Thore Graepel
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
50
Venues
21
Active years
1997–2022
Best venue rank
A*
Where they publish
Papers
50 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2022 | ICLR | EigenGame Unloaded: When playing games is better than optimizing. | Ian Gemp, Brian McWilliams, Claire Vernade, Thore Graepel |
| 2022 | ICLR | NeuPL: Neural Population Learning. | Siqi Liu, Luke Marris, Daniel Hennes, Josh Merel, Nicolas Heess, Thore Graepel |
| 2021 | ICLR | EigenGame: PCA as a Nash Equilibrium. | Ian Gemp, Brian McWilliams, Claire Vernade, Thore Graepel |
| 2021 | ICML | Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot. | Joel Z. Leibo, Edgar A. Duez-Guzmn, Alexander Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, Thore Graepel |
| 2021 | ICML | Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers. | Luke Marris, Paul Muller, Marc Lanctot, Karl Tuyls, Thore Graepel |
| 2021 | IJCAI | A Neural Network Auction For Group Decision Making Over a Continuous Space. | Yoram Bachrach, Ian Gemp, Marta Garnelo, Jnos Kramr, Tom Eccles, Dan Rosenbaum, Thore Graepel |
| 2020 | ICLR | Smooth markets: A basic mechanism for organizing gradient-based learners. | David Balduzzi, Wojciech M. Czarnecki, Tom Anthony, Ian Gemp, Edward Hughes, Joel Z. Leibo, Georgios Piliouras, Thore Graepel |
| 2020 | ICLR | A Generalized Training Approach for Multiagent Learning. | Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Prolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Rmi Munos |
| 2020 | IJCNN | Adaptive Mechanism Design: Learning to Promote Cooperation. | Tobias Baumann, Thore Graepel, John Shawe-Taylor |
| 2019 | ICLR | Emergent Coordination Through Competition. | Siqi Liu, Guy Lever, Josh Merel, Saran Tunyasuvunakool, Nicolas Heess, Thore Graepel |
| 2019 | ICLR | Relational Forward Models for Multi-Agent Learning. | Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano, Vincius Flores Zambaldi, Jnos Kramr, Neil C. Rabinowitz, Thore Graepel, Matthew M. Botvinick, Peter W. Battaglia |
| 2019 | ICML | Open-ended learning in symmetric zero-sum games. | David Balduzzi, Marta Garnelo, Yoram Bachrach, Wojciech Czarnecki, Julien Prolat, Max Jaderberg, Thore Graepel |
| 2018 | ICML | The Mechanics of n-Player Differentiable Games. | David Balduzzi, Sbastien Racanire, James Martens, Jakob N. Foerster, Karl Tuyls, Thore Graepel |
| 2015 | ESOP | Probabilistic Programs as Spreadsheet Queries. | Andrew D. Gordon, Claudio V. Russo, Marcin Szymczak, Johannes Borgstrm, Nicolas Rolland, Thore Graepel, Daniel Tarlow |
| 2014 | ECIR | Learning a Theory of Marriage (and Other Relations) from a Web Corpus. | Sandro Bauer, Stephen Clark, Laura Rimell, Thore Graepel |
| 2014 | POPL | Tabular: a schema-driven probabilistic programming language. | Andrew D. Gordon, Thore Graepel, Nicolas Rolland, Claudio V. Russo, Johannes Borgstrm, John Guiver |
| 2013 | CIKM | Automated probabilistic modeling for relational data. | Sameer Singh, Thore Graepel |
| 2013 | KDD | SIGMa: simple greedy matching for aligning large knowledge bases. | Simon Lacoste-Julien, Konstantina Palla, Alex Davies, Gjergji Kasneci, Thore Graepel, Zoubin Ghahramani |
| 2013 | POPL | A model-learner pattern for bayesian reasoning. | Andrew D. Gordon, Mihhail Aizatulin, Johannes Borgstrm, Guillaume Claret, Thore Graepel, Aditya V. Nori, Sriram K. Rajamani, Claudio V. Russo |
| 2013 | WWW | Inferring the demographics of search users: social data meets search queries. | Bin Bi, Milad Shokouhi, Michal Kosinski, Thore Graepel |
| 2012 | AAAI | Quality Expectation-Variance Tradeoffs in Crowdsourcing Contests. | Xi Alice Gao, Yoram Bachrach, Peter B. Key, Thore Graepel |
| 2012 | AAMAS | Crowd IQ: aggregating opinions to boost performance. | Yoram Bachrach, Thore Graepel, Gjergji Kasneci, Michal Kosinski, Jurgen Van Gael |
