Header logo is



no image
Outlook and challenges for hydrogen storage in nanoporous materials

Broom, D. P., Webb, C. J., Hurst, K. E., Parilla, P. A., Gennett, T., Brown, C. M., Zacharia, R., Tylianakis, E., Klontzas, E., Froudakis, G. E., Steriotis, T. A., Trikalitis, P. N., Anton, D. L., Hardy, B., Tamburello, D., Corgnale, C., van Hassel, B. A., Cossement, D., Chahine, R., Hirscher, M.

{Applied Physics A}, 122(3), Springer-Verlag Heidelberg, Heidelberg, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Quantum sieving for separation of hydrogen isotopes using MOFs

Oh, H., Hirscher, M.

{European Journal of Inorganic Chemistry}, 2016(27):4278-4289, Wiley-VCH, Weinheim, Germany, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Direct patterning of vortex generators on a fiber tip using a focused ion beam

Vayalamkuzhi, P., Bhattacharya, S., Eigenthaler, U., Keskinbora, K., Salman, C. T., Hirscher, M., Spatz, J. P., Viswanathan, N. K.

{Optics Letters}, 41(10):2133-2136, Optical Society of America, Washington, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Two-body problem of core-region coupled magnetic vortex stacks

Hänze, M., Adolff, C. F., Velten, S., Weigand, M., Meier, G.

{Physical Review B}, 93(5), American Physical Society, Woodbury, NY, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Irreproducibility in hydrogen storage material research

Broom, D. P., Hirscher, M.

{Energy \& Environmental Science}, 9(11):3368-3380, Royal Society of Chemistry, Cambridge, UK, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Effect of surface configurations on the room-temperature magnetism of pure ZnO

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

{Journal of Materials Chemistry C}, 4(19):4166-4175, Royal Society of Chemistry, London, UK, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
On the synthesis and microstructure analysis of high performance MnBi

Chen, Y., Sawatzki, S., Ener, S., Sepehri-Amin, H., Leineweber, A., Gregori, G., Qu, F., Muralidhar, S., Ohkubo, T., Hono, K., Gutfleisch, O., Kronmüller, H., Schütz, G., Goering, E.

{AIP Advances}, 6(12), 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Deep Learning for Diabetic Retinopathy Diagnostics

Balles, Lukas

Heidelberg University, 2016 (mastersthesis)

[BibTex]

[BibTex]


no image
Cell patterning in a hydrogel using optically induced dielectrophoresis

Hu, W., Ishii, K., Ohta, A. T.

In Optical MEMS and Nanophotonics (OMN), 2016 International Conference on, pages: 1-2, 2016 (inproceedings)

pi

[BibTex]

[BibTex]


no image
Scene Flow Propagation for Semantic Mapping and Object Discovery in Dynamic Street Scenes

Kochanov, D., Osep, A., Stueckler, J., Leibe, B.

In IEEE/RSJ Int. Conference on Intelligent Robots and Systems, IROS, 2016 (inproceedings)

ev

[BibTex]

[BibTex]


no image
Separating cognitive load facets in a working memory updating task: An experimental approach

Wirzberger, M., Beege, M., Schneider, S., Nebel, S., Rey, G. D.

In International Meeting of the Psychonomic Society, Granada – Spain, May 5-8, 2016, Abstract Book, pages: 211-212, 2016 (inproceedings)

re

[BibTex]

[BibTex]


no image
The role of individual defects on the magnetic screening of HTSC films

Ruoß, S., Stahl, C., Weigand, M., Zahn, P., Bayer, J., Schütz, G., Albrecht, J.

{New Journal of Physics}, 18(10), IOP Publishing, Bristol, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Magnetic switching of nanoscale antidot lattices

Wiedwald, U., Gräfe, J., Lebecki, K. M., Skripnik, M., Haering, F., Schütz, G., Ziemann, P., Goering, E., Nowak, U.

{Beilstein Journal of Nanotechnology}, 7, pages: 733-750, Beilstein-Institut, Frankfurt am Main, 2016 (article)

mms

DOI Project Page [BibTex]

DOI Project Page [BibTex]


no image
Hydrogen-based energy storage (IEA-HIA Task 32)

Buckley, C. E., Chen, P., van Hassel, B. A., Hirscher, M.

