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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)

mms

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)

mms

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)

mms

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)

mms

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.

am mg

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)

pi

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)

pi

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)

pi

[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.

am mg

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)

mms

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)

mms

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)

mms

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)

mms

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)

mms

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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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)

mms

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)

mms

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)

mms

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]

2012


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Jensen-Bregman LogDet Divergence with Application to Efficient Similarity Search for Covariance Matrices

Cherian, A., Sra, S., Banerjee, A., Papanikolopoulos, N.

IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(9):2161-2174, December 2012 (article)

ei

DOI [BibTex]

2012


DOI [BibTex]


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Hippocampal-Cortical Interaction during Periods of Subcortical Silence

Logothetis, N., Eschenko, O., Murayama, Y., Augath, M., Steudel, T., Evrard, H., Besserve, M., Oeltermann, A.

Nature, 491, pages: 547-553, November 2012 (article)

Abstract
Hippocampal ripples, episodic high-frequency field-potential oscillations primarily occurring during sleep and calmness, have been described in mice, rats, rabbits, monkeys and humans, and so far they have been associated with retention of previously acquired awake experience. Although hippocampal ripples have been studied in detail using neurophysiological methods, the global effects of ripples on the entire brain remain elusive, primarily owing to a lack of methodologies permitting concurrent hippocampal recordings and whole-brain activity mapping. By combining electrophysiological recordings in hippocampus with ripple-triggered functional magnetic resonance imaging, here we show that most of the cerebral cortex is selectively activated during the ripples, whereas most diencephalic, midbrain and brainstem regions are strongly and consistently inhibited. Analysis of regional temporal response patterns indicates that thalamic activity suppression precedes the hippocampal population burst, which itself is temporally bounded by massive activations of association and primary cortical areas. These findings suggest that during off-line memory consolidation, synergistic thalamocortical activity may be orchestrating a privileged interaction state between hippocampus and cortex by silencing the output of subcortical centres involved in sensory processing or potentially mediating procedural learning. Such a mechanism would cause minimal interference, enabling consolidation of hippocampus-dependent memory.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Thermodynamic limits of dynamic cooling

Allahverdyan, A., Hovhannisyan, K., Janzing, D., Mahler, G.

Physical Review E, 84(4):16, October 2012 (article)

Abstract
We study dynamic cooling, where an externally driven two-level system is cooled via reservoir, a quantum system with initial canonical equilibrium state. We obtain explicitly the minimal possible temperature Tmin>0 reachable for the two-level system. The minimization goes over all unitary dynamic processes operating on the system and reservoir and over the reservoir energy spectrum. The minimal work needed to reach Tmin grows as 1/Tmin. This work cost can be significantly reduced, though, if one is satisfied by temperatures slightly above Tmin. Our results on Tmin>0 prove unattainability of the absolute zero temperature without ambiguities that surround its derivation from the entropic version of the third law. We also study cooling via a reservoir consisting of N≫1 identical spins. Here we show that Tmin∝1/N and find the maximal cooling compatible with the minimal work determined by the free energy. Finally we discuss cooling by reservoir with an initially microcanonic state and show that although a purely microcanonic state can yield the zero temperature, the unattainability is recovered when taking into account imperfections in preparing the microcanonic state.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Coupled Action Recognition and Pose Estimation from Multiple Views

Yao, A., Gall, J., van Gool, L.

International Journal of Computer Vision, 100(1):16-37, October 2012 (article)

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publisher's site code pdf Project Page Project Page Project Page [BibTex]

publisher's site code pdf Project Page Project Page Project Page [BibTex]


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GLIDE: GPU-Based Linear Regression for Detection of Epistasis

Kam-Thong, T., Azencott, C., Cayton, L., Pütz, B., Altmann, A., Karbalai, N., Sämann, P., Schölkopf, B., Müller-Myhsok, B., Borgwardt, K.

