Edwin V. Bonilla
Edwin V. Bonilla
Principal Research Scientist, CSIRO's Data61
Verified email at data61.csiro.au - Homepage
TitleCited byYear
Multi-task Gaussian process prediction
EV Bonilla, KM Chai, C Williams
Advances in neural information processing systems, 153-160, 2008
7062008
Using machine learning to focus iterative optimization
F Agakov, E Bonilla, J Cavazos, B Franke, G Fursin, MFP O'Boyle, ...
Proceedings of the international symposium on code generation and …, 2006
4152006
Rapidly selecting good compiler optimizations using performance counters
J Cavazos, G Fursin, F Agakov, E Bonilla, MFP O'Boyle, O Temam
International Symposium on Code Generation and Optimization (CGO'07), 185-197, 2007
2492007
Milepost gcc: Machine learning enabled self-tuning compiler
G Fursin, Y Kashnikov, AW Memon, Z Chamski, O Temam, M Namolaru, ...
International journal of parallel programming 39 (3), 296-327, 2011
1802011
Improving Topic Coherence with Regularized Topic Models
D Newman, EV Bonilla, W Buntine
1622011
Automatic feature generation for machine learning based optimizing compilation
H Leather, E Bonilla, M O'Boyle
Proceedings of the 7th annual IEEE/ACM International Symposium on Code …, 2009
1292009
MILEPOST GCC: machine learning based research compiler
G Fursin, C Miranda, O Temam, M Namolaru, E Yom-Tov, A Zaks, ...
1232008
Kernel multi-task learning using task-specific features
EV Bonilla, FV Agakov, CKI Williams
Artificial Intelligence and Statistics, 43-50, 2007
1032007
New objective functions for social collaborative filtering
J Noel, S Sanner, KN Tran, P Christen, L Xie, EV Bonilla, E Abbasnejad, ...
Proceedings of the 21st international conference on World Wide Web, 859-868, 2012
842012
Automatic performance model construction for the fast software exploration of new hardware designs
J Cavazos, C Dubach, F Agakov, E Bonilla, MFP O'Boyle, G Fursin, ...
Proceedings of the 2006 international conference on Compilers, architecture …, 2006
792006
A predictive model for dynamic microarchitectural adaptivity control
C Dubach, TM Jones, EV Bonilla, MFP O'Boyle
Proceedings of the 2010 43rd Annual IEEE/ACM International Symposium on …, 2010
762010
Gaussian process preference elicitation
EV Bonilla, S Guo, S Sanner
Advances in neural information processing systems, 262-270, 2010
75*2010
Portable compiler optimisation across embedded programs and microarchitectures using machine learning
C Dubach, TM Jones, EV Bonilla, G Fursin, MFP O'Boyle
Proceedings of the 42nd Annual IEEE/ACM International Symposium on …, 2009
652009
Random feature expansions for deep Gaussian processes
K Cutajar, EV Bonilla, P Michiardi, M Filippone
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
64*2017
Collaborative Multi-output Gaussian Processes.
TV Nguyen, EV Bonilla
UAI, 643-652, 2014
512014
Scalable inference for Gaussian process models with black-box likelihoods
A Dezfouli, EV Bonilla
Advances in Neural Information Processing Systems, 1414-1422, 2015
412015
Fast allocation of Gaussian process experts
T Nguyen, E Bonilla
International Conference on Machine Learning, 145-153, 2014
382014
Learning community-based preferences via dirichlet process mixtures of gaussian processes
E Abbasnejad, S Sanner, EV Bonilla, P Poupart
Twenty-Third International Joint Conference on Artificial Intelligence, 2013
332013
Automated variational inference for Gaussian process models
TV Nguyen, EV Bonilla
Advances in Neural Information Processing Systems, 1404-1412, 2014
252014
AutoGP: Exploring the capabilities and limitations of Gaussian process models
K Krauth, EV Bonilla, K Cutajar, M Filippone
arXiv preprint arXiv:1610.05392, 2016
222016
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