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2017


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Model-based Contextual Policy Search for Data-Efficient Generalization of Robot Skills

Kupcsik, A., Deisenroth, M., Peters, J., Ai Poh, L., Vadakkepat, V., Neumann, G.

Artificial Intelligence, 247, pages: 415-439, 2017, Special Issue on AI and Robotics (article)

link (url) DOI [BibTex]

2017

link (url) DOI [BibTex]


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Anticipatory Action Selection for Human-Robot Table Tennis

Wang, Z., Boularias, A., Mülling, K., Schölkopf, B., Peters, J.

Artificial Intelligence, 247, pages: 399-414, 2017, Special Issue on AI and Robotics (article)

Abstract
Abstract Anticipation can enhance the capability of a robot in its interaction with humans, where the robot predicts the humans' intention for selecting its own action. We present a novel framework of anticipatory action selection for human-robot interaction, which is capable to handle nonlinear and stochastic human behaviors such as table tennis strokes and allows the robot to choose the optimal action based on prediction of the human partner's intention with uncertainty. The presented framework is generic and can be used in many human-robot interaction scenarios, for example, in navigation and human-robot co-manipulation. In this article, we conduct a case study on human-robot table tennis. Due to the limited amount of time for executing hitting movements, a robot usually needs to initiate its hitting movement before the opponent hits the ball, which requires the robot to be anticipatory based on visual observation of the opponent's movement. Previous work on Intention-Driven Dynamics Models (IDDM) allowed the robot to predict the intended target of the opponent. In this article, we address the problem of action selection and optimal timing for initiating a chosen action by formulating the anticipatory action selection as a Partially Observable Markov Decision Process (POMDP), where the transition and observation are modeled by the \{IDDM\} framework. We present two approaches to anticipatory action selection based on the \{POMDP\} formulation, i.e., a model-free policy learning method based on Least-Squares Policy Iteration (LSPI) that employs the \{IDDM\} for belief updates, and a model-based Monte-Carlo Planning (MCP) method, which benefits from the transition and observation model by the IDDM. Experimental results using real data in a simulated environment show the importance of anticipatory action selection, and that \{POMDPs\} are suitable to formulate the anticipatory action selection problem by taking into account the uncertainties in prediction. We also show that existing algorithms for POMDPs, such as \{LSPI\} and MCP, can be applied to substantially improve the robot's performance in its interaction with humans.

DOI [BibTex]

DOI [BibTex]


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Kernel Mean Embedding of Distributions: A Review and Beyond

Muandet, K., Fukumizu, K., Sriperumbudur, B., Schölkopf, B.

Foundations and Trends in Machine Learning, 10(1-2):1-141, 2017 (article)

DOI [BibTex]

DOI [BibTex]


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Prediction of intention during interaction with iCub with Probabilistic Movement Primitives

Dermy, O., Paraschos, A., Ewerton, M., Charpillet, F., Peters, J., Ivaldi, S.

Frontiers in Robotics and AI, 4, pages: 45, 2017 (article)

DOI [BibTex]

DOI [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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Manifold-based multi-objective policy search with sample reuse

Parisi, S., Pirotta, M., Peters, J.

Neurocomputing, 263, pages: 3-14, (Editors: Madalina Drugan, Marco Wiering, Peter Vamplew, and Madhu Chetty), 2017, Special Issue on Multi-Objective Reinforcement Learning (article)

DOI [BibTex]

DOI [BibTex]


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Robot Learning

Peters, J., Lee, D., Kober, J., Nguyen-Tuong, D., Bagnell, J., Schaal, S.

In Springer Handbook of Robotics, pages: 357-394, 15, 2nd, (Editors: Siciliano, Bruno and Khatib, Oussama), Springer International Publishing, 2017 (inbook)

[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]


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easyGWAS: A Cloud-based Platform for Comparing the Results of Genome-wide Association Studies

Grimm, D., Roqueiro, D., Salome, P., Kleeberger, S., Greshake, B., Zhu, W., Liu, C., Lippert, C., Stegle, O., Schölkopf, B., Weigel, D., Borgwardt, K.

The Plant Cell, 29(1):5-19, 2017 (article)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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A Novel Unsupervised Segmentation Approach Quantifies Tumor Tissue Populations Using Multiparametric MRI: First Results with Histological Validation

Katiyar, P., Divine, M. R., Kohlhofer, U., Quintanilla-Martinez, L., Schölkopf, B., Pichler, B. J., Disselhorst, J. A.

Molecular Imaging and Biology, 19(3):391-397, 2017 (article)

DOI [BibTex]

DOI [BibTex]


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Elements of Causal Inference - Foundations and Learning Algorithms

Peters, J., Janzing, D., Schölkopf, B.

