52 results
(View BibTeX file of all listed publications)

**Unsupervised identification of neural events in local field potentials**
44th Annual Meeting of the Society for Neuroscience (Neuroscience), 2014 (talk)

**Quantifying statistical dependency**
Research Network on Learning Systems Summer School, 2014 (talk)

**Causal Inference from Passive Observations**
24th Summer School University of Jyväskylā, Finland, August, 2014 (talk)

**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)

**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)

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)

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

**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)

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

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

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)

**Grundlagen von Support Vector Maschinen und Anwendungen in der Bildverarbeitung**
September 2004 (talk)

Bousquet, O.
**Introduction to Category Theory**
Internal Seminar, January 2004 (talk)

Bousquet, O.
**Advanced Statistical Learning Theory**
Machine Learning Summer School, 2004 (talk)

Bousquet, O.
**Statistical Learning Theory**
Machine Learning Summer School, August 2003 (talk)

**Remarks on Statistical Learning Theory**
Machine Learning Summer School, August 2003 (talk)

**Rademacher and Gaussian averages in Learning Theory**
Universite de Marne-la-Vallee, March 2003 (talk)

Bousquet, O., Schölkopf, B.
**Statistical Learning Theory**
March 2003 (talk)