Human Heredity, 73(4):220-236, September 2012 (article)

Abstract
Due to recent advances in genotyping technologies, mapping phenotypes to single loci in the genome has become a standard technique in statistical genetics. However, one-locus mapping fails to explain much of the phenotypic variance in complex traits. Here, we present GLIDE, which maps phenotypes to pairs of genetic loci and systematically searches for the epistatic interactions expected to reveal part of this missing heritability. GLIDE makes use of the computational power of consumer-grade graphics cards to detect such interactions via linear regression. This enabled us to conduct a systematic two-locus mapping study on seven disease data sets from the Wellcome Trust Case Control Consortium and on in-house hippocampal volume data in 6 h per data set, while current single CPU-based approaches require more than a year’s time to complete the same task.

ei

Web [BibTex]

Web [BibTex]


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Fast projection onto mixed-norm balls with applications

Sra, S.

Minining and Knowledge Discovery (DMKD), 25(2):358-377, September 2012 (article)

ei

DOI [BibTex]

DOI [BibTex]


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Bayesian estimation of free energies from equilibrium simulations

Habeck, M.

Physical Review Letters, 109(10):5, September 2012 (article)

Abstract
Free energy calculations are an important tool in statistical physics and biomolecular simulation. This Letter outlines a Bayesian method to estimate free energies from equilibrium Monte Carlo simulations. A Gibbs sampler is developed that allows efficient sampling of free energies and the density of states. The Gibbs sampling output can be used to estimate expected free energy differences and their uncertainties. The probabilistic formulation offers a unifying framework for existing methods such as the weighted histogram analysis method and the multistate Bennett acceptance ratio; both are shown to be approximate versions of the full probabilistic treatment.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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DRAPE: DRessing Any PErson

Guan, P., Reiss, L., Hirshberg, D., Weiss, A., Black, M. J.

ACM Trans. on Graphics (Proc. SIGGRAPH), 31(4):35:1-35:10, July 2012 (article)

Abstract
We describe a complete system for animating realistic clothing on synthetic bodies of any shape and pose without manual intervention. The key component of the method is a model of clothing called DRAPE (DRessing Any PErson) that is learned from a physics-based simulation of clothing on bodies of different shapes and poses. The DRAPE model has the desirable property of "factoring" clothing deformations due to body shape from those due to pose variation. This factorization provides an approximation to the physical clothing deformation and greatly simplifies clothing synthesis. Given a parameterized model of the human body with known shape and pose parameters, we describe an algorithm that dresses the body with a garment that is customized to fit and possesses realistic wrinkles. DRAPE can be used to dress static bodies or animated sequences with a learned model of the cloth dynamics. Since the method is fully automated, it is appropriate for dressing large numbers of virtual characters of varying shape. The method is significantly more efficient than physical simulation.

ps

YouTube pdf talk Project Page Project Page [BibTex]

YouTube pdf talk Project Page Project Page [BibTex]


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PAC-Bayesian Inequalities for Martingales

Seldin, Y., Laviolette, F., Cesa-Bianchi, N., Shawe-Taylor, J., Auer, P.

IEEE Transactions on Information Theory, 58(12):7086-7093, June 2012 (article)

Abstract
We present a set of high-probability inequalities that control the concentration of weighted averages of multiple (possibly uncountably many) simultaneously evolving and interdependent martingales. We also present a comparison inequality that bounds expectation of a convex function of martingale difference type variables by expectation of the same function of independent Bernoulli variables. This inequality is applied to derive a tighter analog of Hoeffding-Azuma inequality.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Entropy Search for Information-Efficient Global Optimization

Hennig, P., Schuler, C.

Journal of Machine Learning Research, 13, pages: 1809-1837, -, June 2012 (article)

Abstract
Contemporary global optimization algorithms are based on local measures of utility, rather than a probability measure over location and value of the optimum. They thus attempt to collect low function values, not to learn about the optimum. The reason for the absence of probabilistic global optimizers is that the corresponding inference problem is intractable in several ways. This paper develops desiderata for probabilistic optimization algorithms, then presents a concrete algorithm which addresses each of the computational intractabilities with a sequence of approximations and explicitly adresses the decision problem of maximizing information gain from each evaluation.

ei pn

PDF Web Project Page [BibTex]

PDF Web Project Page [BibTex]


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Visual Orientation and Directional Selectivity Through Thalamic Synchrony

Stanley, G., Jin, J., Wang, Y., Desbordes, G., Wang, Q., Black, M., Alonso, J.

