Binxin Ru
Cited by
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Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels
B Ru, X Wan, X Dong, M Osborne
ICLR 2021, 2020
BayesOpt Adversarial Attack
R Binxin, C Adam, B Arno, Y Gal
International Conference on Learning Representations, 2020
Bayesian optimisation over multiple continuous and categorical inputs
B Ru, A Alvi, V Nguyen, MA Osborne, S Roberts
International Conference on Machine Learning, 8276-8285, 2020
How powerful are performance predictors in neural architecture search?
C White, A Zela, R Ru, Y Liu, F Hutter
Advances in Neural Information Processing Systems 34, 28454-28469, 2021
Fast Information-theoretic Bayesian Optimisation
B Ru, M McLeod, D Granziol, MA Osborne
International Conference on Machine Learning (ICML) 2018, 2018
Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation
AS Alvi, B Ru, J Calliess, SJ Roberts, MA Osborne
International Conference on Machine Learning (ICML) 2019, 2019
Neural architecture generator optimization
R Ru, P Esperanca, FM Carlucci
Advances in Neural Information Processing Systems 33, 12057-12069, 2020
Speedy Performance Estimation for Neural Architecture Search
B Ru, C Lyle, L Schut, M van der Wilk, Y Gal
Advances in Neural Information Processing Systems, 2021, 2021
Think global and act local: Bayesian optimisation over high-dimensional categorical and mixed search spaces
X Wan, V Nguyen, H Ha, B Ru, C Lu, MA Osborne
arXiv preprint arXiv:2102.07188, 2021
A bayesian perspective on training speed and model selection
C Lyle, L Schut, R Ru, Y Gal, M van der Wilk
Advances in neural information processing systems 33, 10396-10408, 2020
MEMe: An accurate maximum entropy method for efficient approximations in large-scale machine learning
D Granziol, B Ru, S Zohren, X Dong, M Osborne, S Roberts
Entropy 21 (6), 551, 2019
On redundancy and diversity in cell-based neural architecture search
X Wan, B Ru, PM Esperanša, Z Li
arXiv preprint arXiv:2203.08887, 2022
Adversarial attacks on graph classifiers via bayesian optimisation
X Wan, H Kenlay, R Ru, A Blaas, MA Osborne, X Dong
Advances in Neural Information Processing Systems 34, 6983-6996, 2021
Learning to identify top elo ratings: A dueling bandits approach
X Yan, Y Du, B Ru, J Wang, H Zhang, X Chen
Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8797-8805, 2022
Approximate neural architecture search via operation distribution learning
X Wan, B Ru, PM Esparanša, FM Carlucci
Proceedings of the IEEE/CVF Winter Conference on Applications of Computerá…, 2022
VBALD-Variational Bayesian approximation of log determinants
D Granziol, E Wagstaff, BX Ru, M Osborne, S Roberts
arXiv preprint arXiv:1802.08054, 2018
DARTS without a validation set: Optimizing the marginal likelihood
M Fil, B Ru, C Lyle, Y Gal
arXiv preprint arXiv:2112.13023, 2021
Entropic spectral learning for large-scale graphs
D Granziol, B Ru, S Zohren, X Dong, M Osborne, S Roberts
arXiv preprint arXiv:1804.06802, 2018
Towards Discovering Neural Architectures from Scratch
S Schrodi, D Stoll, B Ru, R Sukthanker, T Brox, F Hutter
arXiv preprint arXiv:2211.01842, 2022
AUTOKD: Automatic Knowledge Distillation Into A Student Architecture Family
RH Eyono, FM Carlucci, PM Esperanša, B Ru, P Torr
arXiv preprint arXiv:2111.03555, 2021
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