183 results
(View BibTeX file of all listed publications)

**Temporal Difference Models: Model-Free Deep RL for Model-Based Control**
*6th International Conference on Learning Representations (ICLR)*, May 2018, *equal contribution (conference)

**Wasserstein Auto-Encoders: Latent Dimensionality and Random Encoders**
*Workshop at the 6th International Conference on Learning Representations (ICLR)*, May 2018 (conference)

**Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning**
*6th International Conference on Learning Representations (ICLR)*, May 2018 (conference)

**Tempered Adversarial Networks**
*Workshop at the 6th International Conference on Learning Representations (ICLR)*, May 2018 (conference)

**Learning Coupled Forward-Inverse Models with Combined Prediction Errors**
*IEEE International Conference on Robotics and Automation, (ICRA)*, pages: 2433-2439, IEEE, May 2018 (conference)

**Learning Disentangled Representations with Wasserstein Auto-Encoders**
*Workshop at the 6th International Conference on Learning Representations (ICLR)*, May 2018 (conference)

**Automatic Estimation of Modulation Transfer Functions**
*IEEE International Conference on Computational Photography (ICCP)*, May 2018 (conference)

**Causal Discovery Using Proxy Variables**
*Workshop at 6th International Conference on Learning Representations (ICLR)*, May 2018 (conference)

**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)

**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)

**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)

**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)

**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)

**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)

**Functional Programming for Modular Bayesian Inference**
*Proceedings of the ACM on Functional Programming (ICFP)*, 2(Article No. 83):1-29, ACM, 2018 (conference)

**Automatic Bayesian Density Analysis**
2018 (conference) Submitted

Babbar, R., Schölkopf, B.
**Adversarial Extreme Multi-label Classification**
2018 (conference) Submitted

**k–SVRG: Variance Reduction for Large Scale Optimization**
In 2018 (inproceedings) Submitted

**Probabilistic Deep Learning using Random Sum-Product Networks**
2018 (conference) Submitted

**A Differentially Private Kernel Two-Sample Test**
2018, *equal contribution (conference) Submitted

**Counterfactuals uncover the modular structure of deep generative models**
2018 (conference) Submitted

**Maschinelles Lernen: Entwicklung ohne Grenzen?**
In *Mit Optimismus in die Zukunft schauen. Künstliche Intelligenz - Chancen und Rahmenbedingungen*, pages: 26-34, (Editors: Bender, G. and Herbrich, R. and Siebenhaar, K.), B&S Siebenhaar Verlag, 2018 (incollection)

**Methods in Psychophysics**
In *Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience*, 5 (Methodology), 7, 4th, John Wiley & Sons, Inc., 2018 (inbook)

**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)

**Transfer Learning for BCIs**
In *Brain–Computer Interfaces Handbook*, pages: 425-442, 22, (Editors: Chang S. Nam, Anton Nijholt and Fabien Lotte), CRC Press, 2018 (incollection)

**Towards compliant humanoids: an experimental assessment of suitable task space position/orientation controllers**
In *IROS 2007*, 2007, pages: 2520-2527, (Editors: Grant, E. , T. C. Henderson), IEEE Service Center, Piscataway, NJ, USA, IEEE/RSJ International Conference on Intelligent Robots and Systems, November 2007 (inproceedings)

**Performance Stabilization and Improvement in Graph-based Semi-supervised Learning with
Ensemble Method and Graph Sharpening**
In *Korean Data Mining Society Conference*, pages: 257-262, Korean Data Mining Society, Seoul, Korea, Korean Data Mining Society Conference, November 2007 (inproceedings)

**Discriminative Subsequence Mining for Action Classification**
In *ICCV 2007*, pages: 1919-1923, IEEE Computer Society, Los Alamitos, CA, USA, 11th IEEE International Conference on Computer Vision, October 2007 (inproceedings)

**A Hilbert Space Embedding for Distributions**
In *Algorithmic Learning Theory, Lecture Notes in Computer Science 4754 *, pages: 13-31, (Editors: M Hutter and RA Servedio and E Takimoto), Springer, Berlin, Germany, 18th International Conference on Algorithmic Learning Theory (ALT), October 2007 (inproceedings)

**Cluster Identification in Nearest-Neighbor Graphs**
In *ALT 2007*, pages: 196-210, (Editors: Hutter, M. , R. A. Servedio, E. Takimoto), Springer, Berlin, Germany, 18th International Conference on Algorithmic Learning Theory, October 2007 (inproceedings)

**Support Vector Machine Learning for Interdependent and Structured Output Spaces**
In *Predicting Structured Data*, pages: 85-104, Advances in neural information processing systems, (Editors: Bakir, G. H. , T. Hofmann, B. Schölkopf, A. J. Smola, B. Taskar, S. V. N. Vishwanathan), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Inducing Metric Violations in Human Similarity Judgements**
In *Advances in Neural Information Processing Systems 19*, pages: 777-784, (Editors: Schölkopf, B. , J. Platt, T. Hofmann), MIT Press, Cambridge, MA, USA, Twentieth Annual Conference on Neural Information Processing Systems (NIPS), September 2007 (inproceedings)

**Cross-Validation Optimization for Large Scale Hierarchical
Classification Kernel Methods**
In *Advances in Neural Information Processing Systems 19*, pages: 1233-1240, (Editors: Schölkopf, B. , J. Platt, T. Hofmann), MIT Press, Cambridge, MA, USA, Twentieth Annual Conference on Neural Information Processing Systems (NIPS), September 2007 (inproceedings)

