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2013


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Thermodynamics as a theory of decision-making with information-processing costs

Ortega, PA, Braun, DA

Proceedings of the Royal Society of London A, 469(2153):1-18, May 2013 (article)

Abstract
Perfectly rational decision-makers maximize expected utility, but crucially ignore the resource costs incurred when determining optimal actions. Here, we propose a thermodynamically inspired formalization of bounded rational decision-making where information processing is modelled as state changes in thermodynamic systems that can be quantified by differences in free energy. By optimizing a free energy, bounded rational decision-makers trade off expected utility gains and information-processing costs measured by the relative entropy. As a result, the bounded rational decision-making problem can be rephrased in terms of well-known variational principles from statistical physics. In the limit when computational costs are ignored, the maximum expected utility principle is recovered. We discuss links to existing decision-making frameworks and applications to human decision-making experiments that are at odds with expected utility theory. Since most of the mathematical machinery can be borrowed from statistical physics, the main contribution is to re-interpret the formalism of thermodynamic free-energy differences in terms of bounded rational decision-making and to discuss its relationship to human decision-making experiments.

ei

DOI [BibTex]

2013


DOI [BibTex]


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Tank-like module-based climbing robot using passive compliant joints

Seo, T., Sitti, M.

IEEE/ASME Transactions on Mechatronics, 18(1):397-408, 2013 (article)

pi

[BibTex]

[BibTex]


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Flapping wings via direct-driving by DC motors

Azhar, M., Campolo, D., Lau, G., Hines, L., Sitti, M.

In Robotics and Automation (ICRA), 2013 IEEE International Conference on, pages: 1397-1402, 2013 (inproceedings)

pi

[BibTex]

[BibTex]


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Three dimensional independent control of multiple magnetic microrobots

Diller, E., Giltinan, J., Jena, P., Sitti, M.

In Robotics and Automation (ICRA), 2013 IEEE International Conference on, pages: 2576-2581, 2013 (inproceedings)

pi

[BibTex]

[BibTex]


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Enhanced fabrication and characterization of gecko-inspired mushroom-tipped microfiber adhesives

Song, J., Mengüç, Y., Sitti, M.

Journal of Adhesion Science and Technology, 27(17):1921-1932, Routledge, 2013 (article)

pi

Project Page [BibTex]

Project Page [BibTex]


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Linear combination of one-step predictive information with an external reward in an episodic policy gradient setting: a critical analysis

Zahedi, K., Martius, G., Ay, N.

Frontiers in Psychology, 4(801), 2013 (article)

Abstract
One of the main challenges in the field of embodied artificial intelligence is the open-ended autonomous learning of complex behaviours. Our approach is to use task-independent, information-driven intrinsic motivation(s) to support task-dependent learning. The work presented here is a preliminary step in which we investigate the predictive information (the mutual information of the past and future of the sensor stream) as an intrinsic drive, ideally supporting any kind of task acquisition. Previous experiments have shown that the predictive information (PI) is a good candidate to support autonomous, open-ended learning of complex behaviours, because a maximisation of the PI corresponds to an exploration of morphology- and environment-dependent behavioural regularities. The idea is that these regularities can then be exploited in order to solve any given task. Three different experiments are presented and their results lead to the conclusion that the linear combination of the one-step PI with an external reward function is not generally recommended in an episodic policy gradient setting. Only for hard tasks a great speed-up can be achieved at the cost of an asymptotic performance lost.

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link (url) DOI [BibTex]


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Switching modes in easy and hard axis magnetic reversal in a self-assembled antidot array

Haering, F., Wiedwald, U., Nothelfer, S., Koslowski, B., Ziemann, P., Lechner, L., Wallucks, A., Lebecki, K., Nowak, U., Gräfe, J., Goering, E., Schütz, G.

{Nanotechnology}, 24, IOP Pub., Bristol, UK, 2013 (article)

mms

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Time-resolved imaging of nonlinear magnetic domain-wall dynamics in ferromagnetic nanowires

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

{Scientific Reports}, 3, Nature Publishing Group, London, UK, 2013 (article)

mms

DOI [BibTex]

DOI [BibTex]


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A cryogenically flexible covalent organic framework for efficient hydrogen isotrope separation by quantum sieving

Oh, H., Kalidindi, S. B., Um, Y., Bureekaew, S., Schmid, R., Fischer, R. A., Hirscher, M.

{Angewandte Chemie International Edition in English}, 52(50):13219-13222, Wiley-VCH Verlag GmbH & Co. KGaA, D-69451 Weinheim, 2013 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Unexpected room-temperature ferromagnetism in bulk ZnO

Chen, Y., Goering, E., Jeurgens, L., Wang, Z., Phillipp, F., Baier, J., Tietze, T., Schütz, G.

{Applied Physics Letters}, (103), American Institute of Physics, Melville, NY, 2013 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Large-area hard magnetic L10-FePt and composite L10-FePt based nanopatterns

Goll, D., Bublat, T.

