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2011


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Projected Newton-type methods in machine learning

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

In Optimization for Machine Learning, pages: 305-330, (Editors: Sra, S., Nowozin, S. and Wright, S. J.), MIT Press, Cambridge, MA, USA, December 2011 (inbook)

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

ei

PDF Web [BibTex]

2011


PDF Web [BibTex]


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Spatiotemporal mapping of rhythmic activity in the inferior convexity of the macaque prefrontal cortex

Panagiotaropoulos, T., Besserve, M., Crocker, B., Kapoor, V., Tolias, A., Panzeri, S., Logothetis, N.

41(239.15), 41st Annual Meeting of the Society for Neuroscience (Neuroscience), November 2011 (poster)

Abstract
The inferior convexity of the macaque prefrontal cortex (icPFC) is known to be involved in higher order processing of sensory information mediating stimulus selection, attention and working memory. Until now, the vast majority of electrophysiological investigations of the icPFC employed single electrode recordings. As a result, relatively little is known about the spatiotemporal structure of neuronal activity in this cortical area. Here we study in detail the spatiotemporal properties of local field potentials (LFP's) in the icPFC using multi electrode recordings during anesthesia. We computed the LFP-LFP coherence as a function of frequency for thousands of pairs of simultaneously recorded sites anterior to the arcuate and inferior to the principal sulcus. We observed two distinct peaks of coherent oscillatory activity between approximately 4-10 and 15-25 Hz. We then quantified the instantaneous phase of these frequency bands using the Hilbert transform and found robust phase gradients across recording sites. The dependency of the phase on the spatial location reflects the existence of traveling waves of electrical activity in the icPFC. The dominant axis of these traveling waves roughly followed the ventral-dorsal plane. Preliminary results show that repeated visual stimulation with a 10s movie had no dramatic effect on the spatial structure of the traveling waves. Traveling waves of electrical activity in the icPFC could reflect highly organized cortical processing in this area of prefrontal cortex.

ei

Web [BibTex]

Web [BibTex]


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Evaluation and Optimization of MR-Based Attenuation Correction Methods in Combined Brain PET/MR

Mantlik, F., Hofmann, M., Bezrukov, I., Schmidt, H., Kolb, A., Beyer, T., Reimold, M., Schölkopf, B., Pichler, B.

2011(MIC18.M-96), 2011 IEEE Nuclear Science Symposium, Medical Imaging Conference (NSS-MIC), October 2011 (poster)

Abstract
Combined PET/MR provides simultaneous molecular and functional information in an anatomical context with unique soft tissue contrast. However, PET/MR does not support direct derivation of attenuation maps of objects and tissues within the measured PET field-of-view. Valid attenuation maps are required for quantitative PET imaging, specifically for scientific brain studies. Therefore, several methods have been proposed for MR-based attenuation correction (MR-AC). Last year, we performed an evaluation of different MR-AC methods, including simple MR thresholding, atlas- and machine learning-based MR-AC. CT-based AC served as gold standard reference. RoIs from 2 anatomic brain atlases with different levels of detail were used for evaluation of correction accuracy. We now extend our evaluation of different MR-AC methods by using an enlarged dataset of 23 patients from the integrated BrainPET/MR (Siemens Healthcare). Further, we analyze options for improving the MR-AC performance in terms of speed and accuracy. Finally, we assess the impact of ignoring BrainPET positioning aids during the course of MR-AC. This extended study confirms the overall prediction accuracy evaluation results of the first evaluation in a larger patient population. Removing datasets affected by metal artifacts from the Atlas-Patch database helped to improve prediction accuracy, although the size of the database was reduced by one half. Significant improvement in prediction speed can be gained at a cost of only slightly reduced accuracy, while further optimizations are still possible.

ei

Web [BibTex]

Web [BibTex]


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Atlas- and Pattern Recognition Based Attenuation Correction on Simultaneous Whole-Body PET/MR

Bezrukov, I., Schmidt, H., Mantlik, F., Schwenzer, N., Hofmann, M., Schölkopf, B., Pichler, B.

