ei
Pong*, V., Gu*, S., Dalal, M., Levine, S.
Temporal Difference Models: Model-Free Deep RL for Model-Based Control
6th International Conference on Learning Representations (ICLR), May 2018, *equal contribution (conference)
ei
Rubenstein, P. K., Schölkopf, B., Tolstikhin, I.
Wasserstein Auto-Encoders: Latent Dimensionality and Random Encoders
Workshop at the 6th International Conference on Learning Representations (ICLR), May 2018 (conference)
ei
Eysenbach, B., Gu, S., Ibarz, J., Levine, S.
Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning
6th International Conference on Learning Representations (ICLR), May 2018 (conference)
ei
Sajjadi, M. S. M., Parascandolo, G., Mehrjou, A., Schölkopf, B.
Tempered Adversarial Networks
Workshop at the 6th International Conference on Learning Representations (ICLR), May 2018 (conference)
ei
Koert, D., Maeda, G., Neumann, G., Peters, J.
Learning Coupled Forward-Inverse Models with Combined Prediction Errors
IEEE International Conference on Robotics and Automation, (ICRA), pages: 2433-2439, IEEE, May 2018 (conference)
ei
Rubenstein, P. K., Schölkopf, B., Tolstikhin, I.
Learning Disentangled Representations with Wasserstein Auto-Encoders
Workshop at the 6th International Conference on Learning Representations (ICLR), May 2018 (conference)
ei
sf
Bauer, M., Volchkov, V., Hirsch, M., Schölkopf, B.
Automatic Estimation of Modulation Transfer Functions
IEEE International Conference on Computational Photography (ICCP), May 2018 (conference)
ei
Rojas-Carulla, M., Baroni, M., Lopez-Paz, D.
Causal Discovery Using Proxy Variables
Workshop at 6th International Conference on Learning Representations (ICLR), May 2018 (conference)
ei
Pinsler, R., Akrour, R., Osa, T., Peters, J., Neumann, G.
Sample and Feedback Efficient Hierarchical Reinforcement Learning from Human Preferences
IEEE International Conference on Robotics and Automation, (ICRA), pages: 596-601, IEEE, May 2018 (conference)
ei
Besserve, M., Shajarisales, N., Schölkopf, B., Janzing, D.
Group invariance principles for causal generative models
Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), 84, pages: 557-565, Proceedings of Machine Learning Research, (Editors: Amos Storkey and Fernando Perez-Cruz), PMLR, April 2018 (conference)
ei
Locatello, F., Khanna, R., Ghosh, J., Rätsch, G.
Boosting Variational Inference: an Optimization Perspective
Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), 84, pages: 464-472, Proceedings of Machine Learning Research, (Editors: Amos Storkey and Fernando Perez-Cruz), PMLR, April 2018 (conference)
ei
Blöbaum, P., Janzing, D., Washio, T., Shimizu, S., Schölkopf, B.
Cause-Effect Inference by Comparing Regression Errors
Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS) , 84, pages: 900-909, Proceedings of Machine Learning Research, (Editors: Amos Storkey and Fernando Perez-Cruz), PMLR, April 2018 (conference)
ei
Schwarz, K., Wieschollek, P., Lensch, H. P. A.
Will People Like Your Image? Learning the Aesthetic Space
2018 IEEE Winter Conference on Applications of Computer Vision (WACV), pages: 2048-2057, March 2018 (conference)
ei
Kim, J., Tabibian, B., Oh, A., Schölkopf, B., Gomez Rodriguez, M.
Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation
Proceedings of the 11th ACM International Conference on Web Search and Data Mining (WSDM), pages: 324-332, (Editors: Yi Chang, Chengxiang Zhai, Yan Liu, and Yoelle Maarek), ACM, Febuary 2018 (conference)
ei
Ścibior, A., Kammar, O., Ghahramani, Z.
Functional Programming for Modular Bayesian Inference
Proceedings of the ACM on Functional Programming (ICFP), 2(Article No. 83):1-29, ACM, 2018 (conference)
ei
Vergari, A., Molina, A., Peharz, R., Ghahramani, Z., Kersting, K., Valera, I.