{Physica Status Solidi A-Applications and Materials Science}, 210(7):1261-1271, Wiley-VCH, Weinheim, 2013 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Wave modes of collective vortex gyration in dipolar-coupled-dot-array magnonic crystals

Han, D., Vogel, A., Jung, H., Lee, K., Weigand, M., Stoll, H., Schütz, G., Fischer, P., Meier, G., Kim, S.

{Scientific Reports}, 3, Nature Publishing Group, London, UK, 2013 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Abstraction in Decision-Makers with Limited Information Processing Capabilities

Genewein, T, Braun, DA

pages: 1-9, NIPS Workshop Planning with Information Constraints for Control, Reinforcement Learning, Computational Neuroscience, Robotics and Games, December 2013 (conference)

Abstract
A distinctive property of human and animal intelligence is the ability to form abstractions by neglecting irrelevant information which allows to separate structure from noise. From an information theoretic point of view abstractions are desirable because they allow for very efficient information processing. In artificial systems abstractions are often implemented through computationally costly formations of groups or clusters. In this work we establish the relation between the free-energy framework for decision-making and rate-distortion theory and demonstrate how the application of rate-distortion for decision-making leads to the emergence of abstractions. We argue that abstractions are induced due to a limit in information processing capacity.

ei

link (url) [BibTex]

link (url) [BibTex]


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A Perching Mechanism for Flying Robots Using a Fibre-Based Adhesive

Daler, L., Klaptocz, A., Briod, A., Sitti, M., Floreano, D.

In Robotics and Automation (ICRA), 2013 IEEE International Conference on, 2013 (inproceedings)

pi

[BibTex]

[BibTex]


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Micro-scale mobile robotics

Diller, E., Sitti, M.

Foundations and Trends in Robotics, 2(3):143-259, Now Publishers Incorporated, 2013 (article)

pi

[BibTex]

[BibTex]


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Survey and Introduction to the Focused Section on Bio-Inspired Mechatronics

Sitti, M., Menciassi, A., Ijspeert, A., Low, K. H., Kim, S.

Mechatronics, IEEE/ASME Transactions on, 18(2):409-418, DOI: 10.1109/TMECH.2012. 2233492, 2013 (article)

pi

[BibTex]

[BibTex]


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Bonding methods for modular micro-robotic assemblies

Diller, E., Zhang, N., Sitti, M.

In Robotics and Automation (ICRA), 2013 IEEE International Conference on, pages: 2588-2593, 2013 (inproceedings)

pi

[BibTex]

[BibTex]


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Robustness of guided self-organization against sensorimotor disruptions

Martius, G.

Advances in Complex Systems, 16(02n03):1350001, 2013 (article)

Abstract
Self-organizing processes are crucial for the development of living beings. Practical applications in robots may benefit from the self-organization of behavior, e.g.~to increase fault tolerance and enhance flexibility, provided that external goals can also be achieved. We present results on the guidance of self-organizing control by visual target stimuli and show a remarkable robustness to sensorimotor disruptions. In a proof of concept study an autonomous wheeled robot is learning an object finding and ball-pushing task from scratch within a few minutes in continuous domains. The robustness is demonstrated by the rapid recovery of the performance after severe changes of the sensor configuration.

al

DOI [BibTex]

DOI [BibTex]


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Controlled Reduction with Unactuated Cyclic Variables: Application to 3D Bipedal Walking with Passive Yaw Rotation

Gregg, R., Righetti, L.

IEEE Transactions on Automatic Control, 58(10):2679-2685, October 2013 (article)

Abstract
This technical note shows that viscous damping can shape momentum conservation laws in a manner that stabilizes yaw rotation and enables steering for underactuated 3D walking. We first show that unactuated cyclic variables can be controlled by passively shaped conservation laws given a stabilizing controller in the actuated coordinates. We then exploit this result to realize controlled geometric reduction with multiple unactuated cyclic variables. We apply this underactuated control strategy to a five-link 3D biped to produce exponentially stable straight-ahead walking and steering in the presence of passive yawing.

mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Learning Task Error Models for Manipulation

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

In 2013 IEEE Conference on Robotics and Automation, IEEE, Karlsruhe, Germany, 2013 (inproceedings)