2011(MIC18.M-116), 2011 IEEE Nuclear Science Symposium, Medical Imaging Conference (NSS-MIC), October 2011 (poster)

Abstract
With the recent availability of clinical whole-body PET/MRI it is possible to evaluate and further develop MR-based attenuation correction methods using simultaneously acquired PET/MR data. We present first results for MRAC on patient data acquired on a fully integrated whole-body PET/MRI (Biograph mMR, Siemens) using our method that applies atlas registration and pattern recognition (ATPR) and compare them to the segmentation-based (SEG) method provided by the manufacturer. The ATPR method makes use of a database of previously aligned pairs of MR-CT volumes to predict attenuation values on a continuous scale. The robustness of the method in presence of MR artifacts was improved by location and size based detection. Lesion to liver and lesion to blood ratios (LLR and LBR) were compared for both methods on 29 iso-contour ROIs in 4 patients. ATPR showed >20% higher LBR and LLR for ROIs in and >7% near osseous tissue. For ROIs in soft tissue, both methods yielded similar ratios with max. differences <6% . For ROIs located within metal artifacts in the MR image, ATPR showed >190% higher LLR and LBR than SEG, where ratios <0.1 occured. For lesions in the neighborhood of artifacts, both ratios were >15% higher for ATPR. If artifacts in MR volumes caused by metal implants are not accounted for in the computation of attenuation maps, they can lead to a strong decrease of lesion to background ratios, even to disappearance of hot spots. Metal implants are likely to occur in the patient collective receiving combined PET/MR scans, of our first 10 patients, 3 had metal implants. Our method is currently able to account for artifacts in the pelvis caused by prostheses. The ability of the ATPR method to account for bone leads to a significant increase of LLR and LBR in osseous tissue, which supports our previous evaluations with combined PET/CT and PET/MR data. For lesions within soft tissue, lesion to background ratios of ATPR and SEG were comparable.

ei

Web [BibTex]

Web [BibTex]


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Retrospective blind motion correction of MR images

Loktyushin, A., Nickisch, H., Pohmann, R.

Magnetic Resonance Materials in Physics, Biology and Medicine, 24(Supplement 1):498, 28th Annual Scientific Meeting ESMRMB, October 2011 (poster)

Abstract
We present a retrospective method, which significantly reduces ghosting and blurring artifacts due to subject motion. No modifications to the sequence (as in [2, 3]), or the use of additional equipment (as in [1]) are required. Our method iteratively searches for the transformation, that applied to the lines in k-space -- yields the sparsest Laplacian filter output in the spatial domain.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Model based reconstruction for GRE EPI

Blecher, W., Pohmann, R., Schölkopf, B., Seeger, M.

Magnetic Resonance Materials in Physics, Biology and Medicine, 24(Supplement 1):493-494, 28th Annual Scientific Meeting ESMRMB, October 2011 (poster)

Abstract
Model based nonlinear image reconstruction methods for MRI [3] are at the heart of modern reconstruction techniques (e.g.compressed sensing [6]). In general, models are expressed as a matrix equation where y and u are column vectors of k-space and image data, X model matrix and e independent noise. However, solving the corresponding linear system is not tractable. Therefore fast nonlinear algorithms that minimize a function wrt.the unknown image are the method of choice: In this work a model for gradient echo EPI, is proposed that incorporates N/2 Ghost correction and correction for field inhomogeneities. In addition to reconstruction from full data, the model allows for sparse reconstruction, joint estimation of image, field-, and relaxation-map (like [5,8] for spiral imaging), and improved N/2 ghost correction.

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Simultaneous multimodal imaging of patients with bronchial carcinoma in a whole body MR/PET system

Brendle, C., Sauter, A., Schmidt, H., Schraml, C., Bezrukov, I., Martirosian, P., Hetzel, J., Müller, M., Claussen, C., Schwenzer, N., Pfannenberg, C.