{Applied Physics A}, 122(2), Springer-Verlag Heidelberg, Heidelberg, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Local domain-wall velocity engineering via tailored potential landscapes in ferromagnetic rings

Richter, K., Krone, A., Mawass, M., Krüger, B., Weigand, M., Stoll, H., Schütz, G., Kläui, M.

{Physical Review Applied}, 5(2), American Physical Society, College Park, Md. [u.a.], 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Geometric control of the magnetization reversal in antidot lattices with perpendicular magnetic anisotropy

Gräfe, J., Weigand, M., Träger, N., Schütz, G., Goering, E. J., Skripnik, M., Nowak, U., Haering, F., Ziemann, P., Wiedwald, U.

{Physical Review B}, 93(10), American Physical Society, Woodbury, NY, 2016 (article)

mms

DOI Project Page Project Page [BibTex]

DOI Project Page Project Page [BibTex]


no image
Growth and characterizationof large weak topological insulator Bi2Tel single crystal by Bismuth self-flux method

Ryu, G., Son, K., Schütz, G.

{Journal of Crystal Growth}, 440, pages: 26-30, North-Holland, Amsterdam, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Additive interfacial chiral interaction in multilayers for stabilization of small individual skyrmions at room temperature

Moreau-Luchaire, C., Moutafis, C., Reyren, N., Sampaio, J., Vaz, C. A. F., Van Horne, N., Bouzehouane, K., Garcia, K., Deranlot, C., Warnicke, P., Wohlhüter, P., George, J.-M., Weigand, M., Raabe, J., Cros, V., Fert, A.

{Nature Nanotechnology}, 11(5):444-448, Nature Publishing Group, London, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Surface defect free growth of a spin dimer TlCuCl3 compound crystals and investigations on its optical and magnetic properties

Ryu, G., Son, K.

{Journal of Solid State Chemistry}, 237, pages: 358-363, Academic Press, Orlando, Fla., 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Physical and mathematical justification of the numerical Brillouin zone integration of the Boltzmann rate equation by Gaussian smearing

Illg, C., Haag, M., Teeny, N., Wirth, J., Fähnle, M.

{Journal of Theoretical and Applied Physics}, 10(1):1-6, Springer, Berlin, Heidelberg, Tehran, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Joint Object Pose Estimation and Shape Reconstruction in Urban Street Scenes Using 3D Shape Priors

Engelmann, F., Stueckler, J., Leibe, B.

In Proc. of the German Conference on Pattern Recognition (GCPR), 2016 (inproceedings)

ev

[BibTex]

[BibTex]


no image
CLT meets WMU: Simultaneous experimental manipulation of load factors in a basal working memory task

Wirzberger, M., Beege, M., Schneider, S., Nebel, S., Rey, G. D.

In 9th International Cognitive Load Theory Conference, June 22nd to 24th, 2016, Bochum, Germany, Abstracts, pages: 19, 2016 (inproceedings)

re

[BibTex]

[BibTex]


no image
Bedingt räumliche Nähe bessere Lernergebnisse? Die Rolle der Distanz und Integration beim Lernen mit multiplen Informationsquellen

Beege, M., Nebel, S., Schneider, S., Wirzberger, M., Schmidt, N., Rey, G. D.

In 50th Conference of the German Psychological Society. Abstracts, pages: 540, Pabst Science Publishers, Lengerich, 2016 (inproceedings)

re

[BibTex]

[BibTex]


no image
On the Effects of Measurement Uncertainty in Optimal Control of Contact Interactions

Ponton, B., Schaal, S., Righetti, L.

In The 12th International Workshop on the Algorithmic Foundations of Robotics WAFR, Berkeley, USA, 2016 (inproceedings)

Abstract
Stochastic Optimal Control (SOC) typically considers noise only in the process model, i.e. unknown disturbances. However, in many robotic applications involving interaction with the environment, such as locomotion and manipulation, uncertainty also comes from lack of precise knowledge of the world, which is not an actual disturbance. We analyze the effects of also considering noise in the measurement model, by devel- oping a SOC algorithm based on risk-sensitive control, that includes the dynamics of an observer in such a way that the control law explicitly de- pends on the current measurement uncertainty. In simulation results on a simple 2D manipulator, we have observed that measurement uncertainty leads to low impedance behaviors, a result in contrast with the effects of process noise that creates stiff behaviors. This suggests that taking into account measurement uncertainty could be a potentially very interesting way to approach problems involving uncertain contact interactions.

am mg

link (url) [BibTex]

link (url) [BibTex]


no image
A Convex Model of Momentum Dynamics for Multi-Contact Motion Generation

Ponton, B., Herzog, A., Schaal, S., Righetti, L.