Abstract
Precise kinematic forward models are important for robots to successfully perform dexterous grasping and manipulation tasks, especially when visual servoing is rendered infeasible due to occlusions. A lot of research has been conducted to estimate geometric and non-geometric parameters of kinematic chains to minimize reconstruction errors. However, kinematic chains can include non-linearities, e.g. due to cable stretch and motor-side encoders, that result in significantly different errors for different parts of the state space. Previous work either does not consider such non-linearities or proposes to estimate non-geometric parameters of carefully engineered models that are robot specific. We propose a data-driven approach that learns task error models that account for such unmodeled non-linearities. We argue that in the context of grasping and manipulation, it is sufficient to achieve high accuracy in the task relevant state space. We identify this relevant state space using previously executed joint configurations and learn error corrections for those. Therefore, our system is developed to generate subsequent executions that are similar to previous ones. The experiments show that our method successfully captures the non-linearities in the head kinematic chain (due to a counterbalancing spring) and the arm kinematic chains (due to cable stretch) of the considered experimental platform, see Fig. 1. The feasibility of the presented error learning approach has also been evaluated in independent DARPA ARM-S testing contributing to successfully complete 67 out of 72 grasping and manipulation tasks.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Bounded Rational Decision-Making in Changing Environments

Grau-Moya, J, Braun, DA

pages: 1-9, NIPS Workshop Planning with Information Constraints for Control, Reinforcement Learning, Computational Neuroscience, Robotics and Games, December 2013 (conference)

Abstract
A perfectly rational decision-maker chooses the best action with the highest utility gain from a set of possible actions. The optimality principles that describe such decision processes do not take into account the computational costs of finding the optimal action. Bounded rational decision-making addresses this problem by specifically trading off information-processing costs and expected utility. Interestingly, a similar trade-off between energy and entropy arises when describing changes in thermodynamic systems. This similarity has been recently used to describe bounded rational agents. Crucially, this framework assumes that the environment does not change while the decision-maker is computing the optimal policy. When this requirement is not fulfilled, the decision-maker will suffer inefficiencies in utility, that arise because the current policy is optimal for an environment in the past. Here we borrow concepts from non-equilibrium thermodynamics to quantify these inefficiencies and illustrate with simulations its relationship with computational resources.

ei

link (url) [BibTex]

link (url) [BibTex]


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Ferromagnetism of zinc oxide nanograined films

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

{Journal of Experimental and Theoretical Physics Letters}, 97(6):367-377, Pleiades Publishing, Inc., 2013 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Hydrogen adsorption properties of platinum decorated hierarchically structured templated carbons

Oh, H., Gennett, T., Atanassov, P., Kurttepeli, M., Bals, S., Hurst, K. E., Hirscher, M.

{Microporous and Mesoporous Materials}, pages: 66-74, Elsevier, Amsterdam, 2013 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Extended s-d models for the dynamics of noncollinear magnetization: Short review of two different approaches

Fähnle, M., Zhang, S.

{Journal of Magnetism and Magnetic Materials}, 326, pages: 232-234, NH, Elsevier, Amsterdam, 2013 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Correlation between spin structure oscillations and domain wall velocities

Bisig, A., Stärk, M., Mawass, M., Moutafis, C., Rhensius, J., Heidler, J., Büttner, F., Noske, M., Weigand, M., Eisebitt, S., Tyliszczak, T., Van Wayenberge, B., Stoll, H., Schütz, G., Kläui, M.

{Nature Communications}, 4, Nature Publishing Group, London, 2013 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Recent advances in use of atomic layer deposition and focused ion beams for fabrication of Fresnel zone plates for hard x-rays

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

{Proceedings of SPIE (The International Society for Optical Engineering)}, 8851, 2013 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Magnetic states in low-pinning high-anisotropy material nanostructures suitable for dynamic imaging

Büttner, F., Moutafis, C., Bisig, A., Wohlhüter, P., Günther, C. M., Mohanty, J., Geilhufe, J., Schneider, M., v. Korff Schmising, C., Schaffert, S., Pfau, B., Hantschmann, M., Riemeier, M., Emmel, M., Finizio, S., Jakob, G., Weigand, M., Rhensius, J., Franken, J. H., Lavrijsen, R., Swagten, H. J. M., Stoll, H., Eisebitt, S., Kläui, M.

{Physical Review B}, 87, Published by the American Physical Society through the American Institute of Physics, Woodbury, NY, 2013 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Experimental and theoretical study of D2/H2 quantum sieving in a carbon molecular sieve

Gotzias, A., Charalambopoulou, G., Ampoumogli, A., Krkljus, I., Hirscher, M., Steriotis, T.

{Adsorption}, 19(2-4):373-379, Springer Science+Business Media, New York, 2013 (article)

mms

DOI [BibTex]

DOI [BibTex]


Thumb xl 2013 ivc rkek teaser
Non-parametric hand pose estimation with object context

Romero, J., Kjellström, H., Ek, C. H., Kragic, D.