Magnetic Resonance Materials in Physics, Biology and Medicine, 24(Supplement 1):141, 28th annual scientific meeting of the European Society for Magnetic Resonance in Medicine and Biology (ESMRB), October 2011 (poster)

Abstract
Purpose/Introduction: Lung cancer is among the most frequent cancers (1). Exact determination of tumour extent and viability is crucial for adequate therapy guidance. [18F]-FDG-PET allows accurate staging and the evaluation of therapy response based on glucose metabolism. Diffusion weighted MRI (DWI) is another promising tool for the evaluation of tumour viability (2,3). The aim of the study was the simultaneous PET-MR acquisition in lung cancer patients and correlation of PET and MR data. Subjects and Methods: Seven patients (age 38-73 years, mean 61 years) with highly suspected or known bronchial carcinoma were examined. First, a [18F]-FDG-PET/CT was performed (injected dose: 332-380 MBq). Subsequently, patients were examined at the whole-body MR/PET (Siemens Biograph mMR). The MRI is a modified 3T Verio whole body system with a magnet bore of 60 cm (max. amplitude gradients 45 mT/m, max. slew rate 200 T/m/s). Concerning the PET, the whole-body MR/PET system comprises 56 detector cassettes with a 59.4 cm transaxial and 25.8 cm axial FoV. The following parameters for PET acquisition were applied: 2 bed positions, 6 min/bed with an average uptake time of 124 min after injection (range: 110-143 min). The attenuation correction of PET data was conducted with a segmentation-based method provided by the manufacturer. Acquired PET data were reconstructed with an iterative 3D OSEM algorithm using 3 iterations and 21 subsets, Gaussian filter of 3 mm. DWI MR images were recorded simultaneously for each bed using two b-values (0/800 s/mm2). SUVmax and ADCmin were assessed in a ROI analysis. The following ratios were calculated: SUVmax(tumor)/SUVmean(liver) and ADCmin(tumor)/ADCmean(muscle). Correlation between SUV and ADC was analyzed (Pearson’s correlation). Results: Diagnostic scans could be obtained in all patients with good tumour delineation. The spatial matching of PET and DWI data was very exact. Most tumours showed a pronounced FDG-uptake in combination with decreased ADC values. Significant correlation was found between SUV and ADC ratios (r = -0.87, p = 0.0118). Discussion/Conclusion: Simultaneous MR/PET imaging of lung cancer is feasible. The whole-body MR/PET system can provide complementary information regarding tumour viability and cellularity which could facilitate a more profound tumour characterization. Further studies have to be done to evaluate the importance of these parameters for therapy decisions and monitoring

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Statistical Learning Theory: Models, Concepts, and Results

von Luxburg, U., Schölkopf, B.

In Handbook of the History of Logic, Vol. 10: Inductive Logic, 10, pages: 651-706, (Editors: Gabbay, D. M., Hartmann, S. and Woods, J. H.), Elsevier North Holland, Amsterdam, Netherlands, May 2011 (inbook)

Abstract
Statistical learning theory provides the theoretical basis for many of today's machine learning algorithms and is arguably one of the most beautifully developed branches of artificial intelligence in general. It originated in Russia in the 1960s and gained wide popularity in the 1990s following the development of the so-called Support Vector Machine (SVM), which has become a standard tool for pattern recognition in a variety of domains ranging from computer vision to computational biology. Providing the basis of new learning algorithms, however, was not the only motivation for developing statistical learning theory. It was just as much a philosophical one, attempting to answer the question of what it is that allows us to draw valid conclusions from empirical data. In this article we attempt to give a gentle, non-technical overview over the key ideas and insights of statistical learning theory. We do not assume that the reader has a deep background in mathematics, statistics, or computer science. Given the nature of the subject matter, however, some familiarity with mathematical concepts and notations and some intuitive understanding of basic probability is required. There exist many excellent references to more technical surveys of the mathematics of statistical learning theory: the monographs by one of the founders of statistical learning theory ([Vapnik, 1995], [Vapnik, 1998]), a brief overview over statistical learning theory in Section 5 of [Sch{\"o}lkopf and Smola, 2002], more technical overview papers such as [Bousquet et al., 2003], [Mendelson, 2003], [Boucheron et al., 2005], [Herbrich and Williamson, 2002], and the monograph [Devroye et al., 1996].

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Crowdsourcing for optimisation of deconvolution methods via an iPhone application

Lang, A.

Hochschule Reutlingen, Germany, April 2011 (mastersthesis)

ei

[BibTex]

[BibTex]


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Robot Learning

Peters, J., Tedrake, R., Roy, N., Morimoto, J.