Automatic Bayesian Density Analysis
2018 (conference) Submitted
am
mg
Ponton, B., Herzog, A., Del Prete, A., Schaal, S., Righetti, L.
On Time Optimization of Centroidal Momentum Dynamics
In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 5776-5782, IEEE, Brisbane, Australia, 2018 (inproceedings)
ei
Babbar, R., Schölkopf, B.
Adversarial Extreme Multi-label Classification
2018 (conference) Submitted
ei
Raj, A., Stich, S.
k–SVRG: Variance Reduction for Large Scale Optimization
In 2018 (inproceedings) Submitted
ei
Peharz, R., Vergari, A., Stelzner, K., Molina, A., Trapp, M., Kersting, K., Ghahramani, Z.
Probabilistic Deep Learning using Random Sum-Product Networks
2018 (conference) Submitted
ei
Raj*, A., Law*, L., Sejdinovic*, D., Park, M.
A Differentially Private Kernel Two-Sample Test
2018, *equal contribution (conference) Submitted
ei
Besserve, M., Sun, R., Schölkopf, B.
Counterfactuals uncover the modular structure of deep generative models
2018 (conference) Submitted
ei
Ścibior, A., Kammar, O., Vákár, M., Staton, S., Yang, H., Cai, Y., Ostermann, K., Moss, S. K., Heunen, C., Ghahramani, Z.
Denotational Validation of Higher-order Bayesian Inference
Proceedings of the ACM on Principles of Programming Languages (POPL), 2(Article No. 60):1-29, ACM, 2018 (conference)
am
mg
Rotella, N., Schaal, S., Righetti, L.
Unsupervised Contact Learning for Humanoid Estimation and Control
In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 411-417, IEEE, Brisbane, Australia, 2018 (inproceedings)
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Gams, A., Mason, S., Ude, A., Schaal, S., Righetti, L.
Learning Task-Specific Dynamics to Improve Whole-Body Control
In Hua, IEEE, Beijing, China, November 2018 (inproceedings)
am
mg
Mason, S., Rotella, N., Schaal, S., Righetti, L.
An MPC Walking Framework With External Contact Forces
In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 1785-1790, IEEE, Brisbane, Australia, May 2018 (inproceedings)
ei
Simon-Gabriel*, C. J., Ścibior*, A., Tolstikhin, I., Schölkopf, B.
Consistent Kernel Mean Estimation for Functions of Random Variables
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)
ei
Bauer, M., van der Wilk, M., Rasmussen, C. E.
Understanding Probabilistic Sparse Gaussian Process Approximations
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)
ei
Tolstikhin, I., Sriperumbudur, B. K., Schölkopf, B.
Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels
Advances in Neural Information Processing Systems 29, pages: 1930-1938, (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)
ei
Parisi, S., Blank, A., Viernickel, T., Peters, J.
Local-utopia Policy Selection for Multi-objective Reinforcement Learning
In IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL), pages: 1-7, IEEE, December 2016 (inproceedings)
ei
Pentina, A., Urner, R.
Lifelong Learning with Weighted Majority Votes
Advances in Neural Information Processing Systems 29, pages: 3612-3620, (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)
ei
Kontorovich, A., Sabato, S., Urner, R.
Active Nearest-Neighbor Learning in Metric Spaces
Advances in Neural Information Processing Systems 29, pages: 856-864, (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)
ei
Belousov, B., Neumann, G., Rothkopf, C., Peters, J.
Catching heuristics are optimal control policies
Advances in Neural Information Processing Systems 29, pages: 1426-1434, (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)
ei
Ewerton, M., Maeda, G., Kollegger, G., Wiemeyer, J., Peters, J.
Incremental Imitation Learning of Context-Dependent Motor Skills
IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids), pages: 351-358, IEEE, November 2016 (conference)
am
ei
Gomez-Gonzalez, S., Neumann, G., Schölkopf, B., Peters, J.
Using Probabilistic Movement Primitives for Striking Movements
16th IEEE-RAS International Conference on Humanoid Robots (Humanoids), pages: 502-508, November 2016 (conference)
ei
Koert, D., Maeda, G., Lioutikov, R., Neumann, G., Peters, J.