In 2016 IEEE-RAS 16th International Conference on Humanoid Robots Humanoids, pages: 842-849, IEEE, Cancun, Mexico, 2016 (inproceedings)

Abstract
Linear models for control and motion generation of humanoid robots have received significant attention in the past years, not only due to their well known theoretical guarantees, but also because of practical computational advantages. However, to tackle more challenging tasks and scenarios such as locomotion on uneven terrain, a more expressive model is required. In this paper, we are interested in contact interaction-centered motion optimization based on the momentum dynamics model. This model is non-linear and non-convex; however, we find a relaxation of the problem that allows us to formulate it as a single convex quadratically-constrained quadratic program (QCQP) that can be very efficiently optimized and is useful for multi-contact planning. This convex model is then coupled to the optimization of end-effector contact locations using a mixed integer program, which can also be efficiently solved. This becomes relevant e.g. to recover from external pushes, where a predefined stepping plan is likely to fail and an online adaptation of the contact location is needed. The performance of our algorithm is demonstrated in several multi-contact scenarios for a humanoid robot.

am mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Helium und Hydrogen Isotope Adsorption and Separation in Metal-Organic Frameworks

Zaiser, Ingrid

Universität Stuttgart, Stuttgart (und Cuvillier Verlag, Göttingen), 2016 (phdthesis)

mms

[BibTex]

[BibTex]


no image
Pinned orbital moments - A new contribution to magnetic anisotropy

Audehm, P., Schmidt, M., Brück, S., Tietze, T., Gräfe, J., Macke, S., Schütz, G., Goering, E.

{Scientific Reports}, 6, Nature Publishing Group, London, UK, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Comparative study of ALD SiO2 thin films for optical applications

Pfeiffer, K., Shestaeva, S., Bingel, A., Munzert, P., Ghazaryan, L., van Helvoirt, C., Kessels, W. M. M., Sanli, U. T., Grévent, C., Schütz, G., Putkonen, M., Buchanan, I., Jensen, L., Ristau, D., Tünnermann, A., Szeghalmi, A.

{Optical materials express}, 6(2):660-670, OSA, Washington, DC, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Combined first-order reversal curve and x-ray microscopy investigation of magnetization reversal mechanisms in hexagonal antidot lattices

Gräfe, J., Weigand, M., Stahl, C., Träger, N., Kopp, M., Schütz, G., Goering, E. J., Haering, F., Ziemann, P., Wiedwald, U.

{Physical Review B}, 93(1), American Physical Society, Woodbury, NY, 2016 (article)

mms

DOI Project Page Project Page [BibTex]

DOI Project Page Project Page [BibTex]


no image
Switching probabilities of magnetic vortex core reversal studied by table top magneto optic Kerr microscopy

Dieterle, G., Gangwar, A., Gräfe, J., Noske, M., Förster, J., Woltersdorf, G., Stoll, H., Back, C. H., Schütz, G.

{Applied Physics Letters}, 108(2), American Institute of Physics, Melville, NY, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Ultrafast demagnetization after femtosecond laser pulses: Transfer of angular momentum from the electronic system to magnetoelastic spin-phonon modes

Tsatsoulis, T., Illg, C., Haag, M., Müller, B. Y., Zhang, L., Fähnle, M.

{Physical Review B}, 93(13), American Physical Society, Woodbury, NY, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Developments in the Ni-Nb-Zr amorphous alloy membranes

Sarker, S., Chandra, D., Hirscher, M., Dolan, M., Isheim, D., Wermer, J., Viano, D., Baricco, M., Udovic, T. J., Grant, D., Palumbo, O., Paolone, A., Cantelli, R.