In Encyclopedia of Machine Learning, pages: 865-869, Encyclopedia of machine learning, (Editors: Sammut, C. and Webb, G. I.), Springer, New York, NY, USA, January 2011 (inbook)

ei

PDF Web DOI [BibTex]

PDF Web DOI [BibTex]


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Support Vector Machines for finding deletions and short insertions using paired-end short reads

Grimm, D., Hagmann, J., König, D., Weigel, D., Borgwardt, KM.

International Conference on Intelligent Systems for Molecular Biology (ISMB), 2011 (poster)

ei

Web [BibTex]

Web [BibTex]


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What You Expect Is What You Get? Potential Use of Contingent Negative Variation for Passive BCI Systems in Gaze-Based HCI

Ihme, K., Zander, TO.

In Affective Computing and Intelligent Interaction, 6975, pages: 447-456, Lecture Notes in Computer Science, (Editors: D’Mello, S., Graesser, A., Schuller, B. and Martin, J.-C.), Springer, Berlin, Germany, 2011 (inbook)

Abstract
When using eye movements for cursor control in human-computer interaction (HCI), it may be difficult to find an appropriate substitute for the click operation. Most approaches make use of dwell times. However, in this context the so-called Midas-Touch-Problem occurs which means that the system wrongly interprets fixations due to long processing times or spontaneous dwellings of the user as command. Lately it has been shown that brain-computer interface (BCI) input bears good prospects to overcome this problem using imagined hand movements to elicit a selection. The current approach tries to develop this idea further by exploring potential signals for the use in a passive BCI, which would have the advantage that the brain signals used as input are generated automatically without conscious effort of the user. To explore event-related potentials (ERPs) giving information about the user’s intention to select an object, 32-channel electroencephalography (EEG) was recorded from ten participants interacting with a dwell-time-based system. Comparing ERP signals during the dwell time with those occurring during fixations on a neutral cross hair, a sustained negative slow cortical potential at central electrode sites was revealed. This negativity might be a contingent negative variation (CNV) reflecting the participants’ anticipation of the upcoming selection. Offline classification suggests that the CNV is detectable in single trial (mean accuracy 74.9 %). In future, research on the CNV should be accomplished to ensure its stable occurence in human-computer interaction and render possible its use as a potential substitue for the click operation.

ei

DOI [BibTex]

DOI [BibTex]


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Kernel Methods in Bioinformatics

Borgwardt, KM.

In Handbook of Statistical Bioinformatics, pages: 317-334, Springer Handbooks of Computational Statistics ; 3, (Editors: Lu, H.H.-S., Schölkopf, B. and Zhao, H.), Springer, Berlin, Germany, 2011 (inbook)

Abstract
Kernel methods have now witnessed more than a decade of increasing popularity in the bioinformatics community. In this article, we will compactly review this development, examining the areas in which kernel methods have contributed to computational biology and describing the reasons for their success.

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Statistical estimation for optimization problems on graphs

Langovoy, M., Sra, S.

Empirical Inference Symposium, 2011 (poster)

ei

[BibTex]


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Cue Combination: Beyond Optimality

Rosas, P., Wichmann, F.

In Sensory Cue Integration, pages: 144-152, (Editors: Trommershäuser, J., Körding, K. and Landy, M. S.), Oxford University Press, 2011 (inbook)

ei

[BibTex]

[BibTex]


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Model Learning in Robot Control

Nguyen-Tuong, D.

Albert-Ludwigs-Universität Freiburg, Germany, 2011 (phdthesis)

ei

[BibTex]

[BibTex]


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Transfer Learning with Copulas

Lopez-Paz, D., Hernandez-Lobato, J.

Neural Information Processing Systems (NIPS), 2011 (poster)

ei

PDF [BibTex]

PDF [BibTex]


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Iterative path integral stochastic optimal control: Theory and applications to motor control

Theodorou, E. A.

University of Southern California, University of Southern California, Los Angeles, CA, 2011 (phdthesis)

am

PDF [BibTex]

PDF [BibTex]


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Learning of grasp selection based on shape-templates

Herzog, A.

