Mark D. Reid

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Robert C. WilliamsonUniversity of TübingenVerified email at uni-tuebingen.de
Rafael FrongilloComputer Science, CU BoulderVerified email at colorado.edu
Tim van ErvenAssociate professor at the University of Amsterdam, the NetherlandsVerified email at uva.nl
Nicolás Della PennaNullius in verbaVerified email at mit.edu
Tiberio CaetanoGradient InstituteVerified email at gradientinstitute.org
Nishant A. MehtaAssistant Professor, University of VictoriaVerified email at uvic.ca
Peter GrünwaldGroup Leader Machine Learning, CWI; Professor of Statistics, Leiden UniversityVerified email at cwi.nl
Malcolm RyanSchool of Computing, Macquarie UniversityVerified email at mq.edu.au
Jie ZhouProfessor, Department of Automation, Tsinghua UniversityVerified email at tsinghua.edu.cn
Professor Javen Qinfeng ShiDirector for Probabilistic Graphical Model Group, University of AdelaideVerified email at adelaide.edu.au
Darío García-GarcíaFeverVerified email at feverup.com
James PettersonPrincipal Data Scientist, IAGVerified email at nicta.com.au
Kristian KerstingProfessor of AI & ML, TU Darmstadt, Co-Director hessian.ai, DFKI, Germany, CLAIRE & ELLISVerified email at cs.tu-darmstadt.de
Wray BuntineProfessor, VinUniversityVerified email at vinuni.edu.vn
Novi QuadriantoProfessor of Machine Learning, University of Sussex UK, BCAM Spain, Monash IndonesiaVerified email at sussex.ac.uk
Anne Mindika PremachandraLecturer, University of Colombo School of ComputingVerified email at ucsc.cmb.ac.lk
James MontgomeryUniversity of TasmaniaVerified email at utas.edu.au
Anton van den HengelDirector of Applied Science at Amazon and Director of the Centre for Augmented Reasoning at AIML.Verified email at adelaide.edu.au
David BalduzziXTX MarketsVerified email at google.com
Shalmali JoshiColumbia UniversityVerified email at cumc.columbia.edu

Mark D. Reid

Apple

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Machine Learning Online Learning Prediction Markets Information Theory


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Composite binary losses MD Reid, RC Williamson The Journal of Machine Learning Research 9999, 2387-2422, 2010	206	2010
Information, divergence and risk for binary experiments MD Reid, RC Williamson Journal of Machine Learning Research 12, 731-817, 2011	195	2011
Fast rates in statistical and online learning T van Erven, PD Grünwald, NA Mehta, MD Reid, RC Williamson Journal of Machine Learning Research 16 (Sep), 1793−1861, 2015	91	2015
Composite Multiclass Losses E Vernet, RC Williamson, MD Reid Neural Information Processing Systems, 2011	57	2011
Surrogate regret bounds for proper losses MD Reid, RC Williamson Proceedings of the 26th Annual International Conference on Machine Learning …, 2009	56	2009
Generalised pinsker inequalities MD Reid, RC Williamson The 22nd Annual Conference on Learning Theory (COLT 2009), 2009	56	2009
Tighter Variational Representations of f-Divergences via Restriction to Probability Measures A Ruderman, MD Reid, D García-García, J Petterson International Conference on Machine Learning, 2012	45	2012
Composite multiclass losses R Williamson, E Vernet, M Reid MIT Press, 2016	43	2016
Kernel conditional quantile estimation via reduction revisited N Quadrianto, K Kersting, MD Reid, TS Caetano, WL Buntine 2009 Ninth IEEE International Conference on Data Mining, 938-943, 2009	39	2009
Interpreting prediction markets: a stochastic approach R Frongillo, N Della Penna, M Reid Advances in Neural Information Processing Systems 25, 3275-3283, 2012	33	2012
Learning to fly: An application of hierarchical reinforcement learning MRK Ryan, M Reid Proceedings of the Seventeenth International Conference on Machine Learning …, 2000	28	2000
Mixability is Bayes risk curvature relative to log loss T Erven, MD Reid, RC Williamson Proceedings of the 24th Annual Conference on Learning Theory, 233-252, 2011	25	2011
Crowd & Prejudice: An Impossibility Theorem for Crowd Labelling without a Gold Standard N Della Penna, MD Reid Proceedings of Collective Intelligence, 2012	21	2012
Convergence analysis of prediction markets via randomized subspace descent R Frongillo, MD Reid Advances in Neural Information Processing Systems 28, 2015	20	2015
An Improved Multiclass LogitBoost Using Adaptive-One-vs-One P Sun, MD Reid, J Zhou Machine Learning Journal (To Appear), 2014	20	2014
Generalized mixability via entropic duality MD Reid, RM Frongillo, RC Williamson, N Mehta Conference on Learning Theory, 1501-1522, 2015	19	2015
Mixability in Statistical Learning T van Erven, PD Grünwald, MD Reid, RC Williamson Neural Information Processing Systems (NIPS), 2012	17*	2012
Using ILP to improve planning in hierarchical reinforcement learning M Reid, M Ryan Inductive Logic Programming: 10th International Conference, ILP 2000 London …, 2000	16	2000
AOSO-LogitBoost: Adaptive One-Vs-One LogitBoost for Multi-Class Problems P Sun, MD Reid, J Zhou International Conference on Machine Learning, 2012	14	2012
Gaussian Distribution. X Zhang Encyclopedia of Machine Learning, 425-428, 2010	14*	2010

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