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John Guiver
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2020 – today
- 2021
- [c15]John M. Winn, Matteo Venanzi, Tom Minka, Ivan Korostelev, John Guiver, Elena Pochernina, Pavel Mishkov, Alex Spengler, Denise J. Wilkins, Siân E. Lindley, Richard Banks, Sam Webster, Yordan Zaykov:
Enterprise Alexandria: Online High-Precision Enterprise Knowledge Base Construction with Typed Entities. AKBC 2021
2010 – 2019
- 2019
- [c14]John M. Winn, John Guiver, Sam Webster, Yordan Zaykov, Martin Kukla, Dany Fabian:
Alexandria: Unsupervised High-Precision Knowledge Base Construction using a Probabilistic Program. AKBC 2019 - 2016
- [j3]Matteo Venanzi, John Guiver, Pushmeet Kohli, Nicholas R. Jennings:
Time-Sensitive Bayesian Information Aggregation for Crowdsourcing Systems. J. Artif. Intell. Res. 56: 517-545 (2016) - 2015
- [c13]Edwin Simpson, Matteo Venanzi, Steven Reece, Pushmeet Kohli, John Guiver, Stephen J. Roberts, Nicholas R. Jennings:
Language Understanding in the Wild: Combining Crowdsourcing and Machine Learning. WWW 2015: 992-1002 - [i1]Matteo Venanzi, John Guiver, Pushmeet Kohli, Nick R. Jennings:
Time-Sensitive Bayesian Information Aggregation for Crowdsourcing Systems. CoRR abs/1510.06335 (2015) - 2014
- [c12]Bar Shalem, Yoram Bachrach, John Guiver, Christopher M. Bishop:
Students, Teachers, Exams and MOOCs: Predicting and Optimizing Attainment in Web-Based Education Using a Probabilistic Graphical Model. ECML/PKDD (3) 2014: 82-97 - [c11]Andrew D. Gordon, Thore Graepel, Nicolas Rolland, Claudio V. Russo, Johannes Borgström, John Guiver:
Tabular: a schema-driven probabilistic programming language. POPL 2014: 321-334 - [c10]Allison June-Barlow Chaney, Mike Gartrell, Jake M. Hofman, John Guiver, Noam Koenigstein, Pushmeet Kohli, Ulrich Paquet:
A large-scale exploration of group viewing patterns. TVX 2014: 31-38 - [c9]Matteo Venanzi, John Guiver, Gabriella Kazai, Pushmeet Kohli, Milad Shokouhi:
Community-based bayesian aggregation models for crowdsourcing. WWW 2014: 155-164 - 2012
- [c8]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 - [c7]Laura Dietz, Ben Gamari, John Guiver, Edward Lloyd Snelson, Ralf Herbrich:
De-Layering Social Networks by Shared Tastes of Friendships. ICWSM 2012 - 2010
- [c6]Elena Zheleva, John Guiver, Eduarda Mendes Rodrigues, Natasa Milic-Frayling:
Statistical models of music-listening sessions in social media. WWW 2010: 1019-1028
2000 – 2009
- 2009
- [j2]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 Explor. 11(2): 63-67 (2009) - [j1]John Guiver, Stefano Mizzaro, Stephen Robertson:
A few good topics: Experiments in topic set reduction for retrieval evaluation. ACM Trans. Inf. Syst. 27(4): 21:1-21:26 (2009) - [c5]John Guiver, Edward Lloyd Snelson:
Bayesian inference for Plackett-Luce ranking models. ICML 2009: 377-384 - 2008
- [c4]John Guiver, Edward Lloyd Snelson:
Learning to rank with SoftRank and Gaussian processes. SIGIR 2008: 259-266 - [c3]Michael J. Taylor, John Guiver, Stephen Robertson, Tom Minka:
SoftRank: optimizing non-smooth rank metrics. WSDM 2008: 77-86 - 2003
- [c2]Paul Turner, John Guiver, Brian Lines:
Introducing the state space bounded derivative network for commercial transition control. ACC 2003: 5400-5404 - [c1]Paul Turner, John Guiver:
The state space bounded derivative network superceding the application of neural networks in control. ECC 2003: 3413-3417
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