Mark D. Reid

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Robert C. WilliamsonUniversity of TübingenVerified email at uni-tuebingen.de
Rafael FrongilloComputer Science, CU BoulderVerified email at cs.berkeley.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
Peter GrünwaldGroup Leader Machine Learning, CWI; Professor of Statistics, Leiden UniversityVerified email at cwi.nl
Nishant A. MehtaAssistant Professor, University of VictoriaVerified email at uvic.ca
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, UoA | DeepSightX | Smarter RegionsVerified email at adelaide.edu.au
Darío García-GarcíaNetflixVerified email at netflix.com
James PettersonPrincipal Data Scientist, IAGVerified email at nicta.com.au
Kristian KerstingProfessor of AI & Machine Learning, TU Darmstadt, Co-Director of hessian.ai, Germany, CLAIRE & ELLISVerified email at cs.tu-darmstadt.de
Wray BuntineProfessor, VinUniversityVerified email at vinuni.edu.vn
Novi QuadriantoReader in Machine Learning, Predictive Analytics Lab (WeArePAL), University of SussexVerified 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 JoshiHarvard UniversityVerified email at seas.harvard.edu

Mark D. Reid

Apple

Verified email at reid.name - Homepage

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	190	2010
Information, divergence and risk for binary experiments MD Reid, RC Williamson Journal of Machine Learning Research 12, 731-817, 2011	183	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	75	2015
Surrogate regret bounds for proper losses MD Reid, RC Williamson Proceedings of the 26th Annual International Conference on Machine Learning …, 2009	54	2009
Composite Multiclass Losses E Vernet, RC Williamson, MD Reid Neural Information Processing Systems, 2011	53	2011
Generalised pinsker inequalities MD Reid, RC Williamson The 22nd Annual Conference on Learning Theory (COLT 2009), 2009	52	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	41	2012
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
Composite multiclass losses R Williamson, E Vernet, M Reid MIT Press, 2016	32	2016
Interpreting prediction markets: a stochastic approach R Frongillo, N Della Penna, M Reid Advances in Neural Information Processing Systems 25, 3275-3283, 2012	31	2012
Learning to fly: An application of hierarchical reinforcement learning M Ryan, M Reid In Proceedings of the 17th 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	21	2011
An Improved Multiclass LogitBoost Using Adaptive-One-vs-One P Sun, MD Reid, J Zhou Machine Learning Journal (To Appear), 2014	20	2014
Crowd & Prejudice: An Impossibility Theorem for Crowd Labelling without a Gold Standard N Della Penna, MD Reid Proceedings of Collective Intelligence, 2012	20	2012
Convergence analysis of prediction markets via randomized subspace descent R Frongillo, MD Reid Advances in Neural Information Processing Systems 28, 2015	19	2015
Generalized mixability via entropic duality MD Reid, RM Frongillo, RC Williamson, N Mehta Conference on Learning Theory, 1501-1522, 2015	17	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 International Conference on Inductive Logic Programming, 174-190, 2000	15	2000
Information, divergence and risk for binary experiments MD Reid, RC Williamson arXiv preprint arXiv:0901.0356, 2009	14	2009
AOSO-LogitBoost: Adaptive One-Vs-One LogitBoost for Multi-Class Problems P Sun, MD Reid, J Zhou International Conference on Machine Learning, 2012	13	2012

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