Image and Vision Computing , 31(8):555 - 564, 2013 (article)

Abstract
In the spirit of recent work on contextual recognition and estimation, we present a method for estimating the pose of human hands, employing information about the shape of the object in the hand. Despite the fact that most applications of human hand tracking involve grasping and manipulation of objects, the majority of methods in the literature assume a free hand, isolated from the surrounding environment. Occlusion of the hand from grasped objects does in fact often pose a severe challenge to the estimation of hand pose. In the presented method, object occlusion is not only compensated for, it contributes to the pose estimation in a contextual fashion; this without an explicit model of object shape. Our hand tracking method is non-parametric, performing a nearest neighbor search in a large database (.. entries) of hand poses with and without grasped objects. The system that operates in real time, is robust to self occlusions, object occlusions and segmentation errors, and provides full hand pose reconstruction from monocular video. Temporal consistency in hand pose is taken into account, without explicitly tracking the hand in the high-dim pose space. Experiments show the non-parametric method to outperform other state of the art regression methods, while operating at a significantly lower computational cost than comparable model-based hand tracking methods.

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Publisher site pdf link (url) [BibTex]

Publisher site pdf link (url) [BibTex]

2011


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Statistical estimation for optimization problems on graphs

Langovoy, M., Sra, S.

In pages: 1-6, NIPS Workshop on Discrete Optimization in Machine Learning (DISCML): Uncertainty, Generalization and Feedback , December 2011 (inproceedings)

Abstract
Large graphs abound in machine learning, data mining, and several related areas. A useful step towards analyzing such graphs is that of obtaining certain summary statistics — e.g., or the expected length of a shortest path between two nodes, or the expected weight of a minimum spanning tree of the graph, etc. These statistics provide insight into the structure of a graph, and they can help predict global properties of a graph. Motivated thus, we propose to study statistical properties of structured subgraphs (of a given graph), in particular, to estimate the expected objective function value of a combinatorial optimization problem over these subgraphs. The general task is very difficult, if not unsolvable; so for concreteness we describe a more specific statistical estimation problem based on spanning trees. We hope that our position paper encourages others to also study other types of graphical structures for which one can prove nontrivial statistical estimates.

ei

PDF Web [BibTex]

2011


PDF Web [BibTex]


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On the discardability of data in Support Vector Classification problems

Del Favero, S., Varagnolo, D., Dinuzzo, F., Schenato, L., Pillonetto, G.

In pages: 3210-3215, IEEE, Piscataway, NJ, USA, 50th IEEE Conference on Decision and Control and European Control Conference (CDC - ECC), December 2011 (inproceedings)

Abstract
We analyze the problem of data sets reduction for support vector classification. The work is also motivated by distributed problems, where sensors collect binary measurements at different locations moving inside an environment that needs to be divided into a collection of regions labeled in two different ways. The scope is to let each agent retain and exchange only those measurements that are mostly informative for the collective reconstruction of the decision boundary. For the case of separable classes, we provide the exact conditions and an efficient algorithm to determine if an element in the training set can become a support vector when new data arrive. The analysis is then extended to the non-separable case deriving a sufficient discardability condition and a general data selection scheme for classification. Numerical experiments relative to the distributed problem show that the proposed procedure allows the agents to exchange a small amount of the collected data to obtain a highly predictive decision boundary.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Causal Inference on Discrete Data using Additive Noise Models

Peters, J., Janzing, D., Schölkopf, B.

IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(12):2436-2450, December 2011 (article)

Abstract
Inferring the causal structure of a set of random variables from a finite sample of the joint distribution is an important problem in science. The case of two random variables is particularly challenging since no (conditional) independences can be exploited. Recent methods that are based on additive noise models suggest the following principle: Whenever the joint distribution {\bf P}^{(X,Y)} admits such a model in one direction, e.g., Y=f(X)+N, N \perp\kern-6pt \perp X, but does not admit the reversed model X=g(Y)+\tilde{N}, \tilde{N} \perp\kern-6pt \perp Y, one infers the former direction to be causal (i.e., X\rightarrow Y). Up to now, these approaches only dealt with continuous variables. In many situations, however, the variables of interest are discrete or even have only finitely many states. In this work, we extend the notion of additive noise models to these cases. We prove that it almost never occurs that additive noise models can be fit in both directions. We further propose an efficient algorithm that is able to perform this way of causal inference on finite samples of discrete variables. We show that the algorithm works on both synthetic and real data sets.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Spontaneous epigenetic variation in the Arabidopsis thaliana methylome

Becker, C., Hagmann, J., Müller, J., Koenig, D., Stegle, O., Borgwardt, K., Weigel, D.

Nature, 480(7376):245-249, December 2011 (article)

Abstract
Heritable epigenetic polymorphisms, such as differential cytosine methylation, can underlie phenotypic variation1, 2. Moreover, wild strains of the plant Arabidopsis thaliana differ in many epialleles3, 4, and these can influence the expression of nearby genes1, 2. However, to understand their role in evolution5, it is imperative to ascertain the emergence rate and stability of epialleles, including those that are not due to structural variation. We have compared genome-wide DNA methylation among 10 A. thaliana lines, derived 30 generations ago from a common ancestor6. Epimutations at individual positions were easily detected, and close to 30,000 cytosines in each strain were differentially methylated. In contrast, larger regions of contiguous methylation were much more stable, and the frequency of changes was in the same low range as that of DNA mutations7. Like individual positions, the same regions were often affected by differential methylation in independent lines, with evidence for recurrent cycles of forward and reverse mutations. Transposable elements and short interfering RNAs have been causally linked to DNA methylation8. In agreement, differentially methylated sites were farther from transposable elements and showed less association with short interfering RNA expression than invariant positions. The biased distribution and frequent reversion of epimutations have important implications for the potential contribution of sequence-independent epialleles to plant evolution.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Information, learning and falsification

Balduzzi, D.

