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67 results (View BibTeX file of all listed publications)

2015

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Causal Inference for Empirical Time Series Based on the Postulate of Independence of Cause and Mechanism

Besserve, M.

53rd Annual Allerton Conference on Communication, Control, and Computing, September 2015 (talk)

[BibTex]

2015

Besserve, M. Causal Inference for Empirical Time Series Based on the Postulate of Independence of Cause and Mechanism 53rd Annual Allerton Conference on Communication, Control, and Computing, September 2015 (talk)

[BibTex]

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Independence of cause and mechanism in brain networks

Besserve, M.

DALI workshop on Networks: Processes and Causality, April 2015 (talk)

[BibTex]

Besserve, M. Independence of cause and mechanism in brain networks DALI workshop on Networks: Processes and Causality, April 2015 (talk)

[BibTex]

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Information-Theoretic Implications of Classical and Quantum Causal Structures

Chaves, R., Majenz, C., Luft, L., Maciel, T., Janzing, D., Schölkopf, B., Gross, D.

18th Conference on Quantum Information Processing (QIP), 2015 (talk)

Web link (url) [BibTex]

Chaves, R., Majenz, C., Luft, L., Maciel, T., Janzing, D., Schölkopf, B., Gross, D. Information-Theoretic Implications of Classical and Quantum Causal Structures 18th Conference on Quantum Information Processing (QIP), 2015 (talk)

Web link (url) [BibTex]

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Assessment of brain tissue damage in the Sub-Acute Stroke Region by Multiparametric Imaging using [89-Zr]-Desferal-EPO-PET/MRI

Castaneda, S. G., Katiyar, P., Russo, F., Disselhorst, J. A., Calaminus, C., Poli, S., Maurer, A., Ziemann, U., Pichler, B. J.

World Molecular Imaging Conference, 2015 (talk)

[BibTex]

Castaneda, S. G., Katiyar, P., Russo, F., Disselhorst, J. A., Calaminus, C., Poli, S., Maurer, A., Ziemann, U., Pichler, B. J. Assessment of brain tissue damage in the Sub-Acute Stroke Region by Multiparametric Imaging using [89-Zr]-Desferal-EPO-PET/MRI World Molecular Imaging Conference, 2015 (talk)

[BibTex]

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Early time point in vivo PET/MR is a promising biomarker for determining efficacy of a novel Db(\alphaEGFR)-scTRAIL fusion protein therapy in a colon cancer model

Divine, M. R., Harant, M., Katiyar, P., Disselhorst, J. A., Bukala, D., Aidone, S., Siegemund, M., Pfizenmaier, K., Kontermann, R., Pichler, B. J.

World Molecular Imaging Conference, 2015 (talk)

[BibTex]

Divine, M. R., Harant, M., Katiyar, P., Disselhorst, J. A., Bukala, D., Aidone, S., Siegemund, M., Pfizenmaier, K., Kontermann, R., Pichler, B. J. Early time point in vivo PET/MR is a promising biomarker for determining efficacy of a novel Db(\alphaEGFR)-scTRAIL fusion protein therapy in a colon cancer model World Molecular Imaging Conference, 2015 (talk)

[BibTex]

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Cosmology from Cosmic Shear with DES Science Verification Data

Abbott, T., Abdalla, F. B., Allam, S., Amara, A., Annis, J., Armstrong, R., Bacon, D., Banerji, M., Bauer, A. H., Baxter, E., others,

arXiv preprint arXiv:1507.05552, 2015 (techreport)

link (url) [BibTex]

Abbott, T., Abdalla, F. B., Allam, S., Amara, A., Annis, J., Armstrong, R., Bacon, D., Banerji, M., Bauer, A. H., Baxter, E., others, Cosmology from Cosmic Shear with DES Science Verification Data arXiv preprint arXiv:1507.05552, 2015 (techreport)

link (url) [BibTex]

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The DES Science Verification Weak Lensing Shear Catalogs

Jarvis, M., Sheldon, E., Zuntz, J., Kacprzak, T., Bridle, S. L., Amara, A., Armstrong, R., Becker, M. R., Bernstein, G. M., Bonnett, C., others,

arXiv preprint arXiv:1507.05603, 2015 (techreport)

link (url) [BibTex]

Jarvis, M., Sheldon, E., Zuntz, J., Kacprzak, T., Bridle, S. L., Amara, A., Armstrong, R., Becker, M. R., Bernstein, G. M., Bonnett, C., others, The DES Science Verification Weak Lensing Shear Catalogs arXiv preprint arXiv:1507.05603, 2015 (techreport)

link (url) [BibTex]

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The search for single exoplanet transits in the Kepler light curves

Foreman-Mackey, D., Hogg, D. W., Schölkopf, B.

IAU General Assembly, 22, pages: 2258352, 2015 (talk)

link (url) [BibTex]

Foreman-Mackey, D., Hogg, D. W., Schölkopf, B. The search for single exoplanet transits in the Kepler light curves IAU General Assembly, 22, pages: 2258352, 2015 (talk)

link (url) [BibTex]

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Unsupervised identification of neural events in local field potentials

Besserve, M., Schölkopf, B., Logothetis, N. K.

44th Annual Meeting of the Society for Neuroscience (Neuroscience), 2014 (talk)

[BibTex]

Besserve, M., Schölkopf, B., Logothetis, N. K. Unsupervised identification of neural events in local field potentials 44th Annual Meeting of the Society for Neuroscience (Neuroscience), 2014 (talk)

[BibTex]

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Quantifying statistical dependency

Besserve, M.

