2312 results
(BibTeX)

**Modeling and Learning Complex Motor Tasks: A case study on Robot Table Tennis**
Technical University Darmstadt, Germany, 2013 (phdthesis)

**Accurate detection of differential RNA processing**
*Nucleic Acids Research*, 41(10):5189-5198, 2013 (article)

**Detecting regulatory gene–environment interactions with unmeasured environmental factors**
*Bioinformatics*, 29(11):1382-1389, 2013 (article)

**im3shape: a maximum likelihood galaxy shear measurement code for cosmic gravitational lensing**
*Monthly Notices of the Royal Astronomical Society*, 434(2):1604-1618, Oxford University Press, 2013 (article)

**Maximizing Kepler science return per telemetered pixel: Detailed models of the focal plane in the two-wheel era**
*arXiv:1309.0653*, 2013 (techreport)

**Maximizing Kepler science return per telemetered pixel: Searching the habitable zones of the brightest stars**
*arXiv:1309.0654*, 2013 (techreport)

**PAC-Bayes-Empirical-Bernstein Inequality**
In *Advances in Neural Information Processing Systems 26*, pages: 109-117, (Editors: C.J.C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K.Q. Weinberger), 27th Annual Conference on Neural Information Processing Systems (NIPS), 2013 (inproceedings)

**Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik**
Springer, 2013 (book)

**On the Relations and Differences between Popper Dimension, Exclusion Dimension and VC-Dimension**
In *Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik*, pages: 53-57, 6, (Editors: Schölkopf, B., Luo, Z. and Vovk, V.), Springer, 2013 (inbook)

**PLAL: Cluster-based active learning**
In *Proceedings of the 26th Annual Conference on Learning Theory*, 30, pages: 376-397, (Editors: Shalev-Shwartz, S. and Steinwart, I.), JMLR, COLT, 2013 (inproceedings)

**Monochromatic Bi-Clustering**
In *Proceedings of the 30th International Conference on Machine Learning*, 28, pages: 145-153, (Editors: Dasgupta, S. and McAllester, D.), JMLR, ICML, 2013 (inproceedings)

**Generative Multiple-Instance Learning Models For Quantitative Electromyography**
In *Proceedings of the 29th Conference on Uncertainty in Artificial Intelligence*, AUAI Press, UAI, 2013 (inproceedings)

**Counterfactual Reasoning and Learning Systems: The Example of Computational Advertising**
*Journal of Machine Learning Research*, 14, pages: 3207-3260, 2013 (article)

**Quasi-Newton Methods: A New Direction**
*Journal of Machine Learning Research*, 14(1):843-865, March 2013 (article)

**How the result of graph clustering methods depends on the construction of the graph**
*ESAIM: Probability & Statistics*, 17, pages: 370-418, January 2013 (article)

**What can neurons do for their brain? Communicate selectivity with bursts**
*Theory in Biosciences *, 132(1):27-39, Springer, March 2013 (article)

**Apprenticeship Learning with Few Examples**
*Neurocomputing*, 104, pages: 83-96, March 2013 (article)

**A neural population model for visual pattern detection**
*Psychological Review*, 120(3):472–496, 2013 (article)

**Feedback Error Learning for Rhythmic Motor Primitives**
In *Proceedings of 2013 IEEE International Conference on Robotics and Automation (ICRA 2013)*, pages: 1317-1322, 2013 (inproceedings)

**Gaussian Process Vine Copulas for Multivariate Dependence**
In *Proceedings of the 30th International Conference on Machine Learning, W&CP 28(2)*, pages: 10-18, (Editors: S Dasgupta and D McAllester), JMLR, ICML, 2013, Poster:
http://people.tuebingen.mpg.de/dlopez/papers/icml2013_gpvine_poster.pdf (inproceedings)

**A Review of Performance Variations in SMR-Based Brain–Computer Interfaces (BCIs)**
In *Brain-Computer Interface Research*, pages: 39-51, 4, SpringerBriefs in Electrical and Computer Engineering, (Editors: Guger, C., Allison, B. Z. and Edlinger, G.), Springer, 2013 (inbook)

**The Randomized Dependence Coefficient**
In *Advances in Neural Information Processing Systems 26*, pages: 1-9, (Editors: C.J.C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K.Q. Weinberger), 27th Annual Conference on Neural Information Processing Systems (NIPS), 2013 (inproceedings)

**On a link between kernel mean maps and Fraunhofer diffraction, with an application to super-resolution beyond the diffraction limit**
In *IEEE Conference on Computer Vision and Pattern Recognition*, pages: 1083-1090, IEEE, CVPR, 2013 (inproceedings)

**Output Kernel Learning Methods**
In *International Workshop on Advances in Regularization,
Optimization, Kernel Methods and Support Vector Machines: theory and applications*, ROKS, 2013 (inproceedings)

**Alignment-based Transfer Learning for Robot Models**
In *Proceedings of the 2013 International Joint Conference on Neural Networks (IJCNN 2013)*, pages: 1-7, 2013 (inproceedings)

**Accurate indel prediction using paired-end short reads**
*BMC Genomics*, 14(132), 2013 (article)

**Nonlinear Causal Discovery for High Dimensional Data: A Kernelized Trace Method**
In *13th International Conference on Data Mining*, pages: 1003-1008, (Editors: H. Xiong, G. Karypis, B. M. Thuraisingham, D. J. Cook and X. Wu), IEEE Computer Society, ICDM, 2013 (inproceedings)

