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Edwin V. Bonilla
Edwin V. Bonilla
Principal Research Scientist, CSIRO's Data61
Verified email at data61.csiro.au - Homepage
Title
Cited by
Cited by
Year
Multi-task Gaussian process prediction
EV Bonilla, C Williams, KM Chai
Advances in Neural Information Processing Systems (NeurIPS), 153-160, 2007
13982007
Using machine learning to focus iterative optimization
F Agakov, E Bonilla, J Cavazos, B Franke, G Fursin, MFP O'Boyle, ...
International Symposium on Code Generation and Optimization, 11 pp.-305, 2006
5202006
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, 185-197, 2007
3442007
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, 296-327, 2011
3212011
Improving Topic Coherence with Regularized Topic Models
D Newman, EV Bonilla, W Buntine
Advances in Neural Information Processing Systems (NeurIPS), 2011
2532011
Automatic feature generation for machine learning--based optimising compilation
H Leather, E Bonilla, M O'boyle
ACM Transactions on Architecture and Code Optimization 11 (1), 1-32, 2014
2152014
Random feature expansions for deep Gaussian processes
K Cutajar, EV Bonilla, P Michiardi, M Filippone
International Conference on Machine Learning (ICML), 884-893, 2017
1742017
MILEPOST GCC: machine learning based research compiler
G Fursin, C Miranda, O Temam, M Namolaru, E Yom-Tov, A Zaks, ...
GCC Summit, 2008
1692008
Kernel multi-task learning using task-specific features
EV Bonilla, FV Agakov, CKI Williams
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2007
1442007
Collaborative Multi-output Gaussian Processes.
TV Nguyen, EV Bonilla
Uncertainty in Artificial Intelligence (UAI), 643-652, 2014
1192014
A predictive model for dynamic microarchitectural adaptivity control
C Dubach, TM Jones, EV Bonilla, MFP O'Boyle
2010 43rd Annual IEEE/ACM International Symposium on Microarchitecture, 485-496, 2010
1152010
Gaussian process preference elicitation
EV Bonilla, S Guo, S Sanner
Advances in Neural Information Processing Systems (NeurIPS), 262-270, 2010
108*2010
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, ...
International conference on Compilers, architecture and synthesis for …, 2006
982006
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
962012
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
812009
Fast allocation of Gaussian process experts
T Nguyen, E Bonilla
International Conference on Machine Learning (ICML), 145-153, 2014
722014
Scalable inference for Gaussian process models with black-box likelihoods
A Dezfouli, EV Bonilla
Advances in Neural Information Processing Systems (NeurIPS) 28, 2015
672015
AutoGP: Exploring the capabilities and limitations of Gaussian process models
K Krauth, EV Bonilla, K Cutajar, M Filippone
Uncertainty in Artificial Intelligence (UAI), 2017
662017
Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings
P Elinas, EV Bonilla, L Tiao
Advances in Neural Information Processing Systems (NeurIPS), 2020
652020
Automated variational inference for Gaussian process models
TV Nguyen, EV Bonilla
Advances in Neural Information Processing Systems (NeurIPS) 27, 2014
452014
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