Research Network on Learning Systems Summer School, 2014 (talk)

[BibTex]

Besserve, M. Quantifying statistical dependency Research Network on Learning Systems Summer School, 2014 (talk)

[BibTex]

2011

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Combined whole-body PET/MR imaging: MR contrast agents do not affect the quantitative accuracy of PET following attenuation correction

Lois, C., Kupferschläger, J., Bezrukov, I., Schmidt, H., Werner, M., Mannheim, J., Pichler, B., Schwenzer, N., Beyer, T.

(SST15-05 ), 97th Scientific Assemble and Annual Meeting of the Radiological Society of North America (RSNA), December 2011 (talk)

Abstract
PURPOSE Combined PET/MR imaging entails the use of MR contrast agents (MRCA) as part of integrated protocols. We assess additional attenuation of the PET emission signals in the presence of oral and intraveneous (iv) MRCA made up of iron oxide and Gd-chelates, respectively. METHOD AND MATERIALS Phantom scans were performed on a clinical PET/CT (Biograph HiRez16, Siemens) and integrated whole-body PET/MR (Biograph mMR, Siemens) using oral (Lumirem) and intraveneous (Gadovist) MRCA. Reference PET attenuation values were determined on a small-animal PET (Inveon, Siemens) using standard PET transmission imaging (TX). Seven syringes of 5mL were filled with (a) Water, (b) Lumirem_100 (100% conc.), (c) Gadovist_100 (100%), (d) Gadovist_18 (18%), (e) Gadovist_02 (0.2%), (f) Imeron-400 CT iv-contrast (100%) and (g) Imeron-400 (2.4%). The same set of syringes was scanned on CT (Sensation16, Siemens) at 120kVp and 160mAs. The effect of MRCA on the attenuation of PET emission data was evaluated using a 20cm cylinder filled uniformly with [18F]-FDG (FDG) in water (BGD). Three 4.5cm diameter cylinders were inserted into the phantom: (C1) Teflon, (C2) Water+FDG (2:1) and (C3) Lumirem_100+FDG (2:1). Two 50mL syringes filled with Gadovist_02+FDG (Sy1) and water+FDG (Sy2) were attached to the sides of (C1) to mimick the effects of iv-contrast in vessels near bone. Syringe-to-background activity ratio was 4-to-1. PET emission data were acquired for 10min each using the PET/CT and the PET/MR. Images were reconstructed using CT- and MR-based attenuation correction. RESULTS Mean linear PET attenuation (cm-1) on TX was (a) 0.098, (b) 0.098, (c) 0.300, (d) 0.134, (e) 0.095, (f) 0.397 and (g) 0.105. Corresponding CT attenuation (HU) was: (a) 5, (b) 14, (c) 3070, (d) 1040, (e) 13, (f) 3070 and (g) 347. Lumirem had little effect on PET attenuation with (C3) being 13% and 10% higher than (C2) on PET/CT and PET/MR, respectively. Gadovist_02 had even smaller effects with (Sy1) being 2.5% lower than (Sy2) on PET/CT and 1.2% higher than (Sy2) on PET/MR. CONCLUSION MRCA in high and clinically relevant concentrations have attenuation values similar to that of CT contrast and water, respectively. In clinical PET/MR scenarios MRCA are not expected to lead to significant attenuation of the PET emission signals.

Web [BibTex]

2011

Lois, C., Kupferschläger, J., Bezrukov, I., Schmidt, H., Werner, M., Mannheim, J., Pichler, B., Schwenzer, N., Beyer, T. Combined whole-body PET/MR imaging: MR contrast agents do not affect the quantitative accuracy of PET following attenuation correction (SST15-05 ), 97th Scientific Assemble and Annual Meeting of the Radiological Society of North America (RSNA), December 2011 (talk)

Web [BibTex]

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Cooperative Cuts: a new use of submodularity in image segmentation

Jegelka, S.

Second I.S.T. Austria Symposium on Computer Vision and Machine Learning, October 2011 (talk)

Web [BibTex]

Jegelka, S. Cooperative Cuts: a new use of submodularity in image segmentation Second I.S.T. Austria Symposium on Computer Vision and Machine Learning, October 2011 (talk)

Web [BibTex]

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Effect of MR Contrast Agents on Quantitative Accuracy of PET in Combined Whole-Body PET/MR Imaging

Lois, C., Bezrukov, I., Schmidt, H., Schwenzer, N., Werner, M., Pichler, B., Kupferschläger, J., Beyer, T.

2011(MIC3-3), 2011 IEEE Nuclear Science Symposium, Medical Imaging Conference (NSS-MIC), October 2011 (talk)

Abstract
Combined whole-body PET/MR systems are being tested in clinical practice today. Integrated imaging protocols entail the use of MR contrast agents (MRCA) that could bias PET attenuation correction. In this work, we assess the effect of MRCA in PET/MR imaging. We analyze the effect of oral and intravenous MRCA on PET activity after attenuation correction. We conclude that in clinical scenarios, MRCA are not expected to lead to significant attenuation of PET signals, and that attenuation maps are not biased after the ingestion of adequate oral contrasts.

Web [BibTex]

Lois, C., Bezrukov, I., Schmidt, H., Schwenzer, N., Werner, M., Pichler, B., Kupferschläger, J., Beyer, T. Effect of MR Contrast Agents on Quantitative Accuracy of PET in Combined Whole-Body PET/MR Imaging 2011(MIC3-3), 2011 IEEE Nuclear Science Symposium, Medical Imaging Conference (NSS-MIC), October 2011 (talk)

Web [BibTex]

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First Results on Patients and Phantoms of a Fully Integrated Clinical Whole-Body PET/MRI

Schmidt, H., Schwenzer, N., Bezrukov, I., Kolb, A., Mantlik, F., Kupferschläger, J., Lois, C., Sauter, A., Brendle, C., Pfannenberg, C., Pichler, B.