| 2012 | ICISC | ML Confidential: Machine Learning on Encrypted Data. | Thore Graepel, Kristin E. Lauter, Michael Naehrig |
| 2012 | ICML | How To Grade a Test Without Knowing the Answers - A Bayesian Graphical Model for Adaptive Crowdsourcing and Aptitude Testing. | Yoram Bachrach, Thore Graepel, Tom Minka, John Guiver |
| 2012 | RecSys | Collaborative learning of preference rankings. | Tim Salimans, Ulrich Paquet, Thore Graepel |
| 2011 | CIDR | DBrev: Dreaming of a Database Revolution. | Gjergji Kasneci, Jurgen Van Gael, Thore Graepel |
| 2011 | CIKM | Automated feature generation from structured knowledge. | Weiwei Cheng, Gjergji Kasneci, Thore Graepel, David H. Stern, Ralf Herbrich |
| 2011 | CIKM | Diverse retrieval via greedy optimization of expected 1-call@k in a latent subtopic relevance model. | Scott Sanner, Shengbo Guo, Thore Graepel, Sadegh Kharazmi, Sarvnaz Karimi |
| 2011 | CSCW | Sociable killers: understanding social relationships in an online first-person shooter game. | Yan Xu, Xiang Cao, Abigail Sellen, Ralf Herbrich, Thore Graepel |
| 2011 | WSDM | CoBayes: bayesian knowledge corroboration with assessors of unknown areas of expertise. | Gjergji Kasneci, Jurgen Van Gael, David H. Stern, Thore Graepel |
| 2010 | AAAI | Collaborative Expert Portfolio Management. | David H. Stern, Horst Samulowitz, Ralf Herbrich, Thore Graepel, Luca Pulina, Armando Tacchella |
| 2010 | ICML | Web-Scale Bayesian Click-Through rate Prediction for Sponsored Search Advertising in Microsoft's Bing Search Engine. | Thore Graepel, Joaquin Quionero Candela, Thomas Borchert, Ralf Herbrich |
| 2009 | KDD | Scalable clustering and keyword suggestion for online advertisements. | Anton Schwaighofer, Joaquin Quionero Candela, Thomas Borchert, Thore Graepel, Ralf Herbrich |
| 2009 | WWW | Matchbox: large scale online bayesian recommendations. | David H. Stern, Ralf Herbrich, Thore Graepel |
| 2008 | KDD | Large scale data analysis and modelling in online services and advertising. | Thore Graepel, Ralf Herbrich |
| 2007 | ICML | Learning to solve game trees. | David H. Stern, Ralf Herbrich, Thore Graepel |
| 2006 | ICML | Bayesian pattern ranking for move prediction in the game of Go. | David H. Stern, Ralf Herbrich, Thore Graepel |
| 2005 | AISTATS | Poisson-Networks: A Model for Structured Poisson Processes. | Shyamsundar Rajaram, Thore Graepel, Ralf Herbrich |
| 2003 | AISTATS | Combining Conjugate Direction Methods with Stochastic Approximation of Gradients. | Nicol N. Schraudolph, Thore Graepel |
| 2003 | COLT | Reducing Kernel Matrix Diagonal Dominance Using Semi-definite Programming. | Jaz S. Kandola, Thore Graepel, John Shawe-Taylor |
| 2003 | ICML | Solving Noisy Linear Operator Equations by Gaussian Processes: Application to Ordinary and Partial Differential Equations. | Thore Graepel |
| 2002 | ICANN | Kernel Matrix Completion by Semidefinite Programming. | Thore Graepel |
| 2002 | ICANN | Stable Adaptive Momentum for Rapid Online Learning in Nonlinear Systems. | Thore Graepel, Nicol N. Schraudolph |
| 2002 | ICANN | Conjugate Directions for Stochastic Gradient Descent. | Nicol N. Schraudolph, Thore Graepel |
| 2001 | ICANN | Learning on Graphs in the Game of Go. | Thore Graepel, Mike Goutri, Marco Krger, Ralf Herbrich |
| 2000 | COLT | Generalisation Error Bounds for Sparse Linear Classifiers. | Thore Graepel, Ralf Herbrich, John Shawe-Taylor |
| 2000 | COLT | Sparsity vs. Large Margins for Linear Classifiers. | Ralf Herbrich, Thore Graepel, John Shawe-Taylor |
| 2000 | ESANN | Robust Bayes Point Machines. | Ralf Herbrich, Thore Graepel, Colin Campbell |
| 2000 | IJCNN | Gaussian Process Regression: Active Data Selection and Test Point Rejection. | Sambu Seo, Marko Wallat, Thore Graepel, Klaus Obermayer |
| 1997 | ICANN | Phase Transitions in Soft Topographic Vector Quantization. | Matthias Burger, Thore Graepel, Klaus Obermayer |