- CSB - MetaPress - Google - Bing - Yahoo
 | 2013 | |
|---|---|---|
| c50 |      | Andrew D. Gordon, Mihhail Aizatulin, Johannes Borgström, Guillaume Claret, Thore Graepel, Aditya V. Nori, Sriram K. Rajamani, Claudio V. Russo: A model-learner pattern for bayesian reasoning. POPL 2013: 403-416 |
| 2012 | ||
| j12 | | Philipp Hennig, David H. Stern, Ralf Herbrich, Thore Graepel: Kernel Topic Models. Journal of Machine Learning Research - Proceedings Track 22: 511-519 (2012) |
| c49 | | Xi Alice Gao, Yoram Bachrach, Peter Key, Thore Graepel: Quality Expectation-Variance Tradeoffs in Crowdsourcing Contests. AAAI 2012 |
| c48 | | Yoram Bachrach, Thore Graepel, Gjergji Kasneci, Michal Kosinski, Jurgen Van Gael: Crowd IQ: aggregating opinions to boost performance. AAMAS 2012: 535-542 |
| c47 | | Thore Graepel, Kristin Lauter, Michael Naehrig: ML Confidential: Machine Learning on Encrypted Data. ICISC 2012: 1-21 |
| c46 | | Yoram Bachrach, Thore Graepel, Tom Minka, John Guiver: How To Grade a Test Without Knowing the Answers - A Bayesian Graphical Model for Adaptive Crowdsourcing and Aptitude Testing. ICML 2012 |
| c45 | | Shengbo Guo, Scott Sanner, Thore Graepel, Wray L. Buntine: Score-Based Bayesian Skill Learning. ECML/PKDD (1) 2012: 106-121 |
| c44 | | Tim Salimans, Ulrich Paquet, Thore Graepel: Collaborative learning of preference rankings. RecSys 2012: 261-264 |
| c43 | | Yoram Bachrach, Michal Kosinski, Thore Graepel, Pushmeet Kohli, David Stillwell: Personality and patterns of Facebook usage. WebSci 2012: 24-32 |
| c42 | | Pushmeet Kohli, Michael Kearns, Yoram Bachrach, Ralf Herbrich, David Stillwell, Thore Graepel: Colonel Blotto on Facebook: the effect of social relations on strategic interaction. WebSci 2012: 141-150 |
| c41 | | Michal Kosinski, Yoram Bachrach, Gjergji Kasneci, Jurgen Van Gael, Thore Graepel: Crowd IQ: measuring the intelligence of crowdsourcing platforms. WebSci 2012: 151-160 |
| i4 | | Simon Lacoste-Julien, Konstantina Palla, Alex Davies, Gjergji Kasneci, Thore Graepel, Zoubin Ghahramani: SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases. CoRR abs/1207.4525 (2012) |
| i3 | | Sameer Singh, Thore Graepel: Compiling Relational Database Schemata into Probabilistic Graphical Models. CoRR abs/1212.0967 (2012) |
| i2 | | Thore Graepel, Kristin Lauter, Michael Naehrig: ML Confidential: Machine Learning on Encrypted Data. IACR Cryptology ePrint Archive 2012: 323 (2012) |
| 2011 | ||
| c40 | | Yoram Bachrach, Pushmeet Kohli, Thore Graepel: Rip-off: playing the cooperative negotiation game. AAMAS 2011: 1179-1180 |
| c39 | | Gjergji Kasneci, Jurgen Van Gael, Thore Graepel: DBrev: Dreaming of a Database Revolution. CIDR 2011: 191-194 |
| c38 | | Weiwei Cheng, Gjergji Kasneci, Thore Graepel, David H. Stern, Ralf Herbrich: Automated feature generation from structured knowledge. CIKM 2011: 1395-1404 |
| c37 | | Scott Sanner, Shengbo Guo, Thore Graepel, Sadegh Kharazmi, Sarvnaz Karimi: Diverse retrieval via greedy optimization of expected 1-call@k in a latent subtopic relevance model. CIKM 2011: 1977-1980 |
| c36 | | Yan Xu, Xiang Cao, Abigail Sellen, Ralf Herbrich, Thore Graepel: Sociable killers: understanding social relationships in an online first-person shooter game. CSCW 2011: 197-206 |