{Applied Physics A}, 122(3), Springer-Verlag Heidelberg, Heidelberg, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Resistance to the transport of H2 through the external surface of as-made and modified silicalite-1 (MFI)

Kalantzopoulos, G. N., Policicchio, A., Maccallini, E., Krkljus, I., Ciuchi, F., Hirscher, M., Agostino, R. G., Golemme, G.

{Microporous and Mesoporous Materials}, 220, pages: 290-297, Elsevier, Amsterdam, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]


no image
Observation of pseudopartial grain boundary wetting in the NdFeB-based alloy

Straumal, B. B., Mazilkin, A. A., Protasova, S. G., Schütz, G., Straumal, A. B., Baretzky, B.

{Journal of Materials Engineering and Performance}, 25(8):3303-3309, 2016 (article)

mms

DOI [BibTex]

DOI [BibTex]

2006


no image
Global Biclustering of Microarray Data

Wolf, T., Brors, B., Hofmann, T., Georgii, E.

In ICDMW 2006, pages: 125-129, (Editors: Tsumoto, S. , C. W. Clifton, N. Zhong, X. Wu, J. Liu, B. W. Wah, Y.-M. Cheung), IEEE Computer Society, Los Alamitos, CA, USA, Sixth IEEE International Conference on Data Mining, December 2006 (inproceedings)

Abstract
We consider the problem of simultaneously clustering genes and conditions of a gene expression data matrix. A bicluster is defined as a subset of genes that show similar behavior within a subset of conditions. Finding biclusters can be useful for revealing groups of genes involved in the same molecular process as well as groups of conditions where this process takes place. Previous work either deals with local, bicluster-based criteria or assumes a very specific structure of the data matrix (e.g. checkerboard or block-diagonal) [11]. In contrast, our goal is to find a set of flexibly arranged biclusters which is optimal in regard to a global objective function. As this is a NP-hard combinatorial problem, we describe several techniques to obtain approximate solutions. We benchmarked our approach successfully on the Alizadeh B-cell lymphoma data set [1].

ei

Web DOI [BibTex]

2006


Web DOI [BibTex]


no image
Conformal Multi-Instance Kernels

Blaschko, M., Hofmann, T.

In NIPS 2006 Workshop on Learning to Compare Examples, pages: 1-6, NIPS Workshop on Learning to Compare Examples, December 2006 (inproceedings)

Abstract
In the multiple instance learning setting, each observation is a bag of feature vectors of which one or more vectors indicates membership in a class. The primary task is to identify if any vectors in the bag indicate class membership while ignoring vectors that do not. We describe here a kernel-based technique that defines a parametric family of kernels via conformal transformations and jointly learns a discriminant function over bags together with the optimal parameter settings of the kernel. Learning a conformal transformation effectively amounts to weighting regions in the feature space according to their contribution to classification accuracy; regions that are discriminative will be weighted higher than regions that are not. This allows the classifier to focus on regions contributing to classification accuracy while ignoring regions that correspond to vectors found both in positive and in negative bags. We show how parameters of this transformation can be learned for support vector machines by posing the problem as a multiple kernel learning problem. The resulting multiple instance classifier gives competitive accuracy for several multi-instance benchmark datasets from different domains.

ei

PDF Web [BibTex]

PDF Web [BibTex]


no image
Some observations on the pedestal effect or dipper function

Henning, B., Wichmann, F.

Journal of Vision, 6(13):50, 2006 Fall Vision Meeting of the Optical Society of America, December 2006 (poster)

Abstract
The pedestal effect is the large improvement in the detectabilty of a sinusoidal “signal” grating observed when the signal is added to a masking or “pedestal” grating of the same spatial frequency, orientation, and phase. We measured the pedestal effect in both broadband and notched noise - noise from which a 1.5-octave band centred on the signal frequency had been removed. Although the pedestal effect persists in broadband noise, it almost disappears in the notched noise. Furthermore, the pedestal effect is substantial when either high- or low-pass masking noise is used. We conclude that the pedestal effect in the absence of notched noise results principally from the use of information derived from channels with peak sensitivities at spatial frequencies different from that of the signal and pedestal. The spatial-frequency components of the notched noise above and below the spatial frequency of the signal and pedestal prevent the use of information about changes in contrast carried in channels tuned to spatial frequencies that are very much different from that of the signal and pedestal. Thus the pedestal or dipper effect measured without notched noise is not a characteristic of individual spatial-frequency tuned channels.

ei

Web DOI [BibTex]

Web DOI [BibTex]


no image
A Kernel Method for the Two-Sample-Problem

Gretton, A., Borgwardt, K., Rasch, M., Schölkopf, B., Smola, A.

