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2017


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Learning Blind Motion Deblurring

Wieschollek, P., Hirsch, M., Schölkopf, B., Lensch, H.

Proceedings IEEE International Conference on Computer Vision (ICCV), pages: 231-240, IEEE, Piscataway, NJ, USA, IEEE International Conference on Computer Vision (ICCV), October 2017 (conference)

link (url) [BibTex]

2017

link (url) [BibTex]


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Personalized Brain-Computer Interface Models for Motor Rehabilitation

Mastakouri, A., Weichwald, S., Ozdenizci, O., Meyer, T., Schölkopf, B., Grosse-Wentrup, M.

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages: 3024-3029, October 2017 (conference)

ArXiv PDF DOI Project Page [BibTex]

ArXiv PDF DOI Project Page [BibTex]


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Multi-frame blind image deconvolution through split frequency - phase recovery

Gauci, A., Abela, J., Cachia, E., Hirsch, M., ZarbAdami, K.

Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), pages: 1022511, (Editors: Yulin Wang, Tuan D. Pham, Vit Vozenilek, David Zhang, Yi Xie), October 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Closing One’s Eyes Affects Amplitude Modulation but Not Frequency Modulation in a Cognitive BCI

Görner, M., Schölkopf, B., Grosse-Wentrup, M.

Proceedings of the 7th Graz Brain-Computer Interface Conference 2017 - From Vision to Reality, pages: 165-170, (Editors: Müller-Putz G.R., Steyrl D., Wriessnegger S. C., Scherer R.), Graz University of Technology, Austria, Graz Brain-Computer Interface Conference, September 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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A Guided Task for Cognitive Brain-Computer Interfaces

Moser, J., Hohmann, M. R., Schölkopf, B., Grosse-Wentrup, M.

Proceedings of the 7th Graz Brain-Computer Interface Conference 2017 - From Vision to Reality, pages: 326-331, (Editors: Müller-Putz G.R., Steyrl D., Wriessnegger S. C., Scherer R.), Graz University of Technology, Austria, Graz Brain-Computer Interface Conference, September 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Bayesian Regression for Artifact Correction in Electroencephalography

Fiebig, K., Jayaram, V., Hesse, T., Blank, A., Peters, J., Grosse-Wentrup, M.

Proceedings of the 7th Graz Brain-Computer Interface Conference 2017 - From Vision to Reality, pages: 131-136, (Editors: Müller-Putz G.R., Steyrl D., Wriessnegger S. C., Scherer R.), Graz University of Technology, Austria, Graz Brain-Computer Interface Conference, September 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Investigating Music Imagery as a Cognitive Paradigm for Low-Cost Brain-Computer Interfaces

Grossberger, L., Hohmann, M. R., Peters, J., Grosse-Wentrup, M.

Proceedings of the 7th Graz Brain-Computer Interface Conference 2017 - From Vision to Reality, pages: 160-164, (Editors: Müller-Putz G.R., Steyrl D., Wriessnegger S. C., Scherer R.), Graz University of Technology, Austria, Graz Brain-Computer Interface Conference, September 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Correlations of Motor Adaptation Learning and Modulation of Resting-State Sensorimotor EEG Activity

Ozdenizci, O., Yalcin, M., Erdogan, A., Patoglu, V., Grosse-Wentrup, M., Cetin, M.

Proceedings of the 7th Graz Brain-Computer Interface Conference 2017 - From Vision to Reality, pages: 384-388, (Editors: Müller-Putz G.R., Steyrl D., Wriessnegger S. C., Scherer R.), Graz University of Technology, Austria, Graz Brain-Computer Interface Conference, September 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Assisting the practice of motor skills by humans with a probability distribution over trajectories

Ewerton, M., Maeda, G., Rother, D., Weimar, J., Lotter, L., Kollegger, G., Wiemeyer, J., Peters, J.