2011(J2-8), 2011 IEEE Nuclear Science Symposium, Medical Imaging Conference (NSS-MIC), October 2011 (talk)

Abstract
First clinical fully integrated whole-body PET/MR scanners are just entering the field. Here, we present studies toward quantification accuracy and variation within the PET field of view of small lesions from our BrainPET/MRI, a dedicated clinical brain scanner which was installed three years ago in Tbingen. Also, we present first results for patient and phantom scans of a fully integral whole-body PET/MRI, which was installed two months ago at our department. The quantification accuracy and homogeneity of the BrainPET-Insert (Siemens Medical Solutions, Germany) installed inside the magnet bore of a clinical 3T MRI scanner (Magnetom TIM Trio, Siemens Medical Solutions, Germany) was evaluated by using eight hollow spheres with inner diameters from 3.95 to 7.86 mm placed at different positions inside a homogeneous cylinder phantom with an 9:1 and 6:1 sphere to background ratio. The quantification accuracy for small lesions at different positions in the PET FoV shows a standard deviation of up to 11% and is acceptable for quantitative brain studies where the homogeneity of quantification on the entire FoV is essental. Image quality and resolution of the new Siemens whole-body PET/MR system (Biograph mMR, Siemens Medical Solutions, Germany) was evaluated according to the NEMA NU2 2007 protocol using a body phantom containing six spheres with inner diameter from 10 to 37 mm at sphere to background ratios of 8:1 and 4:1 and the F-18 point sources located at different positions inside the PET FoV, respectively. The evaluation of the whole-body PET/MR system reveals a good PET image quality and resolution comparable to state-of-the-art clinical PET/CT scanners. First images of patient studies carried out at the whole-body PET/MR are presented highlighting the potency of combined PET/MR imaging.

Web [BibTex]

Schmidt, H., Schwenzer, N., Bezrukov, I., Kolb, A., Mantlik, F., Kupferschläger, J., Lois, C., Sauter, A., Brendle, C., Pfannenberg, C., Pichler, B. First Results on Patients and Phantoms of a Fully Integrated Clinical Whole-Body PET/MRI 2011(J2-8), 2011 IEEE Nuclear Science Symposium, Medical Imaging Conference (NSS-MIC), October 2011 (talk)

Web [BibTex]

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Effect of MR contrast agents on quantitative accuracy of PET in combined whole-body PET/MR imaging

Lois, C., Kupferschläger, J., Bezrukov, I., Schmidt, H., Werner, M., Mannheim, J., Pichler, B., Schwenzer, N., Beyer, T.

(OP314), Annual Congress of the European Association of Nuclear Medicine (EANM), October 2011 (talk)

Abstract
PURPOSE:Combined PET/MR imaging entails the use of MR contrast agents (MRCA) as part of integrated protocols. MRCA are made up of iron oxide and Gd-chelates for oral and intravenous (iv) application, respectively. We assess additional attenuation of the PET emission signals in the presence of oral and iv MRCA.MATERIALS AND METHODS:Phantom scans were performed on a clinical PET/CT (Biograph HiRez16, Siemens) and an integrated whole-body PET/MR (Biograph mMR, Siemens). Two common MRCA were evaluated: Lumirem (oral) and Gadovist (iv).Reference PET attenuation values were determined on a dedicated small-animal PET (Inveon, Siemens) using equivalent standard PET transmission source imaging (TX). Seven syringes of 5mL were filled with (a) Water, (b) Lumirem_100 (100% concentration), (c) Gadovist_100 (100%), (d) Gadovist_18 (18%), (e) Gadovist_02 (0.2%), (f) Imeron-400 CT iv-contrast (100%) and (g) Imeron-400 (2.4%). The same set of syringes was scanned on CT (Sensation16, Siemens) at 120kVp and 160mAs.The effect of MRCA on the attenuation of PET emission data was evaluated using a 20cm cylinder filled uniformly with [18F]-FDG (FDG) in water (BGD). Three 4.5cm diameter cylinders were inserted into the phantom: (C1) Teflon, (C2) Water+FDG (2:1) and (C3) Lumirem_100+FDG (2:1). Two 50mL syringes filled with Gadovist_02+FDG (Sy1) and water+FDG (Sy2) were attached to the sides of (C1) to mimick the effects of iv-contrast in vessels near bone. Syringe-to-background activity ratio was 4-to-1.PET emission data were acquired for 10min each using the PET/CT and the PET/MR. Images were reconstructed using CT- and MR-based attenuation correction (AC). Since Teflon is not correctly identified on MR, PET(/MR) data were reconstructed using MR-AC and CT-AC.RESULTS:Mean linear PET attenuation (cm-1) on TX was (a) 0.098, (b) 0.098, (c) 0.300, (d) 0.134, (e) 0.095, (f) 0.397 and (g) 0.105. Corresponding CT attenuation (HU) was: (a) 5, (b) 14, (c) 3070, (d) 1040, (e) 13, (f) 3070 and (g) 347.Lumirem had little effect on PET attenuation with (C3) being 13%, 10% and 11% higher than (C2) on PET/CT, PET/MR with MR-AC, and PET/MR with CT-AC, respectively. Gadovist_02 had even smaller effects with (Sy1) being 2.5% lower, 1.2% higher, and 3.5% lower than (Sy2) on PET/CT, PET/MR with MR-AC and PET/MR with CT-AC, respectively.CONCLUSION:MRCA in high and clinically relevant concentrations have attenuation values similar to that of CT contrast and water, respectively. In clinical PET/MR scenarios MRCA are not expected to lead to significant attenuation of the PET emission signals.

