58 results
(View BibTeX file of all listed publications)

**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)

**MR-Based Attenuation Correction for Combined Brain PET/MR: Robustness of Atlas- and Pattern Recognition Method to Atlas Registration Failures**
IEEE Nuclear Science Symposium and Medical Imaging Conference (IEEE MIC), 2013 (talk)

**Proceedings of the 10th European Workshop on Reinforcement Learning, Volume 24 **
pages: 173, JMLR, European Workshop On Reinforcement Learning, EWRL, 2013 (proceedings)

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

**Support Vector Machines, Support Measure Machines, and Quasar Target Selection**
Center for Cosmology and Particle Physics (CCPP), New York University, December 2012 (talk)

**Hilbert Space Embedding for Dirichlet Process Mixtures**
NIPS Workshop on Confluence between Kernel Methods and Graphical Models, December 2012 (talk)

**Simultaneous small animal PET/MR in activated and resting state reveals multiple brain networks**
20th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM), May 2012 (talk)

**A new PET insert for simultaneous PET/MR small animal imaging**
20th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM), May 2012 (talk)

**Evaluation of a new, large field of view, small animal PET/MR system**
50. Jahrestagung der Deutschen Gesellschaft fuer Nuklearmedizin (NuklearMedizin), April 2012 (talk)

**Simultaneous small animal PET/MR reveals different brain networks during stimulation and rest**
World Molecular Imaging Congress (WMIC), 2012 (talk)

Muandet, K.
**Support Measure Machines for Quasar Target Selection**
Astro Imaging Workshop, 2012 (talk)

**PAC-Bayesian Analysis: A Link Between Inference and Statistical Physics
**
Workshop on Statistical Physics of Inference and Control Theory, 2012 (talk)

**PET Performance Measurements of a Next Generation Dedicated Small Animal PET/MR Scanner**
Nuclear Science Symposium and Medical Imaging Conference (NSS-MIC), 2012 (talk)

**PAC-Bayesian Analysis of Supervised, Unsupervised, and Reinforcement Learning
**
Tutorial at the 29th International Conference on Machine Learning (ICML), 2012 (talk)

**Influence of MR-based attenuation correction on lesions within bone and susceptibility artifact regions**
Molekulare Bildgebung (MoBi), 2012 (talk)

**Structured Apprenticeship Learning**
European Workshop on Reinforcement Learning (EWRL), 2012 (talk)

**PAC-Bayesian Analysis and Its Applications**
Tutorial at The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2012 (talk)

**Machine Learning and Interpretation in Neuroimaging - Revised Selected and Invited Contributions**
pages: 266, Springer, Heidelberg, Germany, International Workshop, MLINI, Held at NIPS, 2012, Lecture Notes in Computer Science, Vol. 7263 (proceedings)

**Solving Nonlinear Continuous State-Action-Observation POMDPs for Mechanical Systems with Gaussian Noise
**
European Workshop on Reinforcement Learning (EWRL), 2012 (talk)

**Kernel Bellman Equations in POMDPs**
Technical Committee on Infomation-Based Induction Sciences and Machine Learning (IBISML'12), 2012 (talk)

**MICCAI, Workshop on Computational Diffusion MRI, 2012 (electronic publication)
**
15th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Workshop on Computational Diffusion MRI , 2012 (proceedings)

**Beta oscillations propagate as traveling waves in the macaque prefrontal cortex**
42nd Annual Meeting of the Society for Neuroscience (Neuroscience), 2012 (talk)

**Machine Learning for Brain-Computer Interfaces**
Mini-Symposia on Assistive Machine Learning for People with Disabilities at NIPS (AMD), December 2009 (talk)

**PAC-Bayesian Approach to Formulation of Clustering Objectives**
NIPS Workshop on "Clustering: Science or Art? Towards Principled Approaches", December 2009 (talk)

**Semi-supervised Kernel Canonical Correlation Analysis of Human Functional Magnetic Resonance Imaging Data**
Women in Machine Learning Workshop (WiML), December 2009 (talk)