In Workshop Human-in-the-loop robotic manipulation: on the influence of the human role at IROS, September 2017 (inproceedings)

link (url) [BibTex]

link (url) [BibTex]


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BIMROB – Bidirectional Interaction Between Human and Robot for the Learning of Movements

Kollegger, G., Ewerton, M., Wiemeyer, J., Peters, J.

Proceedings of the 11th International Symposium on Computer Science in Sport (IACSS), (663):151-163, Advances in Intelligent Systems and Computing, (Editors: Lames M., Saupe D. and Wiemeyer J.), Springer International Publishing, September 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Goal-driven dimensionality reduction for reinforcement learning

Parisi, S., Ramstedt, S., Peters, J.

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 4634-4639, IEEE, September 2017 (conference)

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Weakly-Supervised Localization of Diabetic Retinopathy Lesions in Retinal Fundus Images

Gondal, M. W., Köhler, J. M., Grzeszick, R., Fink, G., Hirsch, M.

IEEE International Conference on Image Processing (ICIP), pages: 2069-2073, September 2017 (conference)

arXiv DOI [BibTex]

arXiv DOI [BibTex]


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Hybrid control trajectory optimization under uncertainty

Pajarinen, J., Kyrki, V., Koval, M., Srinivasa, S., Peters, J., Neumann, G.

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 5694-5701, September 2017 (conference)

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Local Bayesian Optimization of Motor Skills

Akrour, R., Sorokin, D., Peters, J., Neumann, G.

Proceedings of the 34th International Conference on Machine Learning, 70, pages: 41-50, Proceedings of Machine Learning Research, (Editors: Doina Precup, Yee Whye Teh), PMLR, International Conference on Machine Learning (ICML), August 2017 (conference)

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Sequence Tutor: Conservative fine-tuning of sequence generation models with KL-control

Jaques, N., Gu, S., Bahdanau, D., Hernández-Lobato, J. M., Turner, R. E., Eck, D.

Proceedings of the 34th International Conference on Machine Learning, 70, pages: 1645-1654, Proceedings of Machine Learning Research, (Editors: Doina Precup, Yee Whye Teh), PMLR, International Conference on Machine Learning (ICML), August 2017 (conference)

Arxiv link (url) Project Page [BibTex]

Arxiv link (url) Project Page [BibTex]


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Lost Relatives of the Gumbel Trick

Balog, M., Tripuraneni, N., Ghahramani, Z., Weller, A.

Proceedings of the 34th International Conference on Machine Learning, 70, pages: 371-379, Proceedings of Machine Learning Research, (Editors: Doina Precup, Yee Whye Teh), PMLR, International Conference on Machine Learning (ICML), August 2017 (conference)

Code link (url) Project Page [BibTex]

Code link (url) Project Page [BibTex]


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Approximate Steepest Coordinate Descent

Stich, S., Raj, A., Jaggi, M.

Proceedings of the 34th International Conference on Machine Learning, 70, pages: 3251-3259, Proceedings of Machine Learning Research, (Editors: Doina Precup, Yee Whye Teh), PMLR, International Conference on Machine Learning (ICML), August 2017 (conference)

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Causal Consistency of Structural Equation Models

Rubenstein*, P. K., Weichwald*, S., Bongers, S., Mooij, J. M., Janzing, D., Grosse-Wentrup, M., Schölkopf, B.

Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence (UAI), (Editors: Gal Elidan, Kristian Kersting, and Alexander T. Ihler), Association for Uncertainty in Artificial Intelligence (AUAI), Conference on Uncertainty in Artificial Intelligence (UAI), August 2017, *equal contribution (conference)

Arxiv PDF link (url) [BibTex]

Arxiv PDF link (url) [BibTex]


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Causal Discovery from Temporally Aggregated Time Series

Gong, M., Zhang, K., Schölkopf, B., Glymour, C., Tao, D.

Proceedings Conference on Uncertainty in Artificial Intelligence (UAI) 2017, pages: ID 269, (Editors: Gal Elidan, Kristian Kersting, and Alexander T. Ihler), Association for Uncertainty in Artificial Intelligence (AUAI), Conference on Uncertainty in Artificial Intelligence (UAI), August 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination

Zhang, K., Huang, B., Zhang, J., Glymour, C., Schölkopf, B.

