Edwin V. Bonilla
Edwin V. Bonilla
Principal Research Scientist, CSIRO's Data61
data61.csiro.au의 이메일 확인됨 - 홈페이지
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Multi-task Gaussian process prediction
C Williams, EV Bonilla, KM Chai
Advances in neural information processing systems, 153-160, 2007
9212007
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
4622006
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
2852007
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
2302011
Improving Topic Coherence with Regularized Topic Models
D Newman, EV Bonilla, W Buntine
Advances in Neural Information Processing Systems, 2011
1892011
Automatic feature generation for machine learning based optimizing compilation
H Leather, E Bonilla, M O'Boyle
2009 International Symposium on Code Generation and Optimization, 81-91, 2009
1552009
MILEPOST GCC: machine learning based research compiler
G Fursin, C Miranda, O Temam, M Namolaru, E Yom-Tov, A Zaks, ...
GCC Summit, 2008
1412008
Kernel multi-task learning using task-specific features
EV Bonilla, FV Agakov, CKI Williams
Artificial Intelligence and Statistics, 43-50, 2007
1292007
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
932010
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
932006
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
922012
Gaussian process preference elicitation
EV Bonilla, S Guo, S Sanner
Advances in neural information processing systems, 262-270, 2010
92*2010
Random feature expansions for deep Gaussian processes
K Cutajar, EV Bonilla, P Michiardi, M Filippone
International Conference on Machine Learning, 884-893, 2017
86*2017
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
732009
Collaborative Multi-output Gaussian Processes.
TV Nguyen, EV Bonilla
UAI, 643-652, 2014
632014
Scalable inference for Gaussian process models with black-box likelihoods
A Dezfouli, EV Bonilla
Advances in Neural Information Processing Systems 28, 1414-1422, 2015
512015
Fast allocation of Gaussian process experts
T Nguyen, E Bonilla
International Conference on Machine Learning, 145-153, 2014
512014
AutoGP: Exploring the capabilities and limitations of Gaussian process models
K Krauth, EV Bonilla, K Cutajar, M Filippone
Uncertainty in Artificial Intelligence, 2017
432017
Learning community-based preferences via dirichlet process mixtures of gaussian processes
E Abbasnejad, S Sanner, EV Bonilla, P Poupart
International joint conference on artificial intelligence, 2013
382013
Automated variational inference for Gaussian process models
TV Nguyen, EV Bonilla
Advances in Neural Information Processing Systems 27, 1404-1412, 2014
352014
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