**A probabilistic approach to robot trajectory generation**
In *Proceedings of the 13th IEEE International Conference on Humanoid Robots (HUMANOIDS)*, pages: 477-483, IEEE, 13th IEEE-RAS International Conference on Humanoid Robots, 2013 (inproceedings)

**Geometric optimisation on positive definite matrices for elliptically contoured distributions**
In *Advances in Neural Information Processing Systems 26*, pages: 2562-2570, (Editors: C.J.C. Burges and L. Bottou and M. Welling and Z. Ghahramani and K.Q. Weinberger), 27th Annual Conference on Neural Information Processing Systems (NIPS), 2013 (inproceedings)

**Coupling between spiking activity and beta band spatio-temporal patterns in the macaque PFC**
43rd Annual Meeting of the Society for Neuroscience (Neuroscience), 2013 (poster)

**Camera-specific Image Denoising**
Eberhard Karls Universität Tübingen, Germany, October 2013 (diplomathesis)

**Regional effects of magnetization dispersion on quantitative perfusion imaging for pulsed and continuous arterial spin labeling**
*Magnetic Resonance in Medicine*, 69(2):524-530, Febuary 2013 (article)

**Fast Probabilistic Optimization from Noisy Gradients**
In *Proceedings of The 30th International Conference on Machine Learning, JMLR W&CP 28(1)*, pages: 62–70, (Editors: S Dasgupta and D McAllester), ICML, 2013 (inproceedings)

**Structure and Dynamics of Information Pathways in On-line Media**
In *6th ACM International Conference on Web Search and Data Mining (WSDM)*, pages: 23-32, (Editors: S Leonardi, A Panconesi, P Ferragina, and A Gionis), ACM, WSDM, 2013 (inproceedings)

**Evaluation and Analysis of the Performance of the EXP3 Algorithm in Stochastic Environments**
In *Proceedings of the Tenth European Workshop on Reinforcement Learning *, pages: 103-116, (Editors: MP Deisenroth and C Szepesvári and J Peters), JMLR, EWRL, 2013 (inproceedings)

**Domain adaptation under Target and Conditional Shift**
In *Proceedings of the 30th International Conference on Machine Learning, W&CP 28 (3)*, pages: 819–827, (Editors: S Dasgupta and D McAllester), JMLR, ICML, 2013 (inproceedings)

**From Ordinary Differential Equations to Structural Causal Models: the deterministic case **
In *Proceedings of the Twenty-Ninth Conference Annual Conference on Uncertainty in Artificial Intelligence*, pages: 440-448, (Editors: A Nicholson and P Smyth), AUAI Press, Corvallis, Oregon, UAI, 2013 (inproceedings)

**A machine learning approach for non-blind image deconvolution**
In *IEEE Conference on Computer Vision and Pattern Recognition*, pages: 1067-1074, IEEE, CVPR, 2013 (inproceedings)

**Domain Generalization via Invariant Feature Representation**
30th International Conference on Machine Learning (ICML2013), 2013 (poster)

**When luminance increment thresholds depend on apparent lightness**
*Journal of Vision*, 13(6):1-11, 2013 (article)

**Autonomous Reinforcement Learning with Hierarchical REPS**
In *Proceedings of the 2013 International Joint Conference on Neural Networks (IJCNN 2013)*, pages: 1-8, 2013 (inproceedings)

**Efficient network-guided multi-locus association mapping with graph cuts**
*Bioinformatics*, 29(13):i171-i179, 2013 (article)

**Geometric Tree Kernels: Classification of COPD from Airway Tree Geometry**
In *Information Processing in Medical Imaging*, pages: 171-183, (Editors: JC Gee and S Joshi and KM Pohl and WM Wells and L Zöllei), Springer, Berlin Heidelberg, 23rd International Conference on Information Processing in Medical Imaging (IPMI), 2013, Lecture Notes in Computer Science, Vol. 7017 (inproceedings)

**On estimation of functional causal models: Post-nonlinear causal model as an example**
In *First IEEE ICDM workshop on causal discovery *, 2013, Held in conjunction with the 12th IEEE International Conference on Data Mining (ICDM 2013) (inproceedings)

**Object Modeling and Segmentation by Robot Interaction with Cluttered Environments**
In *Proceedings of the IEEE International Conference on Humanoid Robots (HUMANOIDS)*, pages: 169-176, IEEE, 13th IEEE-RAS International Conference on Humanoid Robots, 2013 (inproceedings)

**Reflection methods for user-friendly submodular optimization**
In *Advances in Neural Information Processing Systems 26*, pages: 1313-1321, (Editors: C.J.C. Burges and L. Bottou and M. Welling and Z. Ghahramani and K.Q. Weinberger), 27th Annual Conference on Neural Information Processing Systems (NIPS), 2013 (inproceedings)

**Semi-supervised learning in causal and anticausal settings**
In *Empirical Inference*, pages: 129-141, 13, Festschrift in Honor of Vladimir Vapnik, (Editors: Schölkopf, B., Luo, Z. and Vovk, V.), Springer, 2013 (inbook)

**Analyzing locking of spikes to spatio-temporal patterns in the macaque prefrontal cortex**
Bernstein Conference, 2013 (poster)

**Studying large-scale brain networks: electrical stimulation and neural-event-triggered fMRI**
Twenty-Second Annual Computational Neuroscience Meeting (CNS*2013), July 2013, journal = {BMC Neuroscience},
year = {2013},
month = {7},
volume = {14},
number = {Supplement 1},
pages = {A1}, (talk)

**Gaussian Process Vine Copulas for Multivariate Dependence**
International Conference on Machine Learning (ICML), 2013 (poster)