Mark D. Reid
Title
Cited by
Cited by
Year
Composite binary losses
MD Reid, RC Williamson
The Journal of Machine Learning Research 9999, 2387-2422, 2010
1612010
Information, divergence and risk for binary experiments
MD Reid, RC Williamson
Journal of Machine Learning Research 12, 731-817, 2011
1582011
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
522015
Surrogate regret bounds for proper losses
MD Reid, RC Williamson
Proceedings of the 26th Annual International Conference on Machine Learning …, 2009
482009
Composite Multiclass Losses
E Vernet, RC Williamson, MD Reid
Neural Information Processing Systems, 2011
442011
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
362009
Generalised pinsker inequalities
MD Reid, RC Williamson
The 22nd Annual Conference on Learning Theory (COLT 2009), 2009
362009
Interpreting prediction markets: a stochastic approach
R Frongillo, N Della Penna, M Reid
Advances in Neural Information Processing Systems 25, 3275-3283, 2012
282012
Learning to fly: An application of hierarchical reinforcement learning
M Ryan, M Reid
In Proceedings of the 17th International Conference on Machine Learning, 2000
252000
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
242012
Composite multiclass losses
RC Williamson, E Vernet, MD Reid
The Journal of Machine Learning Research 17 (1), 7860-7911, 2016
212016
Mixability is Bayes risk curvature relative to log loss
T Van Erven, MD Reid, RC Williamson
The Journal of Machine Learning Research 13 (1), 1639-1663, 2012
192012
Mixability in Statistical Learning
T van Erven, PD Grünwald, MD Reid, RC Williamson
Neural Information Processing Systems (NIPS), 2012
15*2012
Using ILP to improve planning in hierarchical reinforcement learning
M Reid, M Ryan
International Conference on Inductive Logic Programming, 174-190, 2000
152000
AOSO-LogitBoost: Adaptive One-Vs-One LogitBoost for Multi-Class Problems
P Sun, MD Reid, J Zhou
International Conference on Machine Learning, 2012
142012
Crowd & Prejudice: An Impossibility Theorem for Crowd Labelling without a Gold Standard
N Della Penna, MD Reid
Proceedings of Collective Intelligence, 2012
132012
Information, divergence and risk for binary experiments
MD Reid, RC Williamson
arXiv preprint arXiv:0901.0356, 2009
132009
Generalized mixability via entropic duality
MD Reid, RM Frongillo, RC Williamson, N Mehta
Conference on Learning Theory, 1501-1522, 2015
122015
Convergence analysis of prediction markets via randomized subspace descent
R Frongillo, MD Reid
Advances in Neural Information Processing Systems, 3034-3042, 2015
112015
A Hybrid Loss for Multiclass and Structured Prediction
Q Shi, M Reid, T Caetano, A Van Den Hengel, Z Wang
Transactions on Pattern Analysis and Machine Intelligence 37 (1), 2-12, 2014
82014
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Articles 1–20