Expectation Propagation, and Laplace's method dealing with non-Gaussian likelihoods and FITC for dealing with large regression tasks.

ei

Web [BibTex]

Web [BibTex]


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Cryo-EM structure and rRNA model of a translating eukaryotic 80S ribosome at 5.5-Å resolution

Armache, J-P., Jarasch, A., Anger, AM., Villa, E., Becker, T., Bhushan, S., Jossinet, F., Habeck, M., Dindar, G., Franckenberg, S., Marquez, V., Mielke, T., Thomm, M., Berninghausen, O., Beatrix, B., Söding, J., Westhof, E., Wilson, DN., Beckmann, R.

Proceedings of the National Academy of Sciences of the United States of America, 107(46):19748-19753, November 2010 (article)

Abstract
Protein biosynthesis, the translation of the genetic code into polypeptides, occurs on ribonucleoprotein particles called ribosomes. Although X-ray structures of bacterial ribosomes are available, high-resolution structures of eukaryotic 80S ribosomes are lacking. Using cryoelectron microscopy and single-particle reconstruction, we have determined the structure of a translating plant (Triticum aestivum) 80S ribosome at 5.5-Å resolution. This map, together with a 6.1-Å map of a Saccharomyces cerevisiae 80S ribosome, has enabled us to model ∼98% of the rRNA. Accurate assignment of the rRNA expansion segments (ES) and variable regions has revealed unique ES–ES and r-protein–ES interactions, providing insight into the structure and evolution of the eukaryotic ribosome.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Policy gradient methods

Peters, J.

Scholarpedia, 5(11):3698, November 2010 (article)

Abstract
Policy gradient methods are a type of reinforcement learning techniques that rely upon optimizing parametrized policies with respect to the expected return (long-term cumulative reward) by gradient descent. They do not suffer from many of the problems that have been marring traditional reinforcement learning approaches such as the lack of guarantees of a value function, the intractability problem resulting from uncertain state information and the complexity arising from continuous states & actions.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Localization of eukaryote-specific ribosomal proteins in a 5.5-Å cryo-EM map of the 80S eukaryotic ribosome

Armache, J-P., Jarasch, A., Anger, AM., Villa, E., Becker, T., Bhushan, S., Jossinet, F., Habeck, M., Dindar, G., Franckenberg, S., Marquez, V., Mielke, T., Thomm, M., Berninghausen, O., Beatrix, B., Söding, J., Westhof, E., Wilson, DN., Beckmann, R.

Proceedings of the National Academy of Sciences of the United States of America, 107(46):19754-19759, November 2010 (article)

Abstract
Protein synthesis in all living organisms occurs on ribonucleoprotein particles, called ribosomes. Despite the universality of this process, eukaryotic ribosomes are significantly larger in size than their bacterial counterparts due in part to the presence of 80 r proteins rather than 54 in bacteria. Using cryoelectron microscopy reconstructions of a translating plant (Triticum aestivum) 80S ribosome at 5.5-Å resolution, together with a 6.1-Å map of a translating Saccharomyces cerevisiae 80S ribosome, we have localized and modeled 74/80 (92.5%) of the ribosomal proteins, encompassing 12 archaeal/eukaryote-specific small subunit proteins as well as the complete complement of the ribosomal proteins of the eukaryotic large subunit. Near-complete atomic models of the 80S ribosome provide insights into the structure, function, and evolution of the eukaryotic translational apparatus.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Spatio-Spectral Remote Sensing Image Classification With Graph Kernels

Camps-Valls, G., Shervashidze, N., Borgwardt, K.

IEEE Geoscience and Remote Sensing Letters, 7(4):741-745, October 2010 (article)

Abstract
This letter presents a graph kernel for spatio-spectral remote sensing image classification with support vector machines (SVMs). The method considers higher order relations in the neighborhood (beyond pairwise spatial relations) to iteratively compute a kernel matrix for SVM learning. The proposed kernel is easy to compute and constitutes a powerful alternative to existing approaches. The capabilities of the method are illustrated in several multi- and hyperspectral remote sensing images acquired over both urban and agricultural areas.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Causal Inference Using the Algorithmic Markov Condition

Janzing, D., Schölkopf, B.

IEEE Transactions on Information Theory, 56(10):5168-5194, October 2010 (article)

Abstract
Inferring the causal structure that links $n$ observables is usually based upon detecting statistical dependences and choosing simple graphs that make the joint measure Markovian. Here we argue why causal inference is also possible when the sample size is one. We develop a theory how to generate causal graphs explaining similarities between single objects. To this end, we replace the notion of conditional stochastic independence in the causal Markov condition with the vanishing of conditional algorithmic mutual information and describe the corresponding causal inference rules. We explain why a consistent reformulation of causal inference in terms of algorithmic complexity implies a new inference principle that takes into account also the complexity of conditional probability densities, making it possible to select among Markov equivalent causal graphs. This insight provides a theoretical foundation of a heuristic principle proposed in earlier work. We also sketch some ideas on how to replace Kolmogorov complexity with decidable complexity criteria. This can be seen as an algorithmic analog of replacing the empirically undecidable question of statistical independence with practical independence tests that are based on implicit or explicit assumptions on the underlying distribution.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Recurrent Policy Gradients

Wierstra, D., Förster, A., Peters, J., Schmidhuber, J.