Web [BibTex]

Lois, C., Kupferschläger, J., Bezrukov, I., Schmidt, H., Werner, M., Mannheim, J., Pichler, B., Schwenzer, N., Beyer, T. Effect of MR contrast agents on quantitative accuracy of PET in combined whole-body PET/MR imaging (OP314), Annual Congress of the European Association of Nuclear Medicine (EANM), October 2011 (talk)

Web [BibTex]

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Multi-parametric Tumor Characterization and Therapy Monitoring using Simultaneous PET/MRI: initial results for Lung Cancer and GvHD

Sauter, A., Schmidt, H., Gueckel, B., Brendle, C., Bezrukov, I., Mantlik, F., Kolb, A., Mueller, M., Reimold, M., Federmann, B., Hetzel, J., Claussen, C., Pfannenberg, C., Horger, M., Pichler, B., Schwenzer, N.

(T110), 2011 World Molecular Imaging Congress (WMIC), September 2011 (talk)

Abstract
Hybrid imaging modalities such as [18F]FDG-PET/CT are superior in staging of e.g. lung cancer disease compared with stand-alone modalities. Clinical PET/MRI systems are about to enter the field of hybrid imaging and offer potential advantages. One added value could be a deeper insight into the tumor metabolism and tumorigenesis due to the combination of PET and dedicated MR methods such as MRS and DWI. Additionally, therapy monitoring of diffucult to diagnose disease such as chronic sclerodermic GvHD (csGvHD) can potentially be improved by this combination. We have applied PET/MRI in 3 patients with lung cancer and 4 patients with csGvHD before and during therapy. All 3 patients had lung cancer confirmed by histology (2 adenocarcinoma, 1 carcinoid). First, a [18F]FDG-PET/CT was performed with the following parameters: injected dose 351.7±25.1 MBq, uptake time 59.0±2.6 min, 3 min/bed. Subsequently, patients were brought to the PET/MRI imaging facility. The whole-body PET/MRI Biograph mMR system comprises 56 detector cassettes with a 59.4 cm transaxial and 25.8 cm axial FoV. The MRI is a modified Verio system with a magnet bore of 60 cm. The following parameters for PET acquisition were applied: uptake time 121.3±2.3 min, 3 bed positions, 6 min/bed. T1w, T2w, and DWI MR images were recorded simultaneously for each bed. Acquired PET data were reconstructed with an iterative 3D OSEM algorithm using 3 iterations and 21 subsets, Gaussian filter of 3 mm. The 4 patients with GvHD were brought to the brainPET/MRI imaging facility 2:10h-2:28h after tracer injection. A 9 min brainPET-acquisition with simultaneous MRI of the lower extremities was accomplished. MRI examination included T1-weighted (pre and post gadolinium) and T2-weighted sequences. Attenuation correction was calculated based on manual bone segmentation and thresholds for soft tissue, fat and air. Soleus muscle (m), crural fascia (f1) and posterior crural intermuscular septum fascia (f2) were surrounded with ROIs based on the pre-treatment T1-weighted images and coregistered using IRW (Siemens). Fascia-to-muscle ratios for PET (f/m), T1 contrast uptake (T1_post-contrast_f-pre-contrast_f/post-contrast_m-pre-contrast_m) and T2 (T2_f/m) were calculated. Both patients with adenocarcinoma show a lower ADC value compared with the carcinoid patient suggesting a higher cellularity. This is also reflected in FDG-PET with higher SUV values. Our initial results reveal that PET/MRI can provide complementary information for a profound tumor characterization and therapy monitoring. The high soft tissue contrast provided by MRI is valuable for the assessment of the fascial inflammation. While in the first patient FDG and contrast uptake as well as edema, represented by T2 signals, decreased with ongoing therapy, all parameters remained comparatively stable in the second patient. Contrary to expectations, an increase in FDG uptake of patient 3 and 4 was accompanied by an increase of the T2 signals, but a decrease in contrast uptake. These initial results suggest that PET/MRI provides complementary information of the complex disease mechanisms in fibrosing disorders.

Web [BibTex]

Sauter, A., Schmidt, H., Gueckel, B., Brendle, C., Bezrukov, I., Mantlik, F., Kolb, A., Mueller, M., Reimold, M., Federmann, B., Hetzel, J., Claussen, C., Pfannenberg, C., Horger, M., Pichler, B., Schwenzer, N. Multi-parametric Tumor Characterization and Therapy Monitoring using Simultaneous PET/MRI: initial results for Lung Cancer and GvHD (T110), 2011 World Molecular Imaging Congress (WMIC), September 2011 (talk)

Web [BibTex]

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Statistical Image Analysis and Percolation Theory

Langovoy, M., Habeck, M., Schölkopf, B.

2011 Joint Statistical Meetings (JSM), August 2011 (talk)

Abstract
We develop a novel method for detection of signals and reconstruction of images in the presence of random noise. The method uses results from percolation theory. We specifically address the problem of detection of multiple objects of unknown shapes in the case of nonparametric noise. The noise density is unknown and can be heavy-tailed. The objects of interest have unknown varying intensities. No boundary shape constraints are imposed on the objects, only a set of weak bulk conditions is required. We view the object detection problem as hypothesis testing for discrete statistical inverse problems. We present an algorithm that allows to detect greyscale objects of various shapes in noisy images. We prove results on consistency and algorithmic complexity of our procedures. Applications to cryo-electron microscopy are presented.