In pages: 1-4, NIPS Philosophy and Machine Learning Workshop, December 2011 (inproceedings)

Abstract
There are (at least) three approaches to quantifying information. The first, algorithmic information or Kolmogorov complexity, takes events as strings and, given a universal Turing machine, quantifies the information content of a string as the length of the shortest program producing it [1]. The second, Shannon information, takes events as belonging to ensembles and quantifies the information resulting from observing the given event in terms of the number of alternate events that have been ruled out [2]. The third, statistical learning theory, has introduced measures of capacity that control (in part) the expected risk of classifiers [3]. These capacities quantify the expectations regarding future data that learning algorithms embed into classifiers. Solomonoff and Hutter have applied algorithmic information to prove remarkable results on universal induction. Shannon information provides the mathematical foundation for communication and coding theory. However, both approaches have shortcomings. Algorithmic information is not computable, severely limiting its practical usefulness. Shannon information refers to ensembles rather than actual events: it makes no sense to compute the Shannon information of a single string – or rather, there are many answers to this question depending on how a related ensemble is constructed. Although there are asymptotic results linking algorithmic and Shannon information, it is unsatisfying that there is such a large gap – a difference in kind – between the two measures. This note describes a new method of quantifying information, effective information, that links algorithmic information to Shannon information, and also links both to capacities arising in statistical learning theory [4, 5]. After introducing the measure, we show that it provides a non-universal analog of Kolmogorov complexity. We then apply it to derive basic capacities in statistical learning theory: empirical VC-entropy and empirical Rademacher complexity. A nice byproduct of our approach is an interpretation of the explanatory power of a learning algorithm in terms of the number of hypotheses it falsifies [6], counted in two different ways for the two capacities. We also discuss how effective information relates to information gain, Shannon and mutual information.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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A general linear non-Gaussian state-space model: Identifiability, identification, and applications

Zhang, K., Hyvärinen, A.

In JMLR Workshop and Conference Proceedings Volume 20, pages: 113-128, (Editors: Hsu, C.-N. , W.S. Lee ), MIT Press, Cambridge, MA, USA, 3rd Asian Conference on Machine Learning (ACML), November 2011 (inproceedings)

Abstract
State-space modeling provides a powerful tool for system identification and prediction. In linear state-space models the data are usually assumed to be Gaussian and the models have certain structural constraints such that they are identifiable. In this paper we propose a non-Gaussian state-space model which does not have such constraints. We prove that this model is fully identifiable. We then propose an efficient two-step method for parameter estimation: one first extracts the subspace of the latent processes based on the temporal information of the data, and then performs multichannel blind deconvolution, making use of both the temporal information and non-Gaussianity. We conduct a series of simulations to illustrate the performance of the proposed method. Finally, we apply the proposed model and parameter estimation method on real data, including major world stock indices and magnetoencephalography (MEG) recordings. Experimental results are encouraging and show the practical usefulness of the proposed model and method.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Non-stationary correction of optical aberrations

Schuler, C., Hirsch, M., Harmeling, S., Schölkopf, B.

In pages: 659-666 , (Editors: DN Metaxas and L Quan and A Sanfeliu and LJ Van Gool), IEEE, Piscataway, NJ, USA, 13th IEEE International Conference on Computer Vision (ICCV), November 2011 (inproceedings)

Abstract
Taking a sharp photo at several megapixel resolution traditionally relies on high grade lenses. In this paper, we present an approach to alleviate image degradations caused by imperfect optics. We rely on a calibration step to encode the optical aberrations in a space-variant point spread function and obtain a corrected image by non-stationary deconvolution. By including the Bayer array in our image formation model, we can perform demosaicing as part of the deconvolution.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Learning low-rank output kernels

Dinuzzo, F., Fukumizu, K.

In JMLR Workshop and Conference Proceedings Volume 20, pages: 181-196, (Editors: Hsu, C.-N. , W.S. Lee), JMLR, Cambridge, MA, USA, 3rd Asian Conference on Machine Learning (ACML) , November 2011 (inproceedings)

Abstract
Output kernel learning techniques allow to simultaneously learn a vector-valued function and a positive semidefinite matrix which describes the relationships between the outputs. In this paper, we introduce a new formulation that imposes a low-rank constraint on the output kernel and operates directly on a factor of the kernel matrix. First, we investigate the connection between output kernel learning and a regularization problem for an architecture with two layers. Then, we show that a variety of methods such as nuclear norm regularized regression, reduced-rank regression, principal component analysis, and low rank matrix approximation can be seen as special cases of the output kernel learning framework. Finally, we introduce a block coordinate descent strategy for learning low-rank output kernels.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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HHfrag: HMM-based fragment detection using HHpred

Kalev, I., Habeck, M.