Logic Journal of the IGPL, 18(5):620-634, October 2010 (article)

Abstract
Reinforcement learning for partially observable Markov decision problems (POMDPs) is a challenge as it requires policies with an internal state. Traditional approaches suffer significantly from this shortcoming and usually make strong assumptions on the problem domain such as perfect system models, state-estimators and a Markovian hidden system. Recurrent neural networks (RNNs) offer a natural framework for dealing with policy learning using hidden state and require only few limiting assumptions. As they can be trained well using gradient descent, they are suited for policy gradient approaches. In this paper, we present a policy gradient method, the Recurrent Policy Gradient which constitutes a model-free reinforcement learning method. It is aimed at training limited-memory stochastic policies on problems which require long-term memories of past observations. The approach involves approximating a policy gradient for a recurrent neural network by backpropagating return-weighted characteristic eligibilities through time. Using a ‘‘Long Short-Term Memory’’ RNN architecture, we are able to outperform previous RL methods on three important benchmark tasks. Furthermore, we show that using history-dependent baselines helps reducing estimation variance significantly, thus enabling our approach to tackle more challenging, highly stochastic environments.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Discriminative frequent subgraph mining with optimality guarantees

Thoma, M., Cheng, H., Gretton, A., Han, J., Kriegel, H., Smola, A., Song, L., Yu, P., Yan, X., Borgwardt, K.

Journal of Statistical Analysis and Data Mining, 3(5):302–318, October 2010 (article)

Abstract
The goal of frequent subgraph mining is to detect subgraphs that frequently occur in a dataset of graphs. In classification settings, one is often interested in discovering discriminative frequent subgraphs, whose presence or absence is indicative of the class membership of a graph. In this article, we propose an approach to feature selection on frequent subgraphs, called CORK, that combines two central advantages. First, it optimizes a submodular quality criterion, which means that we can yield a near-optimal solution using greedy feature selection. Second, our submodular quality function criterion can be integrated into gSpan, the state-of-the-art tool for frequent subgraph mining, and help to prune the search space for discriminative frequent subgraphs even during frequent subgraph mining.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Bayesian Inference and Experimental Design for Large Generalised Linear Models

Nickisch, H.

Biologische Kybernetik, Technische Universität Berlin, Berlin, Germany, September 2010 (phdthesis)

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Combining active learning and reactive control for robot grasping

Kroemer, O., Detry, R., Piater, J., Peters, J.

Robotics and Autonomous Systems, 58(9):1105-1116, September 2010 (article)

Abstract
Grasping an object is a task that inherently needs to be treated in a hybrid fashion. The system must decide both where and how to grasp the object. While selecting where to grasp requires learning about the object as a whole, the execution only needs to reactively adapt to the context close to the grasp’s location. We propose a hierarchical controller that reflects the structure of these two sub-problems, and attempts to learn solutions that work for both. A hybrid architecture is employed by the controller to make use of various machine learning methods that can cope with the large amount of uncertainty inherent to the task. The controller’s upper level selects where to grasp the object using a reinforcement learner, while the lower level comprises an imitation learner and a vision-based reactive controller to determine appropriate grasping motions. The resulting system is able to quickly learn good grasps of a novel object in an unstructured environment, by executing smooth reaching motions and preshapin g the hand depending on the object’s geometry. The system was evaluated both in simulation and on a real robot.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Nonparametric Regression between General Riemannian Manifolds

Steinke, F., Hein, M., Schölkopf, B.

SIAM Journal on Imaging Sciences, 3(3):527-563, September 2010 (article)

Abstract
We study nonparametric regression between Riemannian manifolds based on regularized empirical risk minimization. Regularization functionals for mappings between manifolds should respect the geometry of input and output manifold and be independent of the chosen parametrization of the manifolds. We define and analyze the three most simple regularization functionals with these properties and present a rather general scheme for solving the resulting optimization problem. As application examples we discuss interpolation on the sphere, fingerprint processing, and correspondence computations between three-dimensional surfaces. We conclude with characterizing interesting and sometimes counterintuitive implications and new open problems that are specific to learning between Riemannian manifolds and are not encountered in multivariate regression in Euclidean space.

ei

Web DOI [BibTex]

Web DOI [BibTex]