Web [BibTex]

Langovoy, M., Habeck, M., Schölkopf, B. Statistical Image Analysis and Percolation Theory 2011 Joint Statistical Meetings (JSM), August 2011 (talk)

Web [BibTex]

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JMLR Workshop and Conference Proceedings Volume 19: COLT 2011

Kakade, S., von Luxburg, U.

pages: 834, MIT Press, Cambridge, MA, USA, 24th Annual Conference on Learning Theory , June 2011 (proceedings)

Web [BibTex]

Kakade, S., von Luxburg, U. JMLR Workshop and Conference Proceedings Volume 19: COLT 2011 pages: 834, MIT Press, Cambridge, MA, USA, 24th Annual Conference on Learning Theory , June 2011 (proceedings)

Web [BibTex]

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PAC-Bayesian Analysis of Martingales and Multiarmed Bandits

Seldin, Y., Laviolette, F., Shawe-Taylor, J., Peters, J., Auer, P.

Max Planck Institute for Biological Cybernetics, Tübingen, Germany, May 2011 (techreport)

Abstract
We present two alternative ways to apply PAC-Bayesian analysis to sequences of dependent random variables. The first is based on a new lemma that enables to bound expectations of convex functions of certain dependent random variables by expectations of the same functions of independent Bernoulli random variables. This lemma provides an alternative tool to Hoeffding-Azuma inequality to bound concentration of martingale values. Our second approach is based on integration of Hoeffding-Azuma inequality with PAC-Bayesian analysis. We also introduce a way to apply PAC-Bayesian analysis in situation of limited feedback. We combine the new tools to derive PAC-Bayesian generalization and regret bounds for the multiarmed bandit problem. Although our regret bound is not yet as tight as state-of-the-art regret bounds based on other well-established techniques, our results significantly expand the range of potential applications of PAC-Bayesian analysis and introduce a new analysis tool to reinforcement learning and many other fields, where martingales and limited feedback are encountered.

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Seldin, Y., Laviolette, F., Shawe-Taylor, J., Peters, J., Auer, P. PAC-Bayesian Analysis of Martingales and Multiarmed Bandits Max Planck Institute for Biological Cybernetics, Tübingen, Germany, May 2011 (techreport)

PDF Web [BibTex]

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Non-stationary Correction of Optical Aberrations

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

(1), Max Planck Institute for Intelligent Systems, Tübingen, Germany, May 2011 (techreport)

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

PDF [BibTex]

Schuler, C., Hirsch, M., Harmeling, S., Schölkopf, B. Non-stationary Correction of Optical Aberrations (1), Max Planck Institute for Intelligent Systems, Tübingen, Germany, May 2011 (techreport)

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Cooperative Cuts

Jegelka, S.

COSA Workshop: Combinatorial Optimization, Statistics, and Applications, March 2011 (talk)

Abstract
Combinatorial problems with submodular cost functions have recently drawn interest. In a standard combinatorial problem, the sum-of-weights cost is replaced by a submodular set function. The result is a powerful model that is though very hard. In this talk, I will introduce cooperative cuts, minimum cuts with submodular edge weights. I will outline methods to approximately solve this problem, and show an application in computer vision. If time permits, the talk will also sketch regret-minimizing online algorithms for submodular-cost combinatorial problems. This is joint work with Jeff Bilmes (University of Washington).

Web [BibTex]

Jegelka, S. Cooperative Cuts COSA Workshop: Combinatorial Optimization, Statistics, and Applications, March 2011 (talk)

Web [BibTex]

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Multiple Kernel Learning: A Unifying Probabilistic Viewpoint

Nickisch, H., Seeger, M.

Max Planck Institute for Biological Cybernetics, March 2011 (techreport)

Abstract
We present a probabilistic viewpoint to multiple kernel learning unifying well-known regularised risk approaches and recent advances in approximate Bayesian inference relaxations. The framework proposes a general objective function suitable for regression, robust regression and classification that is lower bound of the marginal likelihood and contains many regularised risk approaches as special cases. Furthermore, we derive an efficient and provably convergent optimisation algorithm.

Web [BibTex]

Nickisch, H., Seeger, M. Multiple Kernel Learning: A Unifying Probabilistic Viewpoint Max Planck Institute for Biological Cybernetics, March 2011 (techreport)

Web [BibTex]

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Multiple testing, uncertainty and realistic pictures

Langovoy, M., Wittich, O.

(2011-004), EURANDOM, Technische Universiteit Eindhoven, January 2011 (techreport)

Abstract
We study statistical detection of grayscale objects in noisy images. The object of interest is of unknown shape and has an unknown intensity, that can be varying over the object and can be negative. No boundary shape constraints are imposed on the object, only a weak bulk condition for the object's interior is required. We propose an algorithm that can be used to detect grayscale objects of unknown shapes in the presence of nonparametric noise of unknown level. Our algorithm is based on a nonparametric multiple testing procedure. We establish the limit of applicability of our method via an explicit, closed-form, non-asymptotic and nonparametric consistency bound. This bound is valid for a wide class of nonparametric noise distributions. We achieve this by proving an uncertainty principle for percolation on nite lattices.

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Langovoy, M., Wittich, O. Multiple testing, uncertainty and realistic pictures (2011-004), EURANDOM, Technische Universiteit Eindhoven, January 2011 (techreport)

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Nonconvex proximal splitting: batch and incremental algorithms

Sra, S.