Karlsruhe Institute of Technology, 2011 (mastersthesis)

am

[BibTex]

[BibTex]


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Automated Control of AFM Based Nanomanipulation

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

In Atomic Force Microscopy Based Nanorobotics, pages: 237-311, Springer Berlin Heidelberg, 2011 (incollection)

pi

[BibTex]

[BibTex]


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Ferromagnetism of ZnO influenced by physical and chemical treatment

Chen, Y.

Universität Stuttgart, Stuttgart, 2011 (mastersthesis)

mms

[BibTex]

[BibTex]


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Herstellung und Charakterisierung von ultradünnen, funktionellen CoFeB Filmen

Streckenbach, F.

Hochschule Esslingen / Hochschule Aalen, Esslingen / Aalen, 2011 (mastersthesis)

mms

[BibTex]

[BibTex]


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Hydrogen adsorption on metal-organic frameworks

Streppel, B.

Universität Stuttgart, Stuttgart, 2011 (phdthesis)

mms

link (url) [BibTex]

link (url) [BibTex]


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Teleoperation Based AFM Manipulation Control

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

In Atomic Force Microscopy Based Nanorobotics, pages: 145-235, Springer Berlin Heidelberg, 2011 (incollection)

pi

[BibTex]

[BibTex]


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Descriptions and challenges of AFM based nanorobotic systems

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

In Atomic Force Microscopy Based Nanorobotics, pages: 13-29, Springer Berlin Heidelberg, 2011 (incollection)

pi

[BibTex]

[BibTex]


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Tipping the Scales: Guidance and Intrinsically Motivated Behavior

Martius, G., Herrmann, J. M.

In Advances in Artificial Life, ECAL 2011, pages: 506-513, (Editors: Tom Lenaerts and Mario Giacobini and Hugues Bersini and Paul Bourgine and Marco Dorigo and René Doursat), MIT Press, 2011 (incollection)

al

[BibTex]

[BibTex]


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Benchmark datasets for pose estimation and tracking

Andriluka, M., Sigal, L., Black, M. J.

In Visual Analysis of Humans: Looking at People, pages: 253-274, (Editors: Moesland and Hilton and Kr"uger and Sigal), Springer-Verlag, London, 2011 (incollection)

ps

publisher's site Project Page [BibTex]

publisher's site Project Page [BibTex]


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Piezo driven strain effects on magneto-crystalline anisotropy

Badr, E.

Universität Stuttgart, Stuttgart, 2011 (mastersthesis)

mms

[BibTex]

[BibTex]


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Magnetooptische Untersuchungen an granularen und beschichteten MgB2 Filmen

Stahl, C.

Universität Stuttgart, Stuttgart, 2011 (mastersthesis)

mms

[BibTex]

[BibTex]


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Mikromagnetismus der Wechselwirkung von Spinwellen mit Domänenwänden in Ferromagneten

Macke, S.

Universität Stuttgart, Stuttgart, 2011 (phdthesis)

mms

[BibTex]

[BibTex]


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Applications of AFM Based Nanorobotic Systems

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

In Atomic Force Microscopy Based Nanorobotics, pages: 313-342, Springer Berlin Heidelberg, 2011 (incollection)

pi

[BibTex]

[BibTex]


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Steerable random fields for image restoration and inpainting

Roth, S., Black, M. J.

In Markov Random Fields for Vision and Image Processing, pages: 377-387, (Editors: Blake, A. and Kohli, P. and Rother, C.), MIT Press, 2011 (incollection)

Abstract
This chapter introduces the concept of a Steerable Random Field (SRF). In contrast to traditional Markov random field (MRF) models in low-level vision, the random field potentials of a SRF are defined in terms of filter responses that are steered to the local image structure. This steering uses the structure tensor to obtain derivative responses that are either aligned with, or orthogonal to, the predominant local image structure. Analysis of the statistics of these steered filter responses in natural images leads to the model proposed here. Clique potentials are defined over steered filter responses using a Gaussian scale mixture model and are learned from training data. The SRF model connects random fields with anisotropic regularization and provides a statistical motivation for the latter. Steering the random field to the local image structure improves image denoising and inpainting performance compared with traditional pairwise MRFs.

ps

publisher site [BibTex]

publisher site [BibTex]


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Herstellung und Qualifizierung gesputterter Magnesiumdiboridschichten

Breyer, F.