Adaptive Computation and Machine Learning Series, The MIT Press, Cambridge, MA, USA, 2017 (book)

PDF [BibTex]

PDF [BibTex]


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Minimax Estimation of Kernel Mean Embeddings

Tolstikhin, I., Sriperumbudur, B., Muandet, K.

Journal of Machine Learning Research, 18(86):1-47, 2017 (article)

link (url) [BibTex]

link (url) [BibTex]


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Policy Gradient Methods

Peters, J., Bagnell, J.

In Encyclopedia of Machine Learning and Data Mining, pages: 982-985, 2nd, (Editors: Sammut, Claude and Webb, Geoffrey I.), Springer US, 2017 (inbook)

link (url) [BibTex]

link (url) [BibTex]


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Temporal evolution of the central fixation bias in scene viewing

Rothkegel, L. O. M., Trukenbrod, H. A., Schütt, H. H., Wichmann, F. A., Engbert, R.

Journal of Vision, 17(13):3, 2017 (article)

DOI [BibTex]

DOI [BibTex]


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Spectral Clustering predicts tumor tissue heterogeneity using dynamic 18F-FDG PET: a complement to the standard compartmental modeling approach

Katiyar, P., Divine, M. R., Kohlhofer, U., Quintanilla-Martinez, L., Schölkopf, B., Pichler, B. J., Disselhorst, J. A.

Journal of Nuclear Medicine, 58(4):651-657, 2017 (article)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Electroencephalographic identifiers of motor adaptation learning

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

Journal of Neural Engineering, 14(4):046027, 2017 (article)

link (url) [BibTex]

link (url) [BibTex]


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Detecting distortions of peripherally presented letter stimuli under crowded conditions

Wallis, T. S. A., Tobias, S., Bethge, M., Wichmann, F. A.

Attention, Perception, & Psychophysics, 79(3):850-862, 2017 (article)

DOI [BibTex]

DOI [BibTex]


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New Directions for Learning with Kernels and Gaussian Processes (Dagstuhl Seminar 16481)

Gretton, A., Hennig, P., Rasmussen, C., Schölkopf, B.

Dagstuhl Reports, 6(11):142-167, 2017 (book)

DOI [BibTex]


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Statistical Asymmetries Between Cause and Effect

Janzing, D.

In Time in Physics, pages: 129-139, Tutorials, Schools, and Workshops in the Mathematical Sciences, (Editors: Renner, Renato and Stupar, Sandra), Springer International Publishing, Cham, 2017 (inbook)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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A parametric texture model based on deep convolutional features closely matches texture appearance for humans

Wallis, T. S. A., Funke, C. M., Ecker, A. S., Gatys, L. A., Wichmann, F. A., Bethge, M.

Journal of Vision, 17(12), 2017 (article)

DOI [BibTex]

DOI [BibTex]


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Robot Learning

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

In Encyclopedia of Machine Learning and Data Mining, pages: 1106-1109, 2nd, (Editors: Sammut, Claude and Webb, Geoffrey I.), Springer US, 2017 (inbook)

DOI [BibTex]

DOI [BibTex]


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Development and Evaluation of a Portable BCI System for Remote Data Acquisition

Emde, T.

Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2017 (mastersthesis)

[BibTex]

[BibTex]


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Brain-Computer Interfaces for patients with Amyotrophic Lateral Sclerosis

Fomina, T.

Eberhard Karls Universität Tübingen, Germany, 2017 (phdthesis)

[BibTex]

[BibTex]


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Unsupervised clustering of EOG as a viable substitute for optical eye-tracking

Flad, N., Fomina, T., Bülthoff, H. H., Chuang, L. L.

In First Workshop on Eye Tracking and Visualization (ETVIS 2015), pages: 151-167, Mathematics and Visualization, (Editors: Burch, M., Chuang, L., Fisher, B., Schmidt, A., and Weiskopf, D.), Springer, 2017 (inbook)

DOI [BibTex]

DOI [BibTex]


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BundleMAP: Anatomically Localized Classification, Regression, and Hypothesis Testing in Diffusion MRI

Khatami, M., Schmidt-Wilcke, T., Sundgren, P. C., Abbasloo, A., Schölkopf, B., Schultz, T.

Pattern Recognition, 63, pages: 593-600, 2017 (article)

DOI [BibTex]

DOI [BibTex]


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Model Selection for Gaussian Mixture Models

Huang, T., Peng, H., Zhang, K.

Statistica Sinica, 27(1):147-169, 2017 (article)

link (url) [BibTex]

link (url) [BibTex]


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An image-computable psychophysical spatial vision model

Schütt, H. H., Wichmann, F. A.