(2), Max Planck Institute for Intelligent Systems, Tübingen, Germany, 2011 (techreport)

Abstract
Within the unmanageably large class of nonconvex optimization, we consider the rich subclass of nonsmooth problems having composite objectives (this includes the extensively studied convex, composite objective problems as a special case). For this subclass, we introduce a powerful, new framework that permits asymptotically non-vanishing perturbations. In particular, we develop perturbation-based batch and incremental (online like) nonconvex proximal splitting algorithms. To our knowledge, this is the rst time that such perturbation-based nonconvex splitting algorithms are being proposed and analyzed. While the main contribution of the paper is the theoretical framework, we complement our results by presenting some empirical results on matrix factorization.

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Sra, S. Nonconvex proximal splitting: batch and incremental algorithms (2), Max Planck Institute for Intelligent Systems, Tübingen, Germany, 2011 (techreport)

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2005

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Spectral clustering and transductive inference for graph data

Zhou, D.

NIPS Workshop on Kernel Methods and Structured Domains, December 2005 (talk)

PDF Web [BibTex]

2005

Zhou, D. Spectral clustering and transductive inference for graph data NIPS Workshop on Kernel Methods and Structured Domains, December 2005 (talk)

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Some thoughts about Gaussian Processes

Chapelle, O.

NIPS Workshop on Open Problems in Gaussian Processes for Machine Learning, December 2005 (talk)

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Chapelle, O. Some thoughts about Gaussian Processes NIPS Workshop on Open Problems in Gaussian Processes for Machine Learning, December 2005 (talk)

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Popper, Falsification and the VC-dimension

Corfield, D., Schölkopf, B., Vapnik, V.

(145), Max Planck Institute for Biological Cybernetics, November 2005 (techreport)

PDF [BibTex]

Corfield, D., Schölkopf, B., Vapnik, V. Popper, Falsification and the VC-dimension (145), Max Planck Institute for Biological Cybernetics, November 2005 (techreport)

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A Combinatorial View of Graph Laplacians

Huang, J.

(144), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, August 2005 (techreport)

Abstract
Discussions about different graph Laplacian, mainly normalized and unnormalized versions of graph Laplacian, have been ardent with respect to various methods in clustering and graph based semi-supervised learning. Previous research on graph Laplacians investigated their convergence properties to Laplacian operators on continuous manifolds. There is still no strong proof on convergence for the normalized Laplacian. In this paper, we analyze different variants of graph Laplacians directly from the ways solving the original graph partitioning problem. The graph partitioning problem is a well-known combinatorial NP hard optimization problem. The spectral solutions provide evidence that normalized Laplacian encodes more reasonable considerations for graph partitioning. We also provide some examples to show their differences.

[BibTex]

Huang, J. A Combinatorial View of Graph Laplacians (144), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, August 2005 (techreport)

[BibTex]

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Beyond Pairwise Classification and Clustering Using Hypergraphs

Zhou, D., Huang, J., Schölkopf, B.

(143), Max Planck Institute for Biological Cybernetics, August 2005 (techreport)

Abstract
In many applications, relationships among objects of interest are more complex than pairwise. Simply approximating complex relationships as pairwise ones can lead to loss of information. An alternative for these applications is to analyze complex relationships among data directly, without the need to first represent the complex relationships into pairwise ones. A natural way to describe complex relationships is to use hypergraphs. A hypergraph is a graph in which edges can connect more than two vertices. Thus we consider learning from a hypergraph, and develop a general framework which is applicable to classification and clustering for complex relational data. We have applied our framework to real-world web classification problems and obtained encouraging results.

PDF [BibTex]

Zhou, D., Huang, J., Schölkopf, B. Beyond Pairwise Classification and Clustering Using Hypergraphs (143), Max Planck Institute for Biological Cybernetics, August 2005 (techreport)

PDF [BibTex]

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Building Sparse Large Margin Classifiers

Wu, M., Schölkopf, B., BakIr, G.

The 22nd International Conference on Machine Learning (ICML), August 2005 (talk)

PDF [BibTex]

Wu, M., Schölkopf, B., BakIr, G. Building Sparse Large Margin Classifiers The 22nd International Conference on Machine Learning (ICML), August 2005 (talk)

PDF [BibTex]

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Learning from Labeled and Unlabeled Data on a Directed Graph

Zhou, D.

The 22nd International Conference on Machine Learning, August 2005 (talk)

Abstract
We propose a general framework for learning from labeled and unlabeled data on a directed graph in which the structure of the graph including the directionality of the edges is considered. The time complexity of the algorithm derived from this framework is nearly linear due to recently developed numerical techniques. In the absence of labeled instances, this framework can be utilized as a spectral clustering method for directed graphs, which generalizes the spectral clustering approach for undirected graphs. We have applied our framework to real-world web classification problems and obtained encouraging results.

PDF [BibTex]

Zhou, D. Learning from Labeled and Unlabeled Data on a Directed Graph The 22nd International Conference on Machine Learning, August 2005 (talk)

PDF [BibTex]

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Machine-Learning Approaches to BCI in Tübingen

Bensch, M., Bogdan, M., Hill, N., Lal, T., Rosenstiel, W., Schölkopf, B., Schröder, M.

Brain-Computer Interface Technology, June 2005, Talk given by NJH. (talk)

[BibTex]

Bensch, M., Bogdan, M., Hill, N., Lal, T., Rosenstiel, W., Schölkopf, B., Schröder, M. Machine-Learning Approaches to BCI in Tübingen Brain-Computer Interface Technology, June 2005, Talk given by NJH. (talk)

[BibTex]

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Generalized Nonnegative Matrix Approximations using Bregman Divergences

Sra, S., Dhillon, I.

