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James Robert Lloyd
James Robert Lloyd
PhD from Machine Learning Group, Cambridge University
Verified email at cam.ac.uk - Homepage
Title
Cited by
Cited by
Year
Structure Discovery in Nonparametric Regression through Compositional Kernel Search
D Duvenaud, JR Lloyd, R Grosse, JB Tenenbaum, Z Ghahramani
International Conference on Machine Learning, 2013
6102013
Automatic Construction and Natural-Language Description of Nonparametric Regression Models
JR Lloyd, D Duvenaud, R Grosse, JB Tenenbaum, Z Ghahramani
Association for the Advancement of Artificial Intelligence (AAAI), 2014
2782014
Random function priors for exchangeable arrays with applications to graphs and relational data
JR Lloyd, P Orbanz, Z Ghahramani, DM Roy
Advance in Neural Information Processing Systems, 2013
1412013
GEFCom2012 hierarchical load forecasting: Gradient boosting machines and Gaussian processes
JR Lloyd
International Journal of Forecasting 30 (2), 369-374, 2014
1372014
Statistical model criticism using kernel two sample tests
JR Lloyd, Z Ghahramani
Advances in neural information processing systems 28, 2015
932015
A brief review of the ChaLearn AutoML challenge: any-time any-dataset learning without human intervention
I Guyon, I Chaabane, HJ Escalante, S Escalera, D Jajetic, JR Lloyd, ...
Workshop on Automatic Machine Learning, 21-30, 2016
912016
The automatic statistician
C Steinruecken, E Smith, D Janz, J Lloyd, Z Ghahramani
Automated machine learning: Methods, systems, challenges, 161-173, 2019
852019
Unsupervised many-to-many object matching for relational data
T Iwata, JR Lloyd, Z Ghahramani
IEEE transactions on pattern analysis and machine intelligence 38 (3), 607-617, 2015
242015
Gaussian process conditional copulas with applications to financial time series
JM Hernández-Lobato, JR Lloyd, D Hernández-Lobato
Advances in Neural Information Processing Systems 26, 2013
192013
Bisakha Ray, Lukasz Romaszko, Michčle Sebag, Alexander Statnikov, Sébastien Treguer, and Evelyne Viegas. 2016. A brief review of the ChaLearn AutoML challenge: any-time any …
I Guyon, I Chaabane, HJ Escalante, S Escalera, D Jajetic, JR Lloyd, ...
Proceedings of the Workshop on Automatic Machine Learning (Proceedings of …, 2015
162015
Structure discovery in nonparametric regression through compositional kernel search (2013)
D Duvenaud, JR Lloyd, R Grosse, JB Tenenbaum, Z Ghahramani
arXiv preprint arXiv:1302.4922, 0
12
Bisakha Ray, Lukasz Romaszko, Michele Sebag, et al. A brief review of the chalearn automl challenge: any-time any-dataset learning without human intervention
I Guyon, I Chaabane, HJ Escalante, S Escalera, D Jajetic, JR Lloyd, ...
Workshop on Automatic Machine Learning, 21-30, 2016
92016
Learning the semantics of discrete random variables: Ordinal or categorical
JM Hernández-Lobato, JR Lloyd, D Hernández-Lobato, Z Ghahramani
NIPS Workshop on Learning Semantics, 2014
32014
Representation, learning, description and criticism of probabilistic models with applications to networks, functions and relational data
JR Lloyd
University of Cambridge, 2015
22015
Exchangeable databases and their functional representation
JR Lloyd, P Orbanz, Z Ghahramani, DM Roy
22013
Automatic Construction and Natural-language Description of Additive Nonparametric Models
JR Lloyd, D Duvenaud, R Grosse, JB Tenenbaum, Z Ghahramani
2013
Publisher's acknowledgement
DR Allred, D Jasmer, JJ Arends, M Jenkins, DJ Argyle, TJ Kennedy, ...
Veterinary Parasitology 69, 159, 1997
1997
Introduction to probabilistic programming
D Duvenaud, J Lloyd, DM Roy
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