Demonstration Based Trajectory Optimization for Generalizable Robot Motions
IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids), pages: 351-358, IEEE, November 2016 (conference)
am
ei
Huang, Y., Büchler, D., Koc, O., Schölkopf, B., Peters, J.
Jointly Learning Trajectory Generation and Hitting Point Prediction in Robot Table Tennis
16th IEEE-RAS International Conference on Humanoid Robots (Humanoids), pages: 650-655, November 2016 (conference)
ei
Tanneberg, D., Paraschos, A., Peters, J., Rueckert, E.
Deep Spiking Networks for Model-based Planning in Humanoids
IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids), pages: 656-661, IEEE, November 2016 (conference)
ei
Maeda, G., Maloo, A., Ewerton, M., Lioutikov, R., Peters, J.
Anticipative Interaction Primitives for Human-Robot Collaboration
AAAI Fall Symposium Series. Shared Autonomy in Research and Practice, pages: 325-330, November 2016 (conference)
ei
Lopez-Paz, D., Schölkopf, B., Bottou, L., Vapnik, V.
Unifying distillation and privileged information
International Conference on Learning Representations (ICLR), November 2016 (conference)
ei
Xiao, L., Wang, J., Heidrich, W., Hirsch, M.
Learning High-Order Filters for Efficient Blind Deconvolution of Document Photographs
Computer Vision - ECCV 2016, Lecture Notes in Computer Science, LNCS 9907, Part III, pages: 734-749, (Editors: Bastian Leibe, Jiri Matas, Nicu Sebe and Max Welling), Springer, October 2016 (conference)
ei
Sharma, D., Tanneberg, D., Grosse-Wentrup, M., Peters, J., Rueckert, E.
Adaptive Training Strategies for BCIs
Cybathlon Symposium, October 2016 (conference)
ei
Osa, T., Peters, J., Neumann, G.
Experiments with Hierarchical Reinforcement Learning of Multiple Grasping Policies
International Symposium on Experimental Robotics (ISER), 1, pages: 160-172, Springer Proceedings in Advanced Robotics, (Editors: Dana Kulic, Yoshihiko Nakamura, Oussama Khatib and Gentiane Venture), Springer, October 2016 (conference)
ei
van Hoof, H., Chen, N., Karl, M., van der Smagt, P., Peters, J.
Stable Reinforcement Learning with Autoencoders for Tactile and Visual Data
Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), pages: 3928-3934, IEEE, October 2016 (conference)
am
ei
Koc, O., Maeda, G., Peters, J.
A New Trajectory Generation Framework in Robotic Table Tennis
Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), pages: 3750-3756, October 2016 (conference)
ei
Manschitz, S., Gienger, M., Kober, J., Peters, J.
Probabilistic Decomposition of Sequential Force Interaction Tasks into Movement Primitives
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 3920-3927, IEEE, October 2016 (conference)
ei
Fiebig, K., Jayaram, V., Peters, J., Grosse-Wentrup, M.
Multi-task logistic regression in brain-computer interfaces
6th Workshop on Brain-Machine Interface Systems at IEEE International Conference on Systems, Man, and Cybernetics (SMC 2016), pages: 002307-002312, IEEE, October 2016 (conference)
ei
Yi, Z., Calandra, R., Veiga, F., van Hoof, H., Hermans, T., Zhang, Y., Peters, J.
Active Tactile Object Exploration with Gaussian Processes
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 4925-4930, IEEE, October 2016 (conference)
ei
Ben-David, S., Urner, R.
On Version Space Compression
Algorithmic Learning Theory - 27th International Conference (ALT), 9925, pages: 50-64, Lecture Notes in Computer Science, (Editors: Ortner, R., Simon, H. U., and Zilles, S.), September 2016 (conference)
ei
Kohlschuetter, J., Peters, J., Rueckert, E.
Learning Probabilistic Features from EMG Data for Predicting Knee Abnormalities
XIV Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON), pages: 668-672, (Editors: Kyriacou, E., Christofides, S., and Pattichis, C. S.), September 2016 (conference)