| c35 | | Gjergji Kasneci, Jurgen Van Gael, David H. Stern, Thore Graepel: CoBayes: bayesian knowledge corroboration with assessors of unknown areas of expertise. WSDM 2011: 465-474 |
| i1 | | Philipp Hennig, David H. Stern, Ralf Herbrich, Thore Graepel: Kernel Topic Models. CoRR abs/1110.4713 (2011) |
| 2010 | ||
| j11 | | Philipp Hennig, David H. Stern, Thore Graepel: Coherent Inference on Optimal Play in Game Trees. Journal of Machine Learning Research - Proceedings Track 9: 326-333 (2010) |
| j10 | | Xinhua Zhang, Thore Graepel, Ralf Herbrich: Bayesian Online Learning for Multi-label and Multi-variate Performance Measures. Journal of Machine Learning Research - Proceedings Track 9: 956-963 (2010) |
| c34 | | David H. Stern, Horst Samulowitz, Ralf Herbrich, Thore Graepel, Luca Pulina, Armando Tacchella: Collaborative Expert Portfolio Management. AAAI 2010 |
| c33 | | Thore Graepel, Joaquin Quiñonero Candela, Thomas Borchert, Ralf Herbrich: Web-Scale Bayesian Click-Through rate Prediction for Sponsored Search Advertising in Microsoft's Bing Search Engine. ICML 2010: 13-20 |
| c32 | | Gjergji Kasneci, Jurgen Van Gael, Ralf Herbrich, Thore Graepel: Bayesian Knowledge Corroboration with Logical Rules and User Feedback. ECML/PKDD (2) 2010: 1-18 |
| 2009 | ||
| j9 | | Peter A. Flach, Sebastian Spiegler, Bruno Golénia, Simon Price, John Guiver, Ralf Herbrich, Thore Graepel, Mohammed J. Zaki: Novel tools to streamline the conference review process: experiences from SIGKDD'09. SIGKDD Explorations 11(2): 63-67 (2009) |
| c31 | | Anton Schwaighofer, Joaquin Quiñonero Candela, Thomas Borchert, Thore Graepel, Ralf Herbrich: Scalable clustering and keyword suggestion for online advertisements. KDD Workshop on Data Mining and Audience Intelligence for Advertising 2009: 27-36 |
| c30 | | David H. Stern, Ralf Herbrich, Thore Graepel: Matchbox: large scale online bayesian recommendations. WWW 2009: 111-120 |
| 2008 | ||
| c29 | | Thore Graepel, Ralf Herbrich: Large scale data analysis and modelling in online services and advertising. KDD 2008: 2 |
| 2007 | ||
| c28 | | |
| c27 | | Pierre Dangauthier, Ralf Herbrich, Tom Minka, Thore Graepel: TrueSkill Through Time: Revisiting the History of Chess. NIPS 2007 |
| 2006 | ||
| j8 | | Michael H. Bowling, Johannes Fürnkranz, Thore Graepel, Ron Musick: Machine learning and games. Machine Learning 63(3): 211-215 (2006) |
| c26 | | David H. Stern, Ralf Herbrich, Thore Graepel: Bayesian pattern ranking for move prediction in the game of Go. ICML 2006: 873-880 |
| c25 | | Ralf Herbrich, Tom Minka, Thore Graepel: TrueSkillTM: A Bayesian Skill Rating System. NIPS 2006: 569-576 |
| 2005 | ||
| j7 | | Shivani Agarwal, Thore Graepel, Ralf Herbrich, Sariel Har-Peled, Dan Roth: Generalization Bounds for the Area Under the ROC Curve. Journal of Machine Learning Research 6: 393-425 (2005) |
| j6 | | Thore Graepel, Ralf Herbrich, John Shawe-Taylor: PAC-Bayesian Compression Bounds on the Prediction Error of Learning Algorithms for Classification. Machine Learning 59(1-2): 55-76 (2005) |
| 2004 | ||
| c24 | | Shivani Agarwal, Thore Graepel, Ralf Herbrich, Dan Roth: A Large Deviation Bound for the Area Under the ROC Curve. NIPS 2004 |
| c23 | | David H. Stern, Thore Graepel, David J. C. MacKay: Modelling Uncertainty in the Game of Go. NIPS 2004 |
| 2003 | ||