Bioinformatics, 27(22):3110-3116, November 2011 (article)

Abstract
Motivation: Over the last decade, both static and dynamic fragment libraries for protein structure prediction have been introduced. The former are built from clusters in either sequence or structure space and aim to extract a universal structural alphabet. The latter are tailored for a particular query protein sequence and aim to provide local structural templates that need to be assembled in order to build the full-length structure. Results: Here, we introduce HHfrag, a dynamic HMM-based fragment search method built on the profile–profile comparison tool HHpred. We show that HHfrag provides advantages over existing fragment assignment methods in that it: (i) improves the precision of the fragments at the expense of a minor loss in sequence coverage; (ii) detects fragments of variable length (6–21 amino acid residues); (iii) allows for gapped fragments and (iv) does not assign fragments to regions where there is no clear sequence conservation. We illustrate the usefulness of fragments detected by HHfrag on targets from most recent CASP.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Reward-Weighted Regression with Sample Reuse for Direct Policy Search in Reinforcement Learning

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

Neural Computation, 23(11):2798-2832, November 2011 (article)

Abstract
Direct policy search is a promising reinforcement learning framework, in particular for controlling continuous, high-dimensional systems. Policy search often requires a large number of samples for obtaining a stable policy update estimator, and this is prohibitive when the sampling cost is expensive. In this letter, we extend an expectation-maximization-based policy search method so that previously collected samples can be efficiently reused. The usefulness of the proposed method, reward-weighted regression with sample reuse (R), is demonstrated through robot learning experiments.

ei

Web DOI [BibTex]


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Stability Condition for Teleoperation System with Packet Loss

Hong, A., Cho, JH., Lee, DY.

In pages: 760-761, 2011 KSME Annual Fall Conference, November 2011 (inproceedings)

Abstract
This paper focuses on the stability condition of teleoperation system where there is a packet loss in communication channel. Communication channel between master and slave cause packet loss and it obviously leads to a performance degradation and instability of teleoperation system. We consider two-channel control architecture for teleoperation system, and control inputs to remote site are produced by position of master and slave. In this paper, teleoperation system is modeled in discrete domain to include packet loss process. Also, the stability condition for teleoperation system with packet loss is discussed with input-to-state stability. Finally, the stability condition is presented in LMI approach.

ei

[BibTex]

[BibTex]


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Model Learning in Robotics: a Survey

Nguyen-Tuong, D., Peters, J.

Cognitive Processing, 12(4):319-340, November 2011 (article)

Abstract
Models are among the most essential tools in robotics, such as kinematics and dynamics models of the robot's own body and controllable external objects. It is widely believed that intelligent mammals also rely on internal models in order to generate their actions. However, while classical robotics relies on manually generated models that are based on human insights into physics, future autonomous, cognitive robots need to be able to automatically generate models that are based on information which is extracted from the data streams accessible to the robot. In this paper, we survey the progress in model learning with a strong focus on robot control on a kinematic as well as dynamical level. Here, a model describes essential information about the behavior of the environment and the in uence of an agent on this environment. In the context of model based learning control, we view the model from three di fferent perspectives. First, we need to study the di erent possible model learning architectures for robotics. Second, we discuss what kind of problems these architecture and the domain of robotics imply for the applicable learning methods. From this discussion, we deduce future directions of real-time learning algorithms. Third, we show where these scenarios have been used successfully in several case studies.

ei

PDF [BibTex]

PDF [BibTex]


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Fast removal of non-uniform camera shake

Hirsch, M., Schuler, C., Harmeling, S., Schölkopf, B.

In pages: 463-470 , (Editors: DN Metaxas and L Quan and A Sanfeliu and LJ Van Gool), IEEE, Piscataway, NJ, USA, 13th IEEE International Conference on Computer Vision (ICCV), November 2011 (inproceedings)

Abstract
Camera shake leads to non-uniform image blurs. State-of-the-art methods for removing camera shake model the blur as a linear combination of homographically transformed versions of the true image. While this is conceptually interesting, the resulting algorithms are computationally demanding. In this paper we develop a forward model based on the efficient filter flow framework, incorporating the particularities of camera shake, and show how an efficient algorithm for blur removal can be obtained. Comprehensive comparisons on a number of real-world blurry images show that our approach is not only substantially faster, but it also leads to better deblurring results.

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PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Home 3D body scans from noisy image and range data

Weiss, A., Hirshberg, D., Black, M.