**Event-Related Potentials in Brain-Computer Interfacing**
Invited lecture on the bachelor & masters course "Introduction to Brain-Computer Interfacing", October 2009 (talk)

**BCI2000 and Python**
Invited lecture at the 5th International BCI2000 Workshop, October 2009 (talk)

**Implementing a Signal Processing Filter in BCI2000 Using C++**
Invited lecture at the 5th International BCI2000 Workshop, October 2009 (talk)

**Learning Motor Primitives for Robotics**
Advanced Telecommunications Research Center ATR, June 2009 (talk)

**Learning To Detect Unseen Object Classes by Between-Class Attribute Transfer**
IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), June 2009 (talk)

**A Kernel Method for the Two-Sample-Problem**
20th Annual Conference on Neural Information Processing Systems (NIPS), December 2006 (talk)

**Ab-initio gene finding using machine learning**
NIPS Workshop on New Problems and Methods in Computational Biology, December 2006 (talk)

**Graph boosting for molecular QSAR analysis**
NIPS Workshop on New Problems and Methods in Computational Biology, December 2006 (talk)

**Inferring Causal Directions by Evaluating the Complexity of Conditional Distributions**
NIPS Workshop on Causality and Feature Selection, December 2006 (talk)

**Learning Optimal EEG Features Across Time, Frequency and Space**
NIPS Workshop on Current Trends in Brain-Computer Interfacing, December 2006 (talk)

**Semi-Supervised Learning**
Advanced Methods in Sequence Analysis Lectures, November 2006 (talk)

**A Machine Learning Approach for Determining the PET Attenuation Map from Magnetic Resonance Images**
IEEE Medical Imaging Conference, November 2006 (talk)

**Semi-Supervised Support Vector Machines and Application to Spam Filtering**
ECML Discovery Challenge Workshop, September 2006 (talk)

**Inferential Structure Determination: Probabilistic determination and validation of NMR structures**
Gordon Research Conference on Computational Aspects of Biomolecular
NMR, September 2006 (talk)

**Machine Learning Algorithms for Polymorphism Detection**
2nd ISCB Student Council Symposium, August 2006 (talk)

**Inferential structure determination: Overview and new developments**
Sixth CCPN Annual Conference: Efficient and Rapid Structure Determination by NMR, July 2006 (talk)

**MCMC inference in (Conditionally) Conjugate Dirichlet Process Gaussian Mixture Models**
ICML Workshop on Learning with Nonparametric Bayesian Methods, June 2006 (talk)

**Sampling for non-conjugate infinite latent feature models**
(Editors: Bernardo, J. M.), 8th Valencia International Meeting on Bayesian Statistics (ISBA), June 2006 (talk)

**Advances in Neural Information Processing Systems 18: Proceedings of the 2005 Conference **
*Proceedings of the 19th Annual Conference on Neural Information Processing Systems (NIPS 2005)*, pages: 1676, MIT Press, Cambridge, MA, USA, 19th Annual Conference on Neural Information Processing Systems (NIPS), May 2006 (proceedings)

**An Inventory of Sequence Polymorphisms For Arabidopsis**
17th International Conference on Arabidopsis Research, April 2006 (talk)

**Machine Learning Challenges: evaluating predictive uncertainty, visual object classification and recognising textual entailment**
*Proceedings of the First Pascal Machine Learning Challenges Workshop on Machine Learning Challenges, Evaluating Predictive Uncertainty, Visual Object Classification and Recognizing Textual Entailment (MLCW 2005)*, pages: 462, Lecture Notes in Computer Science, Springer, Heidelberg, Germany, First Pascal Machine Learning Challenges Workshop (MLCW), 2006 (proceedings)

Zhou, D.
**How to learn from very few examples?**
October 2004 (talk)

Zhou, D.
**Discrete vs. Continuous: Two Sides of Machine Learning**
October 2004 (talk)

Zhou, D.
**Discrete vs. Continuous: Two Sides of Machine Learning**
October 2004 (talk)