Univ. of Texas at Austin, June 2005 (techreport)

[BibTex]

Sra, S., Dhillon, I. Generalized Nonnegative Matrix Approximations using Bregman Divergences Univ. of Texas at Austin, June 2005 (techreport)

[BibTex]

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Learning Motor Primitives with Reinforcement Learning

Peters, J., Schaal, S.

ROBOTICS Workshop on Modular Foundations for Control and Perception, June 2005 (talk)

Web [BibTex]

Peters, J., Schaal, S. Learning Motor Primitives with Reinforcement Learning ROBOTICS Workshop on Modular Foundations for Control and Perception, June 2005 (talk)

Web [BibTex]

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Measuring Statistical Dependence with Hilbert-Schmidt Norms

Gretton, A., Bousquet, O., Smola, A., Schölkopf, B.

(140), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, June 2005 (techreport)

Abstract
We propose an independence criterion based on the eigenspectrum of covariance operators in reproducing kernel Hilbert spaces (RKHSs), consisting of an empirical estimate of the Hilbert-Schmidt norm of the cross-covariance operator (we term this a Hilbert-Schmidt Independence Criterion, or HSIC). This approach has several advantages, compared with previous kernel-based independence criteria. First, the empirical estimate is simpler than any other kernel dependence test, and requires no user-defined regularisation. Second, there is a clearly defined population quantity which the empirical estimate approaches in the large sample limit, with exponential convergence guaranteed between the two: this ensures that independence tests based on HSIC do not suffer from slow learning rates. Finally, we show in the context of independent component analysis (ICA) that the performance of HSIC is competitive with that of previously published kernel-based criteria, and of other recently published ICA methods.

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Gretton, A., Bousquet, O., Smola, A., Schölkopf, B. Measuring Statistical Dependence with Hilbert-Schmidt Norms (140), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, June 2005 (techreport)

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Consistency of Kernel Canonical Correlation Analysis

Fukumizu, K., Bach, F., Gretton, A.

(942), Institute of Statistical Mathematics, 4-6-7 Minami-azabu, Minato-ku, Tokyo 106-8569 Japan, June 2005 (techreport)

PDF [BibTex]

Fukumizu, K., Bach, F., Gretton, A. Consistency of Kernel Canonical Correlation Analysis (942), Institute of Statistical Mathematics, 4-6-7 Minami-azabu, Minato-ku, Tokyo 106-8569 Japan, June 2005 (techreport)

PDF [BibTex]

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Motor Skill Learning for Humanoid Robots

Peters, J.

First Conference Undergraduate Computer Sciences and Informations Sciences (CS/IS), May 2005 (talk)

[BibTex]

Peters, J. Motor Skill Learning for Humanoid Robots First Conference Undergraduate Computer Sciences and Informations Sciences (CS/IS), May 2005 (talk)

[BibTex]

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Kernel Constrained Covariance for Dependence Measurement

Gretton, A., Smola, A., Bousquet, O., Herbrich, R., Belitski, A., Augath, M., Murayama, Y., Schölkopf, B., Logothetis, N.

AISTATS, January 2005 (talk)

Abstract
We discuss reproducing kernel Hilbert space (RKHS)-based measures of statistical dependence, with emphasis on constrained covariance (COCO), a novel criterion to test dependence of random variables. We show that COCO is a test for independence if and only if the associated RKHSs are universal. That said, no independence test exists that can distinguish dependent and independent random variables in all circumstances. Dependent random variables can result in a COCO which is arbitrarily close to zero when the source densities are highly non-smooth. All current kernel-based independence tests share this behaviour. We demonstrate exponential convergence between the population and empirical COCO. Finally, we use COCO as a measure of joint neural activity between voxels in MRI recordings of the macaque monkey, and compare the results to the mutual information and the correlation. We also show the effect of removing breathing artefacts from the MRI recording.

PostScript [BibTex]

Gretton, A., Smola, A., Bousquet, O., Herbrich, R., Belitski, A., Augath, M., Murayama, Y., Schölkopf, B., Logothetis, N. Kernel Constrained Covariance for Dependence Measurement AISTATS, January 2005 (talk)

PostScript [BibTex]

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Approximate Inference for Robust Gaussian Process Regression

Kuss, M., Pfingsten, T., Csato, L., Rasmussen, C.

(136), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 2005 (techreport)

Abstract
Gaussian process (GP) priors have been successfully used in non-parametric Bayesian regression and classification models. Inference can be performed analytically only for the regression model with Gaussian noise. For all other likelihood models inference is intractable and various approximation techniques have been proposed. In recent years expectation-propagation (EP) has been developed as a general method for approximate inference. This article provides a general summary of how expectation-propagation can be used for approximate inference in Gaussian process models. Furthermore we present a case study describing its implementation for a new robust variant of Gaussian process regression. To gain further insights into the quality of the EP approximation we present experiments in which we compare to results obtained by Markov chain Monte Carlo (MCMC) sampling.

PDF [BibTex]

Kuss, M., Pfingsten, T., Csato, L., Rasmussen, C. Approximate Inference for Robust Gaussian Process Regression (136), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 2005 (techreport)

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Maximum-Margin Feature Combination for Detection and Categorization

BakIr, G., Wu, M., Eichhorn, J.

Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 2005 (techreport)

Abstract
In this paper we are concerned with the optimal combination of features of possibly different types for detection and estimation tasks in machine vision. We propose to combine features such that the resulting classifier maximizes the margin between classes. In contrast to existing approaches which are non-convex and/or generative we propose to use a discriminative model leading to convex problem formulation and complexity control. Furthermore we assert that decision functions should not compare apples and oranges by comparing features of different types directly. Instead we propose to combine different similarity measures for each different feature type. Furthermore we argue that the question: ”Which feature type is more discriminative for task X?” is ill-posed and show empirically that the answer to this question might depend on the complexity of the decision function.