20th Annual Conference on Neural Information Processing Systems (NIPS), December 2006 (talk)

Abstract
We propose two statistical tests to determine if two samples are from different distributions. Our test statistic is in both cases the distance between the means of the two samples mapped into a reproducing kernel Hilbert space (RKHS). The first test is based on a large deviation bound for the test statistic, while the second is based on the asymptotic distribution of this statistic. We show that the test statistic can be computed in $O(m^2)$ time. We apply our approach to a variety of problems, including attribute matching for databases using the Hungarian marriage method, where our test performs strongly. We also demonstrate excellent performance when comparing distributions over graphs, for which no alternative tests currently exist.

ei

PDF [BibTex]

PDF [BibTex]


no image
Ab-initio gene finding using machine learning

Schweikert, G., Zeller, G., Zien, A., Ong, C., de Bona, F., Sonnenburg, S., Phillips, P., Rätsch, G.

NIPS Workshop on New Problems and Methods in Computational Biology, December 2006 (talk)

ei

Web [BibTex]

Web [BibTex]


no image
Reinforcement Learning by Reward-Weighted Regression

Peters, J.

NIPS Workshop: Towards a New Reinforcement Learning? , December 2006 (talk)

ei

Web [BibTex]

Web [BibTex]


no image
Graph boosting for molecular QSAR analysis

Saigo, H., Kadowaki, T., Kudo, T., Tsuda, K.

NIPS Workshop on New Problems and Methods in Computational Biology, December 2006 (talk)

Abstract
We propose a new boosting method that systematically combines graph mining and mathematical programming-based machine learning. Informative and interpretable subgraph features are greedily found by a series of graph mining calls. Due to our mathematical programming formulation, subgraph features and pre-calculated real-valued features are seemlessly integrated. We tested our algorithm on a quantitative structure-activity relationship (QSAR) problem, which is basically a regression problem when given a set of chemical compounds. In benchmark experiments, the prediction accuracy of our method favorably compared with the best results reported on each dataset.

ei

Web [BibTex]

Web [BibTex]


no image
A New Projected Quasi-Newton Approach for the Nonnegative Least Squares Problem

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

(TR-06-54), Univ. of Texas, Austin, December 2006 (techreport)

ei

PDF [BibTex]

PDF [BibTex]


no image
Inferring Causal Directions by Evaluating the Complexity of Conditional Distributions

Sun, X., Janzing, D., Schölkopf, B.

NIPS Workshop on Causality and Feature Selection, December 2006 (talk)

Abstract
We propose a new approach to infer the causal structure that has generated the observed statistical dependences among n random variables. The idea is that the factorization of the joint measure of cause and effect into P(cause)P(effect|cause) leads typically to simpler conditionals than non-causal factorizations. To evaluate the complexity of the conditionals we have tried two methods. First, we have compared them to those which maximize the conditional entropy subject to the observed first and second moments since we consider the latter as the simplest conditionals. Second, we have fitted the data with conditional probability measures being exponents of functions in an RKHS space and defined the complexity by a Hilbert-space semi-norm. Such a complexity measure has several properties that are useful for our purpose. We describe some encouraging results with both methods applied to real-world data. Moreover, we have combined constraint-based approaches to causal discovery (i.e., methods using only information on conditional statistical dependences) with our method in order to distinguish between causal hypotheses which are equivalent with respect to the imposed independences. Furthermore, we compare the performance to Bayesian approaches to causal inference.

ei

Web [BibTex]


no image
Information-theoretic Metric Learning

Davis, J., Kulis, B., Sra, S., Dhillon, I.