In Int. Conf. on Computer Vision (ICCV), pages: 1951-1958, IEEE, Barcelona, November 2011 (inproceedings)

Abstract
The 3D shape of the human body is useful for applications in fitness, games and apparel. Accurate body scanners, however, are expensive, limiting the availability of 3D body models. We present a method for human shape reconstruction from noisy monocular image and range data using a single inexpensive commodity sensor. The approach combines low-resolution image silhouettes with coarse range data to estimate a parametric model of the body. Accurate 3D shape estimates are obtained by combining multiple monocular views of a person moving in front of the sensor. To cope with varying body pose, we use a SCAPE body model which factors 3D body shape and pose variations. This enables the estimation of a single consistent shape while allowing pose to vary. Additionally, we describe a novel method to minimize the distance between the projected 3D body contour and the image silhouette that uses analytic derivatives of the objective function. We propose a simple method to estimate standard body measurements from the recovered SCAPE model and show that the accuracy of our method is competitive with commercial body scanning systems costing orders of magnitude more.

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pdf YouTube poster Project Page Project Page [BibTex]

pdf YouTube poster Project Page Project Page [BibTex]


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FaST linear mixed models for genome-wide association studies

Lippert, C., Listgarten, J., Liu, Y., Kadie, CM., Davidson, RI., Heckerman, D.

Nature Methods, 8(10):833–835, October 2011 (article)

Abstract
We describe factored spectrally transformed linear mixed models (FaST-LMM), an algorithm for genome-wide association studies (GWAS) that scales linearly with cohort size in both run time and memory use. On Wellcome Trust data for 15,000 individuals, FaST-LMM ran an order of magnitude faster than current efficient algorithms. Our algorithm can analyze data for 120,000 individuals in just a few hours, whereas current algorithms fail on data for even 20,000 individuals (http://mscompbio.codeplex.com/).

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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The effect of noise correlations in populations of diversely tuned neurons

Ecker, A., Berens, P., Tolias, A., Bethge, M.

Journal of Neuroscience, 31(40):14272-14283, October 2011 (article)

Abstract
The amount of information encoded by networks of neurons critically depends on the correlation structure of their activity. Neurons with similar stimulus preferences tend to have higher noise correlations than others. In homogeneous populations of neurons, this limited range correlation structure is highly detrimental to the accuracy of a population code. Therefore, reduced spike count correlations under attention, after adaptation, or after learning have been interpreted as evidence for a more efficient population code. Here, we analyze the role of limited range correlations in more realistic, heterogeneous population models. We use Fisher information and maximum-likelihood decoding to show that reduced correlations do not necessarily improve encoding accuracy. In fact, in populations with more than a few hundred neurons, increasing the level of limited range correlations can substantially improve encoding accuracy. We found that this improvement results from a decrease in noise entropy that is associated with increasing correlations if the marginal distributions are unchanged. Surprisingly, for constant noise entropy and in the limit of large populations, the encoding accuracy is independent of both structure and magnitude of noise correlations.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Attenuation correction in MR-BrainPET with segmented T1-weighted MR images of the patient’s head: A comparative study with CT

Wagenknecht, G., Rota Kops, E., Mantlik, F., Fried, E., Pilz, T., Hautzel, H., Tellmann, L., Pichler, B., Herzog, H.

In pages: 2261-2266 , IEEE, Piscataway, NJ, USA, IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), October 2011 (inproceedings)

Abstract
Our method for attenuation correction (AC) in MR-BrainPET with segmented T1-weighted MR images of the pa-tient's head was applied to data from different MR-BrainPET scanners (Jülich, Tübingen) and compared to CT-based results. The study objectives presented in this paper are twofold. The first objective is to examine if the segmentation method developed for and successfully applied to 3D MP-RAGE data can also be used to segment other T1-weighted MR data such as 3D FLASH data. The second aim is to show if the similarity of segmented MR-based (SBA) and CT-based AC (CBA) obtained at HR+ PET can also be confirmed for BrainPET for which the new AC method is intended for. In order to reach the first objective, 14 segmented MR data sets (three 3D MP-RAGE data sets from Jülich and eleven 3D FLASH data sets from Tubingen) were compared to the resp. CT data based on the Dice coefficient and scatter plots. For bone, a CT threshold HU>;500 was applied. Dice coefficients (mean±std) for the upper cranial part of the skull, the skull above cavities, and in the caudal part including the cerebellum are 0.73±0.1, 0.79±0.04, and 0.49±0.02 for the Jülich data and 0.7U0.1, 0.72±0.1, and 0.60±0.05 for the Tubingen data. To reach the second aim, SBA and CBA were compared for six subjects based on VOI (AAL atlas) analysis. Mean absolute relative difference (maRD) values are maRD(JUFVBWl-FDG): 0.99%±0.83%, maRD(JüFVBW2-FDG): 0.90%±0.89%, and maRD(JUEP-Fluma- zenil): 1.85%±1.25% for the Jülich data and maRD(TuTP02- FDG): 2.99%±1.65%, maRD(TuNP01-FDG): 5.37%±2.29%, and maRD(TuNP02-FDG): 6.52%±1.69% for the three best-segmented Tübingen data sets. The results show similar segmentation quality for both Tl- weighted MR sequence types. The application to AC in BrainPET - hows a high similarity to CT-based AC if the standardized ACF value for bone used in SBA is in good accordance to the bone density of the patient in question.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Analysis of Fixed-Point and Coordinate Descent Algorithms for Regularized Kernel Methods

Dinuzzo, F.