PDF [BibTex]

BakIr, G., Wu, M., Eichhorn, J. Maximum-Margin Feature Combination for Detection and Categorization Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 2005 (techreport)

PDF [BibTex]

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Towards a Statistical Theory of Clustering. Presented at the PASCAL workshop on clustering, London

von Luxburg, U., Ben-David, S.

Presented at the PASCAL workshop on clustering, London, 2005 (techreport)

Abstract
The goal of this paper is to discuss statistical aspects of clustering in a framework where the data to be clustered has been sampled from some unknown probability distribution. Firstly, the clustering of the data set should reveal some structure of the underlying data rather than model artifacts due to the random sampling process. Secondly, the more sample points we have, the more reliable the clustering should be. We discuss which methods can and cannot be used to tackle those problems. In particular we argue that generalization bounds as they are used in statistical learning theory of classification are unsuitable in a general clustering framework. We suggest that the main replacements of generalization bounds should be convergence proofs and stability considerations. This paper should be considered as a road map paper which identifies important questions and potentially fruitful directions for future research about statistical clustering. We do not attempt to present a complete statistical theory of clustering.

PDF [BibTex]

von Luxburg, U., Ben-David, S. Towards a Statistical Theory of Clustering. Presented at the PASCAL workshop on clustering, London Presented at the PASCAL workshop on clustering, London, 2005 (techreport)

PDF [BibTex]

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Approximate Bayesian Inference for Psychometric Functions using MCMC Sampling

Kuss, M., Jäkel, F., Wichmann, F.

(135), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 2005 (techreport)

Abstract
In psychophysical studies the psychometric function is used to model the relation between the physical stimulus intensity and the observer's ability to detect or discriminate between stimuli of different intensities. In this report we propose the use of Bayesian inference to extract the information contained in experimental data estimate the parameters of psychometric functions. Since Bayesian inference cannot be performed analytically we describe how a Markov chain Monte Carlo method can be used to generate samples from the posterior distribution over parameters. These samples are used to estimate Bayesian confidence intervals and other characteristics of the posterior distribution. In addition we discuss the parameterisation of psychometric functions and the role of prior distributions in the analysis. The proposed approach is exemplified using artificially generate d data and in a case study for real experimental data. Furthermore, we compare our approach with traditional methods based on maximum-likelihood parameter estimation combined with bootstrap techniques for confidence interval estimation. The appendix provides a description of an implementation for the R environment for statistical computing and provides the code for reproducing the results discussed in the experiment section.

PDF [BibTex]

Kuss, M., Jäkel, F., Wichmann, F. Approximate Bayesian Inference for Psychometric Functions using MCMC Sampling (135), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 2005 (techreport)

PDF [BibTex]

2002

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Kernel Dependency Estimation

Weston, J., Chapelle, O., Elisseeff, A., Schölkopf, B., Vapnik, V.

(98), Max Planck Institute for Biological Cybernetics, August 2002 (techreport)

Abstract
We consider the learning problem of finding a dependency between a general class of objects and another, possibly different, general class of objects. The objects can be for example: vectors, images, strings, trees or graphs. Such a task is made possible by employing similarity measures in both input and output spaces using kernel functions, thus embedding the objects into vector spaces. Output kernels also make it possible to encode prior information and/or invariances in the loss function in an elegant way. We experimentally validate our approach on several tasks: mapping strings to strings, pattern recognition, and reconstruction from partial images.

PDF [BibTex]

2002

Weston, J., Chapelle, O., Elisseeff, A., Schölkopf, B., Vapnik, V. Kernel Dependency Estimation (98), Max Planck Institute for Biological Cybernetics, August 2002 (techreport)

PDF [BibTex]

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Global Geometry of SVM Classifiers

Zhou, D., Xiao, B., Zhou, H., Dai, R.

Max Planck Institute for Biological Cybernetics, Tübingen, Germany, June 2002 (techreport)

Abstract
We construct an geometry framework for any norm Support Vector Machine (SVM) classifiers. Within this framework, separating hyperplanes, dual descriptions and solutions of SVM classifiers are constructed by a purely geometric fashion. In contrast with the optimization theory used in SVM classifiers, we have no complicated computations any more. Each step in our theory is guided by elegant geometric intuitions.

PDF PostScript [BibTex]

Zhou, D., Xiao, B., Zhou, H., Dai, R. Global Geometry of SVM Classifiers Max Planck Institute for Biological Cybernetics, Tübingen, Germany, June 2002 (techreport)

PDF PostScript [BibTex]

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Computationally Efficient Face Detection

Romdhani, S., Torr, P., Schölkopf, B., Blake, A.

(MSR-TR-2002-69), Microsoft Research, June 2002 (techreport)

Web [BibTex]

Romdhani, S., Torr, P., Schölkopf, B., Blake, A. Computationally Efficient Face Detection (MSR-TR-2002-69), Microsoft Research, June 2002 (techreport)

Web [BibTex]

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Kernel-based nonlinear blind source separation

Harmeling, S., Ziehe, A., Kawanabe, M., Müller, K.

EU-Project BLISS, January 2002 (techreport)

GZIP [BibTex]

Harmeling, S., Ziehe, A., Kawanabe, M., Müller, K. Kernel-based nonlinear blind source separation EU-Project BLISS, January 2002 (techreport)

GZIP [BibTex]