Hochschule Aalen, Aalen, 2011 (mastersthesis)

mms

[BibTex]

[BibTex]


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Nanomechanics of AFM based nanomanipulation

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

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

pi

[BibTex]

[BibTex]


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Instrumentation Issues of an AFM Based Nanorobotic System

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

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

pi

[BibTex]

[BibTex]


no image
Projected Newton-type methods in machine learning

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

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

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

mms

link (url) [BibTex]

link (url) [BibTex]


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Study of krypton/xenon storage and separation in microporous frameworks

Soleimani Dorcheh, A.

Universität Darmstadt, Darmstadt, 2011 (mastersthesis)

mms

[BibTex]

[BibTex]

2005


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Extension to Kernel Dependency Estimation with Applications to Robotics

BakIr, G.

Biologische Kybernetik, Technische Universität Berlin, Berlin, November 2005 (phdthesis)

Abstract
Kernel Dependency Estimation(KDE) is a novel technique which was designed to learn mappings between sets without making assumptions on the type of the involved input and output data. It learns the mapping in two stages. In a first step, it tries to estimate coordinates of a feature space representation of elements of the set by solving a high dimensional multivariate regression problem in feature space. Following this, it tries to reconstruct the original representation given the estimated coordinates. This thesis introduces various algorithmic extensions to both stages in KDE. One of the contributions of this thesis is to propose a novel linear regression algorithm that explores low-dimensional subspaces during learning. Furthermore various existing strategies for reconstructing patterns from feature maps involved in KDE are discussed and novel pre-image techniques are introduced. In particular, pre-image techniques for data-types that are of discrete nature such as graphs and strings are investigated. KDE is then explored in the context of robot pose imitation where the input is a an image with a human operator and the output is the robot articulated variables. Thus, using KDE, robot pose imitation is formulated as a regression problem.

ei

PDF PDF [BibTex]

2005


PDF PDF [BibTex]


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Kernel methods for dependence testing in LFP-MUA

Gretton, A., Belitski, A., Murayama, Y., Schölkopf, B., Logothetis, N.

35(689.17), 35th Annual Meeting of the Society for Neuroscience (Neuroscience), November 2005 (poster)

Abstract
A fundamental problem in neuroscience is determining whether or not particular neural signals are dependent. The correlation is the most straightforward basis for such tests, but considerable work also focuses on the mutual information (MI), which is capable of revealing dependence of higher orders that the correlation cannot detect. That said, there are other measures of dependence that share with the MI an ability to detect dependence of any order, but which can be easier to compute in practice. We focus in particular on tests based on the functional covariance, which derive from work originally accomplished in 1959 by Renyi. Conceptually, our dependence tests work by computing the covariance between (infinite dimensional) vectors of nonlinear mappings of the observations being tested, and then determining whether this covariance is zero - we call this measure the constrained covariance (COCO). When these vectors are members of universal reproducing kernel Hilbert spaces, we can prove this covariance to be zero only when the variables being tested are independent. The greatest advantage of these tests, compared with the mutual information, is their simplicity – when comparing two signals, we need only take the largest eigenvalue (or the trace) of a product of two matrices of nonlinearities, where these matrices are generally much smaller than the number of observations (and are very simple to construct). We compare the mutual information, the COCO, and the correlation in the context of finding changes in dependence between the LFP and MUA signals in the primary visual cortex of the anaesthetized macaque, during the presentation of dynamic natural stimuli. We demonstrate that the MI and COCO reveal dependence which is not detected by the correlation alone (which we prove by artificially removing all correlation between the signals, and then testing their dependence with COCO and the MI); and that COCO and the MI give results consistent with each other on our data.

ei

Web [BibTex]

Web [BibTex]


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Geometrical aspects of statistical learning theory

Hein, M.

Biologische Kybernetik, Darmstadt, Darmstadt, November 2005 (phdthesis)

ei

PDF [BibTex]

PDF [BibTex]


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Implicit Surfaces For Modelling Human Heads

Steinke, F.