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI), pages: 1347-1353, (Editors: Carles Sierra), August 2017 (conference)

PDF DOI [BibTex]

PDF DOI [BibTex]


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Flexible Spatio-Temporal Networks for Video Prediction

Lu, C., Hirsch, M., Schölkopf, B.

Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, pages: 2137-2145, IEEE, Piscataway, NJ, USA, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017 (conference)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Discovering Causal Signals in Images

Lopez-Paz, D., Nishihara, R., Chintala, S., Schölkopf, B., Bottou, L.

Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, pages: 58-66, IEEE, Piscataway, NJ, USA, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017 (conference)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Dynamic Time-of-Flight

Schober, M., Adam, A., Yair, O., Mazor, S., Nowozin, S.

Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, pages: 170-179, IEEE, Piscataway, NJ, USA, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Strategic exploration in human adaptive control

Schulz, E., Klenske, E., Bramley, N., Speekenbrink, M.

Proceedings of the 39th Annual Conference of the Cognitive Science Society (CogSci), (Editors: Glenn Gunzelmann, Andrew Howes, Thora Tenbrink and Eddy J. Davelaar), cognitivesciencesociety.org, July 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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State-Regularized Policy Search for Linearized Dynamical Systems

Abdulsamad, H., Arenz, O., Peters, J., Neumann, G.

Proceedings of the Twenty-Seventh International Conference on Automated Planning and Scheduling, (ICAPS), pages: 419-424, (Editors: Laura Barbulescu, Jeremy Frank, Mausam and Stephen F. Smith), AAAI Press, June 2017 (conference)

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Deep Reinforcement Learning for Robotic Manipulation with Asynchronous Off-Policy Updates

Gu*, S., Holly*, E., Lillicrap, T., Levine, S.

Proceedings 2017 IEEE International Conference on Robotics and Automation (ICRA), IEEE, Piscataway, NJ, USA, IEEE International Conference on Robotics and Automation (ICRA), May 2017, *equal contribution (conference)

Arxiv Project Page [BibTex]

Arxiv Project Page [BibTex]


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Context-Driven Movement Primitive Adaptation

Wilbers, D., Lioutikov, R., Peters, J.

IEEE International Conference on Robotics and Automation (ICRA), pages: 3469-3475, IEEE, May 2017 (conference)

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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A Learning-based Shared Control Architecture for Interactive Task Execution

Farraj, F. B., Osa, T., Pedemonte, N., Peters, J., Neumann, G., Giordano, P.

IEEE International Conference on Robotics and Automation (ICRA), pages: 329-335, IEEE, May 2017 (conference)

DOI Project Page Project Page [BibTex]

DOI Project Page Project Page [BibTex]


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Frequency Peak Features for Low-Channel Classification in Motor Imagery Paradigms

Jayaram, V., Schölkopf, B., Grosse-Wentrup, M.

Proceedings of the 8th International IEEE/EMBS Conference on Neural Engineering (NER), pages: 321-324, May 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Empowered skills

Gabriel, A., Akrour, R., Peters, J., Neumann, G.

IEEE International Conference on Robotics and Automation (ICRA), pages: 6435-6441, IEEE, May 2017 (conference)

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Layered direct policy search for learning hierarchical skills

End, F., Akrour, R., Peters, J., Neumann, G.

IEEE International Conference on Robotics and Automation (ICRA), pages: 6442-6448, IEEE, May 2017 (conference)

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic

Gu, S., Lillicrap, T., Ghahramani, Z., Turner, R. E., Levine, S.

Proceedings International Conference on Learning Representations (ICLR), OpenReviews.net, International Conference on Learning Representations, April 2017 (conference)

PDF link (url) Project Page [BibTex]

PDF link (url) Project Page [BibTex]


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Categorical Reparametrization with Gumbel-Softmax

Jang, E., Gu, S., Poole, B.