IEEE Transactions on Neural Networks, 22(10):1576-1587, October 2011 (article)

Abstract
In this paper, we analyze the convergence of two general classes of optimization algorithms for regularized kernel methods with convex loss function and quadratic norm regularization. The first methodology is a new class of algorithms based on fixed-point iterations that are well-suited for a parallel implementation and can be used with any convex loss function. The second methodology is based on coordinate descent, and generalizes some techniques previously proposed for linear support vector machines. It exploits the structure of additively separable loss functions to compute solutions of line searches in closed form. The two methodologies are both very easy to implement. In this paper, we also show how to remove non-differentiability of the objective functional by exactly reformulating a convex regularization problem as an unconstrained differentiable stabilization problem.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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A biomimetic approach to robot table tennis

Mülling, K., Kober, J., Peters, J.

Adaptive Behavior , 19(5):359-376 , October 2011 (article)

Abstract
Playing table tennis is a difficult motor task that requires fast movements, accurate control and adaptation to task parameters. Although human beings see and move slower than most robot systems, they significantly outperform all table tennis robots. One important reason for this higher performance is the human movement generation. In this paper, we study human movements during table tennis and present a robot system that mimics human striking behavior. Our focus lies on generating hitting motions capable of adapting to variations in environmental conditions, such as changes in ball speed and position. Therefore, we model the human movements involved in hitting a table tennis ball using discrete movement stages and the virtual hitting point hypothesis. The resulting model was evaluated both in a physically realistic simulation and on a real anthropomorphic seven degrees of freedom Barrett WAM™ robot arm.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Whole-genome sequencing of multiple Arabidopsis thaliana populations

Cao, J., Schneeberger, K., Ossowski, S., Günther, T., Bender, S., Fitz, J., Koenig, D., Lanz, C., Stegle, O., Lippert, C., Wang, X., Ott, F., Müller, J., Alonso-Blanco, C., Borgwardt, K., Schmid, K., Weigel, D.

Nature Genetics, 43(10):956–963, October 2011 (article)

Abstract
The plant Arabidopsis thaliana occurs naturally in many different habitats throughout Eurasia. As a foundation for identifying genetic variation contributing to adaptation to diverse environments, a 1001 Genomes Project to sequence geographically diverse A. thaliana strains has been initiated. Here we present the first phase of this project, based on population-scale sequencing of 80 strains drawn from eight regions throughout the species' native range. We describe the majority of common small-scale polymorphisms as well as many larger insertions and deletions in the A. thaliana pan-genome, their effects on gene function, and the patterns of local and global linkage among these variants. The action of processes other than spontaneous mutation is identified by comparing the spectrum of mutations that have accumulated since A. thaliana diverged from its closest relative 10 million years ago with the spectrum observed in the laboratory. Recent species-wide selective sweeps are rare, and potentially deleterious mutations are more common in marginal populations.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Evaluating the Automated Alignment of 3D Human Body Scans

Hirshberg, D. A., Loper, M., Rachlin, E., Tsoli, A., Weiss, A., Corner, B., Black, M. J.

In 2nd International Conference on 3D Body Scanning Technologies, pages: 76-86, (Editors: D’Apuzzo, Nicola), Hometrica Consulting, Lugano, Switzerland, October 2011 (inproceedings)

Abstract
The statistical analysis of large corpora of human body scans requires that these scans be in alignment, either for a small set of key landmarks or densely for all the vertices in the scan. Existing techniques tend to rely on hand-placed landmarks or algorithms that extract landmarks from scans. The former is time consuming and subjective while the latter is error prone. Here we show that a model-based approach can align meshes automatically, producing alignment accuracy similar to that of previous methods that rely on many landmarks. Specifically, we align a low-resolution, artist-created template body mesh to many high-resolution laser scans. Our alignment procedure employs a robust iterative closest point method with a regularization that promotes smooth and locally rigid deformation of the template mesh. We evaluate our approach on 50 female body models from the CAESAR dataset that vary significantly in body shape. To make the method fully automatic, we define simple feature detectors for the head and ankles, which provide initial landmark locations. We find that, if body poses are fairly similar, as in CAESAR, the fully automated method provides dense alignments that enable statistical analysis and anthropometric measurement.

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pdf slides DOI Project Page [BibTex]

pdf slides DOI Project Page [BibTex]