In NIPS 2006 Workshop on Learning to Compare Examples, pages: 1-5, NIPS Workshop on Learning to Compare Examples, December 2006 (inproceedings)

Abstract
We formulate the metric learning problem as that of minimizing the differential relative entropy between two multivariate Gaussians under constraints on the Mahalanobis distance function. Via a surprising equivalence, we show that this problem can be solved as a low-rank kernel learning problem. Specifically, we minimize the Burg divergence of a low-rank kernel to an input kernel, subject to pairwise distance constraints. Our approach has several advantages over existing methods. First, we present a natural information-theoretic formulation for the problem. Second, the algorithm utilizes the methods developed by Kulis et al. [6], which do not involve any eigenvector computation; in particular, the running time of our method is faster than most existing techniques. Third, the formulation offers insights into connections between metric learning and kernel learning.

ei

PDF Web [BibTex]

PDF Web [BibTex]


no image
Pattern Mining in Frequent Dynamic Subgraphs

Borgwardt, KM., Kriegel, H-P., Wackersreuther, P.

In pages: 818-822, (Editors: Clifton, C.W.), IEEE Computer Society, Los Alamitos, CA, USA, Sixth International Conference on Data Mining (ICDM), December 2006 (inproceedings)

Abstract
Graph-structured data is becoming increasingly abundant in many application domains. Graph mining aims at finding interesting patterns within this data that represent novel knowledge. While current data mining deals with static graphs that do not change over time, coming years will see the advent of an increasing number of time series of graphs. In this article, we investigate how pattern mining on static graphs can be extended to time series of graphs. In particular, we are considering dynamic graphs with edge insertions and edge deletions over time. We define frequency in this setting and provide algorithmic solutions for finding frequent dynamic subgraph patterns. Existing subgraph mining algorithms can be easily integrated into our framework to make them handle dynamic graphs. Experimental results on real-world data confirm the practical feasibility of our approach.

ei

Web DOI [BibTex]

Web DOI [BibTex]


no image
Structure validation of the Josephin domain of ataxin-3: Conclusive evidence for an open conformation

Nicastro, G., Habeck, M., Masino, L., Svergun, DI., Pastore, A.

Journal of Biomolecular NMR, 36(4):267-277, December 2006 (article)

Abstract
The availability of new and fast tools in structure determination has led to a more than exponential growth of the number of structures solved per year. It is therefore increasingly essential to assess the accuracy of the new structures by reliable approaches able to assist validation. Here, we discuss a specific example in which the use of different complementary techniques, which include Bayesian methods and small angle scattering, resulted essential for validating the two currently available structures of the Josephin domain of ataxin-3, a protein involved in the ubiquitin/proteasome pathway and responsible for neurodegenerative spinocerebellar ataxia of type 3. Taken together, our results demonstrate that only one of the two structures is compatible with the experimental information. Based on the high precision of our refined structure, we show that Josephin contains an open cleft which could be directly implicated in the interaction with polyubiquitin chains and other partners.

ei

Web DOI [BibTex]

Web DOI [BibTex]


no image
Probabilistic inference for solving (PO)MDPs

Toussaint, M., Harmeling, S., Storkey, A.

(934), School of Informatics, University of Edinburgh, December 2006 (techreport)

ei

PDF [BibTex]

PDF [BibTex]


no image
A Unifying View of Wiener and Volterra Theory and Polynomial Kernel Regression

Franz, M., Schölkopf, B.

Neural Computation, 18(12):3097-3118, December 2006 (article)

Abstract
Volterra and Wiener series are perhaps the best understood nonlinear system representations in signal processing. Although both approaches have enjoyed a certain popularity in the past, their application has been limited to rather low-dimensional and weakly nonlinear systems due to the exponential growth of the number of terms that have to be estimated. We show that Volterra and Wiener series can be represented implicitly as elements of a reproducing kernel Hilbert space by utilizing polynomial kernels. The estimation complexity of the implicit representation is linear in the input dimensionality and independent of the degree of nonlinearity. Experiments show performance advantages in terms of convergence, interpretability, and system sizes that can be handled.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


no image
Minimal Logical Constraint Covering Sets

Sinz, F., Schölkopf, B.

(155), Max Planck Institute for Biological Cybernetics, Tübingen, December 2006 (techreport)

Abstract
We propose a general framework for computing minimal set covers under class of certain logical constraints. The underlying idea is to transform the problem into a mathematical programm under linear constraints. In this sense it can be seen as a natural extension of the vector quantization algorithm proposed by Tipping and Schoelkopf. We show which class of logical constraints can be cast and relaxed into linear constraints and give an algorithm for the transformation.

ei

PDF [BibTex]

PDF [BibTex]