Proceedings International Conference on Learning Representations 2017, OpenReviews.net, International Conference on Learning Representations, April 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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DeepCoder: Learning to Write Programs

Balog, M., Gaunt, A. L., Brockschmidt, M., Nowozin, S., Tarlow, D.

Proceedings International Conference on Learning Representations 2017, OpenReviews.net, International Conference on Learning Representations, April 2017 (conference)

Arxiv link (url) Project Page [BibTex]

Arxiv link (url) Project Page [BibTex]


Distilling Information Reliability and Source Trustworthiness from Digital Traces
Distilling Information Reliability and Source Trustworthiness from Digital Traces

Tabibian, B., Valera, I., Farajtabar, M., Song, L., Schölkopf, B., Gomez Rodriguez, M.

Proceedings of the 26th International Conference on World Wide Web (WWW), pages: 847-855, (Editors: Barrett, R., Cummings, R., Agichtein, E. and Gabrilovich, E. ), ACM, April 2017 (conference)

Project DOI Project Page Project Page [BibTex]

Project DOI Project Page Project Page [BibTex]


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Local Group Invariant Representations via Orbit Embeddings

Raj, A., Kumar, A., Mroueh, Y., Fletcher, T., Schölkopf, B.

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS), 54, pages: 1225-1235, Proceedings of Machine Learning Research, (Editors: Aarti Singh and Jerry Zhu), April 2017 (conference)

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Pre-Movement Contralateral EEG Low Beta Power Is Modulated with Motor Adaptation Learning

Ozdenizci, O., Yalcin, M., Erdogan, A., Patoglu, V., Grosse-Wentrup, M., Cetin, M.

International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages: 934-938, March 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Automatic detection of motion artifacts in MR images using CNNs

Meding, K., Loktyushin, A., Hirsch, M.

42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages: 811-815, March 2017 (conference)

DOI [BibTex]

DOI [BibTex]


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Catching heuristics are optimal control policies

Belousov, B., Neumann, G., Rothkopf, C., Peters, J.

Proceedings of the Thirteenth Karniel Computational Motor Control Workshop, March 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]


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DiSMEC – Distributed Sparse Machines for Extreme Multi-label Classification

Babbar, R., Schölkopf, B.

Proceedings of the Tenth ACM International Conference on Web Search and Data Mining (WSDM), pages: 721-729, Febuary 2017 (conference)

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Policy Search with High-Dimensional Context Variables

Tangkaratt, V., van Hoof, H., Parisi, S., Neumann, G., Peters, J., Sugiyama, M.

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI), pages: 2632-2638, (Editors: Satinder P. Singh and Shaul Markovitch), AAAI Press, Febuary 2017 (conference)

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Iterative Feedback-basierte Korrekturstrategien beim Bewegungslernen von Mensch-Roboter-Dyaden

Ewerton, M., Kollegger, G., Maeda, G., Wiemeyer, J., Peters, J.

In DVS Sportmotorik 2017, 2017 (inproceedings)

link (url) [BibTex]

link (url) [BibTex]


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BIMROB - Bidirectional Interaction between human and robot for the learning of movements - Robot trains human - Human trains robot

Kollegger, G., Wiemeyer, J., Ewerton, M., Peters, J.

In Inovation & Technologie im Sport - 23. Sportwissenschaftlicher Hochschultag der deutschen Vereinigung für Sportwissenschaft, pages: 179, (Editors: A. Schwirtz, F. Mess, Y. Demetriou & V. Senner ), Czwalina-Feldhaus, 2017 (inproceedings)

[BibTex]

[BibTex]


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BIMROB – Bidirektionale Interaktion von Mensch und Roboter beim Bewegungslernen

Wiemeyer, J., Peters, J., Kollegger, G., Ewerton, M.

DVS Sportmotorik 2017, 2017 (conference)

link (url) [BibTex]

link (url) [BibTex]

2005


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Kernel ICA for Large Scale Problems

Jegelka, S., Gretton, A., Achlioptas, D.