Journal of Neuroscience, 32(26):9073-9088, June 2012 (article)

Abstract
Thalamic neurons respond to visual scenes by generating synchronous spike trains on the timescale of 10–20 ms that are very effective at driving cortical targets. Here we demonstrate that this synchronous activity contains unexpectedly rich information about fundamental properties of visual stimuli. We report that the occurrence of synchronous firing of cat thalamic cells with highly overlapping receptive fields is strongly sensitive to the orientation and the direction of motion of the visual stimulus. We show that this stimulus selectivity is robust, remaining relatively unchanged under different contrasts and temporal frequencies (stimulus velocities). A computational analysis based on an integrate-and-fire model of the direct thalamic input to a layer 4 cortical cell reveals a strong correlation between the degree of thalamic synchrony and the nonlinear relationship between cortical membrane potential and the resultant firing rate. Together, these findings suggest a novel population code in the synchronous firing of neurons in the early visual pathway that could serve as the substrate for establishing cortical representations of the visual scene.

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preprint publisher's site Project Page [BibTex]

preprint publisher's site Project Page [BibTex]


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A Neuromorphic Architecture for Object Recognition and Motion Anticipation Using Burst-STDP

Nere, A., Olcese, U., Balduzzi, D., Tononi, G.

PLoS ONE, 7(5):17, May 2012 (article)

Abstract
In this work we investigate the possibilities offered by a minimal framework of artificial spiking neurons to be deployed in silico. Here we introduce a hierarchical network architecture of spiking neurons which learns to recognize moving objects in a visual environment and determine the correct motor output for each object. These tasks are learned through both supervised and unsupervised spike timing dependent plasticity (STDP). STDP is responsible for the strengthening (or weakening) of synapses in relation to pre- and post-synaptic spike times and has been described as a Hebbian paradigm taking place both in vitro and in vivo. We utilize a variation of STDP learning, called burst-STDP, which is based on the notion that, since spikes are expensive in terms of energy consumption, then strong bursting activity carries more information than single (sparse) spikes. Furthermore, this learning algorithm takes advantage of homeostatic renormalization, which has been hypothesized to promote memory consolidation during NREM sleep. Using this learning rule, we design a spiking neural network architecture capable of object recognition, motion detection, attention towards important objects, and motor control outputs. We demonstrate the abilities of our design in a simple environment with distractor objects, multiple objects moving concurrently, and in the presence of noise. Most importantly, we show how this neural network is capable of performing these tasks using a simple leaky-integrate-and-fire (LIF) neuron model with binary synapses, making it fully compatible with state-of-the-art digital neuromorphic hardware designs. As such, the building blocks and learning rules presented in this paper appear promising for scalable fully neuromorphic systems to be implemented in hardware chips.

ei

PDF Web DOI [BibTex]


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Online Kernel-based Learning for Task-Space Tracking Robot Control

Nguyen-Tuong, D., Peters, J.

IEEE Transactions on Neural Networks and Learning Systems, 23(9):1417-1425, May 2012 (article)

Abstract
Abstract—Task-space control of redundant robot systems based on analytical models is known to be susceptive to modeling errors. Here, data driven model learning methods may present an interesting alternative approach. However, learning models for task-space tracking control from sampled data is an illposed problem. In particular, the same input data point can yield many different output values, which can form a non-convex solution space. Because the problem is ill-posed, models cannot be learned from such data using common regression methods. While learning of task-space control mappings is globally illposed, it has been shown in recent work that it is locally a well-defined problem. In this paper, we use this insight to formulate a local, kernel-based learning approach for online model learning for task-space tracking control. We propose a parametrization for the local model which makes an application in task-space tracking control of redundant robots possible. The model parametrization further allows us to apply the kerneltrick and, therefore, enables a formulation within the kernel learning framework. For evaluations, we show the ability of the method for online model learning for task-space tracking control of redundant robots.