Journal of Vision, 17(12), 2017 (article)

DOI [BibTex]

DOI [BibTex]


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Methods and measurements to compare men against machines

Wichmann, F. A., Janssen, D. H. J., Geirhos, R., Aguilar, G., Schütt, H. H., Maertens, M., Bethge, M.

Electronic Imaging, pages: 36-45(10), 2017 (article)

DOI [BibTex]

DOI [BibTex]


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Generalized phase locking analysis of electrophysiology data

Safavi, S., Panagiotaropoulos, T., Kapoor, V., Logothetis, N. K., Besserve, M.

ESI Systems Neuroscience Conference (ESI-SyNC 2017): Principles of Structural and Functional Connectivity, 2017 (poster)

[BibTex]

[BibTex]


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A Comparison of Autoregressive Hidden Markov Models for Multimodal Manipulations With Variable Masses

Kroemer, O., Peters, J.

IEEE Robotics and Automation Letters, 2(2):1101-1108, 2017 (article)

DOI [BibTex]

DOI [BibTex]


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Phase Estimation for Fast Action Recognition and Trajectory Generation in Human-Robot Collaboration

Maeda, G., Ewerton, M., Neumann, G., Lioutikov, R., Peters, J.

International Journal of Robotics Research, 36(13-14):1579-1594, 2017, Special Issue on the Seventeenth International Symposium on Robotics Research (article)

DOI [BibTex]

DOI [BibTex]


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Causal models for decision making via integrative inference

Geiger, P.

University of Stuttgart, Germany, 2017 (phdthesis)

[BibTex]

[BibTex]


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A Phase-coded Aperture Camera with Programmable Optics

Chen, J., Hirsch, M., Heintzmann, R., Eberhardt, B., Lensch, H. P. A.

Electronic Imaging, 2017(17):70-75, 2017 (article)

DOI [BibTex]

DOI [BibTex]


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Absence of EEG correlates of self-referential processing depth in ALS

Fomina, T., Weichwald, S., Synofzik, M., Just, J., Schöls, L., Schölkopf, B., Grosse-Wentrup, M.

PLOS ONE, 12(6):e0180136, 2017 (article)

PDF DOI [BibTex]


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On Maximum Entropy and Inference

Gresele, L., Marsili, M.

Entropy, 19(12):article no. 642, 2017 (article)

link (url) [BibTex]

link (url) [BibTex]


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Towards Engagement Models that Consider Individual Factors in HRI: On the Relation of Extroversion and Negative Attitude Towards Robots to Gaze and Speech During a Human-Robot Assembly Task

Ivaldi, S., Lefort, S., Peters, J., Chetouani, M., Provasi, J., Zibetti, E.

International Journal of Social Robotics, 9(1):63-86, 2017 (article)

DOI [BibTex]


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Non-parametric Policy Search with Limited Information Loss

van Hoof, H., Neumann, G., Peters, J.

Journal of Machine Learning Research , 18(73):1-46, 2017 (article)

link (url) [BibTex]

link (url) [BibTex]


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Stability of Controllers for Gaussian Process Dynamics

Vinogradska, J., Bischoff, B., Nguyen-Tuong, D., Peters, J.

Journal of Machine Learning Research, 18(100):1-37, 2017 (article)

link (url) [BibTex]

link (url) [BibTex]


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Learning Optimal Configurations for Modeling Frowning by Transcranial Electrical Stimulation

Sücker, K.

Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2017 (mastersthesis)

[BibTex]

[BibTex]


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SUV-quantification of physiological lung tissue in an integrated PET/MR-system: Impact of lung density and bone tissue

Seith, F., Schmidt, H., Gatidis, S., Bezrukov, I., Schraml, C., Pfannenberg, C., la Fougère, C., Nikolaou, K., Schwenzer, N.

PLOS ONE, 12(5):1-13, 2017 (article)

DOI [BibTex]

DOI [BibTex]

2016


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Consistent Kernel Mean Estimation for Functions of Random Variables

Simon-Gabriel*, C. J., Ścibior*, A., Tolstikhin, I., Schölkopf, B.

Advances in Neural Information Processing Systems 29, pages: 1732-1740, (Editors: D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, and R. Garnett), Curran Associates, Inc., 30th Annual Conference on Neural Information Processing Systems, December 2016, *joint first authors (conference)

link (url) [BibTex]

2016

link (url) [BibTex]


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Understanding Probabilistic Sparse Gaussian Process Approximations

Bauer, M., van der Wilk, M., Rasmussen, C. E.

Advances in Neural Information Processing Systems 29, pages: 1533-1541, (Editors: D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, and R. Garnett), Curran Associates, Inc., 30th Annual Conference on Neural Information Processing Systems, December 2016 (conference)

link (url) [BibTex]

link (url) [BibTex]