In pages: -, NIPS Workshop on Large Scale Kernel Machines, December 2005 (inproceedings)

Web [BibTex]

2005

Web [BibTex]


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Infinite dimensional exponential families by reproducing kernel Hilbert spaces

Fukumizu, K.

In IGAIA 2005, pages: 324-333, 2nd International Symposium on Information Geometry and its Applications, December 2005 (inproceedings)

Abstract
The purpose of this paper is to propose a method of constructing exponential families of Hilbert manifold, on which estimation theory can be built. Although there have been works on infinite dimensional exponential families of Banach manifolds (Pistone and Sempi, 1995; Gibilisco and Pistone, 1998; Pistone and Rogantin, 1999), they are not appropriate to discuss statistical estimation with finite number of samples; the likelihood function with finite samples is not continuous on the manifold. In this paper we use a reproducing kernel Hilbert space as a functional space for constructing an exponential manifold. A reproducing kernel Hilbert space is dened as a Hilbert space of functions such that evaluation of a function at an arbitrary point is a continuous functional on the Hilbert space. Since we can discuss the value of a function with this space, it is very natural to use a manifold associated with a reproducing kernel Hilbert space as a basis of estimation theory. We focus on the maximum likelihood estimation (MLE) with the exponential manifold of a reproducing kernel Hilbert space. As in many non-parametric estimation methods, straightforward extension of MLE to an infinite dimensional exponential manifold suffers the problem of ill-posedness caused by the fact that the estimator should be chosen from the infinite dimensional space with only finite number of constraints given by the data. To solve this problem, a pseudo-maximum likelihood method is proposed by restricting the infinite dimensional manifold to a series of finite dimensional submanifolds, which enlarge as the number of samples increases. Some asymptotic results in the limit of infinite samples are shown, including the consistency of the pseudo-MLE.

PDF Web [BibTex]

PDF Web [BibTex]


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Shortest-path kernels on graphs

Borgwardt, KM., Kriegel, H-P.

In pages: 74-81, IEEE Computer Society, Los Alamitos, CA, USA, Fifth International Conference on Data Mining (ICDM), November 2005 (inproceedings)

Abstract
Data mining algorithms are facing the challenge to deal with an increasing number of complex objects. For graph data, a whole toolbox of data mining algorithms becomes available by defining a kernel function on instances of graphs. Graph kernels based on walks, subtrees and cycles in graphs have been proposed so far. As a general problem, these kernels are either computationally expensive or limited in their expressiveness. We try to overcome this problem by defining expressive graph kernels which are based on paths. As the computation of all paths and longest paths in a graph is NP-hard, we propose graph kernels based on shortest paths. These kernels are computable in polynomial time, retain expressivity and are still positive definite. In experiments on classification of graph models of proteins, our shortest-path kernels show significantly higher classification accuracy than walk-based kernels.

Web DOI [BibTex]

Web DOI [BibTex]


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Training Support Vector Machines with Multiple Equality Constraints

Kienzle, W., Schölkopf, B.

In Proceedings of the 16th European Conference on Machine Learning, Lecture Notes in Computer Science, Vol. 3720, pages: 182-193, (Editors: JG Carbonell and J Siekmann), Springer, Berlin, Germany, ECML, November 2005 (inproceedings)

Abstract
In this paper we present a primal-dual decomposition algorithm for support vector machine training. As with existing methods that use very small working sets (such as Sequential Minimal Optimization (SMO), Successive Over-Relaxation (SOR) or the Kernel Adatron (KA)), our method scales well, is straightforward to implement, and does not require an external QP solver. Unlike SMO, SOR and KA, the method is applicable to a large number of SVM formulations regardless of the number of equality constraints involved. The effectiveness of our algorithm is demonstrated on a more difficult SVM variant in this respect, namely semi-parametric support vector regression.

PDF DOI [BibTex]

PDF DOI [BibTex]