Biologische Kybernetik, Eberhard-Karls-Universität, Tübingen, September 2005 (diplomathesis)

ei

[BibTex]

[BibTex]


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Rapid animal detection in natural scenes: Critical features are local

Wichmann, F., Rosas, P., Gegenfurtner, K.

Journal of Vision, 5(8):376, Fifth Annual Meeting of the Vision Sciences Society (VSS), September 2005 (poster)

Abstract
Thorpe et al (Nature 381, 1996) first showed how rapidly human observers are able to classify natural images as to whether they contain an animal or not. Whilst the basic result has been replicated using different response paradigms (yes-no versus forced-choice), modalities (eye movements versus button presses) as well as while measuring neurophysiological correlates (ERPs), it is still unclear which image features support this rapid categorisation. Recently Torralba and Oliva (Network: Computation in Neural Systems, 14, 2003) suggested that simple global image statistics can be used to predict seemingly complex decisions about the absence and/or presence of objects in natural scences. They show that the information contained in a small number (N=16) of spectral principal components (SPC)—principal component analysis (PCA) applied to the normalised power spectra of the images—is sufficient to achieve approximately 80% correct animal detection in natural scenes. Our goal was to test whether human observers make use of the power spectrum when rapidly classifying natural scenes. We measured our subjects' ability to detect animals in natural scenes as a function of presentation time (13 to 167 msec); images were immediately followed by a noise mask. In one condition we used the original images, in the other images whose power spectra were equalised (each power spectrum was set to the mean power spectrum over our ensemble of 1476 images). Thresholds for 75% correct animal detection were in the region of 20–30 msec for all observers, independent of the power spectrum of the images: this result makes it very unlikely that human observers make use of the global power spectrum. Taken together with the results of Gegenfurtner, Braun & Wichmann (Journal of Vision [abstract], 2003), showing the robustness of animal detection to global phase noise, we conclude that humans use local features, like edges and contours, in rapid animal detection.

ei

Web DOI [BibTex]

Web DOI [BibTex]


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Learning an Interest Operator from Eye Movements

Kienzle, W., Franz, M., Wichmann, F., Schölkopf, B.

International Workshop on Bioinspired Information Processing (BIP 2005), 2005, pages: 1, September 2005 (poster)

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Machine Learning Methods for Brain-Computer Interdaces

Lal, TN.

Biologische Kybernetik, University of Darmstadt, September 2005 (phdthesis)

ei

Web [BibTex]

Web [BibTex]


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Classification of natural scenes using global image statistics

Drewes, J., Wichmann, F., Gegenfurtner, K.

Journal of Vision, 5(8):602, Fifth Annual Meeting of the Vision Sciences Society (VSS), September 2005 (poster)

Abstract
The algorithmic classification of complex, natural scenes is generally considered a difficult task due to the large amount of information conveyed by natural images. Work by Simon Thorpe and colleagues showed that humans are capable of detecting animals within novel natural scenes with remarkable speed and accuracy. This suggests that the relevant information for classification can be extracted at comparatively limited computational cost. One hypothesis is that global image statistics such as the amplitude spectrum could underly fast image classification (Johnson & Olshausen, Journal of Vision, 2003; Torralba & Oliva, Network: Comput. Neural Syst., 2003). We used linear discriminant analysis to classify a set of 11.000 images into animal and non-animal images. After applying a DFT to the image, we put the Fourier spectrum into bins (8 orientations with 6 frequency bands each). Using all bins, classification performance on the Fourier spectrum reached 70%. However, performance was similar (67%) when only the high spatial frequency information was used and decreased steadily at lower spatial frequencies, reaching a minimum (50%) for the low spatial frequency information. Similar results were obtained when all bins were used on spatially filtered images. A detailed analysis of the classification weights showed that a relatively high level of performance (67%) could also be obtained when only 2 bins were used, namely the vertical and horizontal orientation at the highest spatial frequency band. Our results show that in the absence of sophisticated machine learning techniques, animal detection in natural scenes is limited to rather modest levels of performance, far below those of human observers. If limiting oneself to global image statistics such as the DFT then mostly information at the highest spatial frequencies is useful for the task. This is analogous to the results obtained with human observers on filtered images (Kirchner et al, VSS 2004).

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Web DOI [BibTex]

Web DOI [BibTex]