**A Local Learning Approach for Clustering**
In *Advances in Neural Information Processing Systems 19*, pages: 1529-1536, (Editors: B Schölkopf and J Platt and T Hofmann), MIT Press, Cambridge, MA, USA, 20th Annual Conference on Neural Information Processing Systems (NIPS), September 2007 (inproceedings)

**Brisk Kernel ICA**
In *Large Scale Kernel Machines*, pages: 225-250, Neural Information Processing, (Editors: Bottou, L. , O. Chapelle, D. DeCoste, J. Weston), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Branch and Bound for Semi-Supervised Support Vector Machines**
In *Advances in Neural Information Processing Systems 19*, pages: 217-224, (Editors: Schölkopf, B. , J. Platt, T. Hofmann), MIT Press, Cambridge, MA, USA, Twentieth Annual Conference on Neural Information Processing Systems (NIPS), September 2007 (inproceedings)

**A Kernel Method for the Two-Sample-Problem**
In *Advances in Neural Information Processing Systems 19*, pages: 513-520, (Editors: B Schölkopf and J Platt and T Hofmann), MIT Press, Cambridge, MA, USA, 20th Annual Conference on Neural Information Processing Systems (NIPS), September 2007 (inproceedings)

**An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models**
In *Advances in Neural Information Processing Systems 19*, pages: 673-680, (Editors: Schölkopf, B. , J. Platt, T. Hofmann), MIT Press, Cambridge, MA, USA, Twentieth Annual Conference on Neural Information Processing Systems (NIPS), September 2007 (inproceedings)

**Learning Dense 3D Correspondence**
In *Advances in Neural Information Processing Systems 19*, pages: 1313-1320, (Editors: B Schölkopf and J Platt and T Hofmann), MIT Press, Cambridge, MA, USA, 20th Annual Conference on Neural Information Processing Systems (NIPS), September 2007 (inproceedings)

**Optimal Dominant Motion Estimation using Adaptive Search of Transformation Space**
In *DAGM 2007*, pages: 204-215, (Editors: Hamprecht, F. A., C. Schnörr, B. Jähne), Springer, Berlin, Germany, 29th Annual Symposium of the German Association for Pattern Recognition, September 2007 (inproceedings)

**Training a Support Vector Machine in the Primal**
In *Large Scale Kernel Machines*, pages: 29-50, Neural Information Processing, (Editors: Bottou, L. , O. Chapelle, D. DeCoste, J. Weston), MIT Press, Cambridge, MA, USA, September 2007, This is a slightly updated version of the Neural Computation paper (inbook)

**Approximation Methods for Gaussian Process Regression**
In *Large-Scale Kernel Machines*, pages: 203-223, Neural Information Processing, (Editors: Bottou, L. , O. Chapelle, D. DeCoste, J. Weston), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Output Grouping using Dirichlet Mixtures of Linear Gaussian State-Space Models**
In *ISPA 2007*, pages: 446-451, IEEE Computer Society, Los Alamitos, CA, USA, 5th International Symposium on Image and Signal Processing and Analysis, September 2007 (inproceedings)

**Manifold Denoising**
In *Advances in Neural Information Processing Systems 19*, pages: 561-568, (Editors: Schölkopf, B. , J. Platt, T. Hofmann), MIT Press, Cambridge, MA, USA, Twentieth Annual Conference on Neural Information Processing Systems (NIPS), September 2007 (inproceedings)

**How to Find Interesting Locations in Video: A Spatiotemporal Interest Point Detector Learned from Human Eye movements**
In *Pattern Recognition*, pages: 405-414, (Editors: FA Hamprecht and C Schnörr and B Jähne), Springer, Berlin, Germany, 29th Annual Symposium of the German Association for Pattern Recognition (DAGM), September 2007 (inproceedings)

**Bayesian Inference for Sparse Generalized Linear Models**
In *ECML 2007*, pages: 298-309, Lecture Notes in Computer Science ; 4701, (Editors: Kok, J. N., J. Koronacki, R. Lopez de Mantaras, S. Matwin, D. Mladenic, A. Skowron), Springer, Berlin, Germany, 18th European Conference on Machine Learning, September 2007 (inproceedings)

**Implicit Surfaces with Globally Regularised and Compactly Supported Basis Functions**
In *Advances in Neural Information Processing Systems 19*, pages: 273-280, (Editors: B Schölkopf and J Platt and T Hofmann), MIT Press, Cambridge, MA, USA, 20th Annual Conference on Neural Information Processing Systems (NIPS), September 2007 (inproceedings)

**Trading Convexity for Scalability**
In *Large Scale Kernel Machines*, pages: 275-300, Neural Information Processing, (Editors: Bottou, L. , O. Chapelle, D. DeCoste, J. Weston), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**A Nonparametric Approach to Bottom-Up Visual Saliency**
In *Advances in Neural Information Processing Systems 19*, pages: 689-696, (Editors: B Schölkopf and J Platt and T Hofmann), MIT Press, Cambridge, MA, USA, 20th Annual Conference on Neural Information Processing Systems (NIPS), September 2007 (inproceedings)

**Information Bottleneck for Non Co-Occurrence Data**
In *Advances in Neural Information Processing Systems 19*, pages: 1241-1248, (Editors: Schölkopf, B. , J. Platt, T. Hofmann), MIT Press, Cambridge, MA, USA, Twentieth Annual Conference on Neural Information Processing Systems (NIPS), September 2007 (inproceedings)