| j5 | | Ralf Herbrich, Thore Graepel: Introduction to the Special Issue on Learning Theory. Journal of Machine Learning Research 4: 755-757 (2003) |
| c22 | | Jaz S. Kandola, Thore Graepel, John Shawe-Taylor: Reducing Kernel Matrix Diagonal Dominance Using Semi-definite Programming. COLT 2003: 288-302 |
| c21 | | Thore Graepel: Solving Noisy Linear Operator Equations by Gaussian Processes: Application to Ordinary and Partial Differential Equations. ICML 2003: 234-241 |
| c20 | | Thore Graepel, Ralf Herbrich: Invariant Pattern Recognition by Semi-Definite Programming Machines. NIPS 2003 |
| c19 | | Thore Graepel, Ralf Herbrich, Andriy Kharechko, John Shawe-Taylor: Semi-Definite Programming by Perceptron Learning. NIPS 2003 |
| 2002 | ||
| j4 | | Ralf Herbrich, Thore Graepel: A PAC-Bayesian margin bound for linear classifiers. IEEE Transactions on Information Theory 48(12): 3140-3150 (2002) |
| c18 | | Thore Graepel, Nicol N. Schraudolph: Stable Adaptive Momentum for Rapid Online Learning in Nonlinear Systems. ICANN 2002: 450-455 |
| c17 | | |
| c16 | | Nicol N. Schraudolph, Thore Graepel: Conjugate Directions for Stochastic Gradient Descent. ICANN 2002: 1351-1358 |
| c15 | | Nicola Cancedda, Cyril Goutte, Jean-Michel Renders, Nicolò Cesa-Bianchi, Alex Conconi, Yaoyong Li, John Shawe-Taylor, Alexei Vinokourov, Thore Graepel, Claudio Gentile: Kernel Methods for Document Filtering. TREC 2002 |
| 2001 | ||
| j3 | | Ralf Herbrich, Thore Graepel, Colin Campbell: Bayes Point Machines. Journal of Machine Learning Research 1: 245-279 (2001) |
| c14 | | Thore Graepel, Mike Goutrié, Marco Krüger, Ralf Herbrich: Learning on Graphs in the Game of Go. ICANN 2001: 347-352 |
| 2000 | ||
| c13 |  | Thore Graepel, Ralf Herbrich, John Shawe-Taylor: Generalisation Error Bounds for Sparse Linear Classifiers. COLT 2000: 298-303 |
| c12 | | Ralf Herbrich, Thore Graepel, John Shawe-Taylor: Sparsity vs. Large Margins for Linear Classifiers. COLT 2000: 304-308 |
| c11 | | Sambu Seo, Marko Wallat, Thore Graepel, Klaus Obermayer: Gaussian Process Regression: Active Data Selection and Test Point Rejection. DAGM-Symposium 2000: 27-34 |
| c10 | | |
| c9 | | Sambu Seo, Marko Wallat, Thore Graepel, Klaus Obermayer: Gaussian Process Regression: Active Data Selection and Test Point Rejection. IJCNN (3) 2000: 241-246 |
| c8 | | |
| c7 | | Ralf Herbrich, Thore Graepel: A PAC-Bayesian Margin Bound for Linear Classifiers: Why SVMs work. NIPS 2000: 224-230 |
| c6 | | |
| c5 | | |
| 1999 | ||
| j2 | | Thore Graepel, Klaus Obermayer: A Stochastic Self-Organizing Map for Proximity Data. Neural Computation 11(1): 139-155 (1999) |
| c4 | | |
| 1998 | ||
| j1 | | Thore Graepel, Matthias Burger, Klaus Obermayer: Self-organizing maps: Generalizations and new optimization techniques. Neurocomputing 21(1-3): 173-190 (1998) |
| c3 | | Thore Graepel, Ralf Herbrich, Peter Bollmann-Sdorra, Klaus Obermayer: Classification on Pairwise Proximity Data. NIPS 1998: 438-444 |
| 1997 | ||
| c2 | | Matthias Burger, Thore Graepel, Klaus Obermayer: Phase Transitions in Soft Topographic Vector Quantization. ICANN 1997: 619-624 |
| c1 | | Matthias Burger, Thore Graepel, Klaus Obermayer: An Annealed Self-Organizing Map for Source Channel Coding. NIPS 1997 |
Colors in the list of coauthors
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