Mark D. Reid

According to our database, Mark D. Reid authored at least 35 papers between 1999 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

PSI Draft Specification.

Mark D. Reid, James Montgomery, Barry J. Drake, Avraham Ruderman

CoRR, 2022

2016

Composite Multiclass Losses.

Robert C. Williamson, Elodie Vernet, Mark D. Reid

J. Mach. Learn. Res., 2016

Compliance-Aware Bandits.

Nicolás Della Penna, Mark D. Reid, David Balduzzi

CoRR, 2016

Causal Bandits: Learning Good Interventions via Causal Inference.

Finnian Lattimore, Tor Lattimore, Mark D. Reid

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

A Hybrid Loss for Multiclass and Structured Prediction.

Qinfeng Shi, Mark D. Reid, Tibério S. Caetano, Anton van den Hengel, Zhenhua Wang

IEEE Trans. Pattern Anal. Mach. Intell., 2015

Fast rates in statistical and online learning.

Tim van Erven, Peter D. Grünwald, Nishant A. Mehta, Mark D. Reid, Robert C. Williamson

J. Mach. Learn. Res., 2015

Protocols and Structures for Inference: A RESTful API for Machine Learning.

James Montgomery, Mark D. Reid, Barry J. Drake

Proceedings of the 2nd International Conference on Predictive APIs and Apps, 2015

Convergence Analysis of Prediction Markets via Randomized Subspace Descent.

Rafael M. Frongillo, Mark D. Reid

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Generalized Mixability via Entropic Duality.

Mark D. Reid, Rafael M. Frongillo, Robert C. Williamson, Nishant A. Mehta

Proceedings of The 28th Conference on Learning Theory, 2015

2014

An improved multiclass LogitBoost using adaptive-one-vs-one.

Peng Sun, Mark D. Reid, Jie Zhou

Mach. Learn., 2014

Generalised Mixability, Constant Regret, and Bayesian Updating.

Mark D. Reid, Rafael M. Frongillo, Robert C. Williamson

CoRR, 2014

Risk Dynamics in Trade Networks.

Rafael M. Frongillo, Mark D. Reid

CoRR, 2014

2013

Aggregating Predictions via Sequential Mini-Trading.

Mindika Premachandra, Mark D. Reid

Proceedings of the Asian Conference on Machine Learning, 2013

2012

Crowd & Prejudice: An Impossibility Theorem for Crowd Labelling without a Gold Standard

Nicolás Della Penna, Mark D. Reid

CoRR, 2012

Interpreting prediction markets: a stochastic approach.

Nicolás Della Penna, Mark D. Reid, Rafael M. Frongillo

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Mixability in Statistical Learning.

Tim van Erven, Peter D. Grünwald, Mark D. Reid, Robert C. Williamson

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

AOSO-LogitBoost: Adaptive One-Vs-One LogitBoost for Multi-Class Problem.

Peng Sun, Mark D. Reid, Jie Zhou

Proceedings of the 29th International Conference on Machine Learning, 2012

Tighter Variational Representations of f-Divergences via Restriction to Probability Measures.

Avraham Ruderman, Mark D. Reid, Dario García-García, James Petterson

Proceedings of the 29th International Conference on Machine Learning, 2012

The Convexity and Design of Composite Multiclass Losses.

Mark D. Reid, Robert C. Williamson, Peng Sun

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Information, Divergence and Risk for Binary Experiments.

Mark D. Reid, Robert C. Williamson

J. Mach. Learn. Res., 2011

Mixability is Bayes Risk Curvature Relative to Log Loss.

Tim van Erven, Mark D. Reid, Robert C. Williamson

Proceedings of the COLT 2011, 2011

Bandit Market Makers

Nicolás Della Penna, Mark D. Reid

CoRR, 2011

2010

Generalization Bounds.

Mark D. Reid

Proceedings of the Encyclopedia of Machine Learning, 2010

Convexity of Proper Composite Binary Losses.

Mark D. Reid, Robert C. Williamson

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Composite Binary Losses.

Mark D. Reid, Robert C. Williamson

J. Mach. Learn. Res., 2010

Conditional Random Fields and Support Vector Machines: A Hybrid Approach

Qinfeng Shi, Mark D. Reid, Tibério S. Caetano

CoRR, 2010

2009

Surrogate regret bounds for proper losses.

Mark D. Reid, Robert C. Williamson

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Kernel Conditional Quantile Estimation via Reduction Revisited.

Novi Quadrianto, Kristian Kersting, Mark D. Reid, Tibério S. Caetano, Wray L. Buntine

Proceedings of the ICDM 2009, 2009

Generalised Pinsker Inequalities.

Mark D. Reid, Robert C. Williamson

Proceedings of the COLT 2009, 2009

2007

DEFT guessing: using inductive transfer to improve rule evaluation from limited data.

Mark D. Reid

PhD thesis, 2007

2004

Improving Rule Evaluation Using Multitask Learning.

Mark D. Reid

Proceedings of the Inductive Logic Programming, 14th International Conference, 2004

2002

Cross training and its application to skill mining.

Daniel Oblinger, Mark D. Reid, Mark Brodie, Rodrigo de Salvo Braz

IBM Syst. J., 2002

2000

Using ILP to Improve Planning in Hierarchical Reinforcement Learning.

Mark D. Reid, Malcolm Ryan

Proceedings of the Inductive Logic Programming, 10th International Conference, 2000

Learning to Fly: An Application of Hierarchical Reinforcement Learning.

Malcolm Ryan, Mark D. Reid

Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

1999

A Noise Resistant Model Inference System.

Eric McCreath, Mark D. Reid

Proceedings of the Discovery Science, 1999