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Information-geometric approach to inferring causal directions

Janzing, D., Mooij, J., Zhang, K., Lemeire, J., Zscheischler, J., Daniušis, P., Steudel, B., Schölkopf, B.

Artificial Intelligence, 182-183, pages: 1-31, May 2012 (article)

Abstract
While conventional approaches to causal inference are mainly based on conditional (in)dependences, recent methods also account for the shape of (conditional) distributions. The idea is that the causal hypothesis “X causes Y” imposes that the marginal distribution PX and the conditional distribution PY|X represent independent mechanisms of nature. Recently it has been postulated that the shortest description of the joint distribution PX,Y should therefore be given by separate descriptions of PX and PY|X. Since description length in the sense of Kolmogorov complexity is uncomputable, practical implementations rely on other notions of independence. Here we define independence via orthogonality in information space. This way, we can explicitly describe the kind of dependence that occurs between PY and PX|Y making the causal hypothesis “Y causes X” implausible. Remarkably, this asymmetry between cause and effect becomes particularly simple if X and Y are deterministically related. We present an inference method that works in this case. We also discuss some theoretical results for the non-deterministic case although it is not clear how to employ them for a more general inference method.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Sparse regularized regression identifies behaviorally-relevant stimulus features from psychophysical data

Schönfelder, V., Wichmann, F.

Journal of the Acoustical Society of America, 131(5):3953-3969, May 2012 (article)

Abstract
As a prerequisite to quantitative psychophysical models of sensory processing it is necessary to learn to what extent decisions in behavioral tasks depend on specific stimulus features, the perceptual cues. Based on relative linear combination weights, this study demonstrates how stimulus-response data can be analyzed in this regard relying on an L1-regularized multiple logistic regression, a modern statistical procedure developed in machine learning. This method prevents complex models from over-fitting to noisy data. In addition, it enforces “sparse” solutions, a computational approximation to the postulate that a good model should contain the minimal set of predictors necessary to explain the data. In simulations, behavioral data from a classical auditory tone-in-noise detection task were generated. The proposed method is shown to precisely identify observer cues from a large set of covarying, interdependent stimulus features—a setting where standard correlational and regression methods fail. The proposed method succeeds for a wide range of signal-to-noise ratios and for deterministic as well as probabilistic observers. Furthermore, the detailed decision rules of the simulated observers were reconstructed from the estimated linear model weights allowing predictions of responses on the basis of individual stimuli.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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glm-ie: The Generalised Linear Models Inference and Estimation Toolbox

Nickisch, H.

Journal of Machine Learning Research, 13, pages: 1699-1703, May 2012 (article)

Abstract
The glm-ie toolbox contains scalable estimation routines for GLMs (generalised linear models) and SLMs (sparse linear models) as well as an implementation of a scalable convex variational Bayesian inference relaxation. We designed the glm-ie package to be simple, generic and easily expansible. Most of the code is written in Matlab including some The code is fully compatible to both Matlab 7.x and GNU Octave 3.3.x. Abstract Probabilistic classification, sparse linear modelling and logistic regression are covered in a common algorithmical framework.

ei

PDF PDF [BibTex]

PDF PDF [BibTex]


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Feature Selection via Dependence Maximization

Song, L., Smola, A., Gretton, A., Bedo, J., Borgwardt, K.

Journal of Machine Learning Research, 13, pages: 1393-1434, May 2012 (article)

Abstract
We introduce a framework of feature selection based on dependence maximization between the selected features and the labels of an estimation problem, using the Hilbert-Schmidt Independence Criterion. The key idea is that good features should be highly dependent on the labels. Our approach leads to a greedy procedure for feature selection. We show that a number of existing feature selectors are special cases of this framework. Experiments on both artificial and real-world data show that our feature selector works well in practice.

ei

PDF [BibTex]

PDF [BibTex]