| The variational Gaussian approximation revisited M Opper, C Archambeau Neural computation 21 (3), 786-792, 2009 | 445 | 2009 |
| Template attacks in principal subspaces C Archambeau, E Peeters, FX Standaert, JJ Quisquater Cryptographic Hardware and Embedded Systems-CHES 2006: 8th International …, 2006 | 409 | 2006 |
| Using subspace-based template attacks to compare and combine power and electromagnetic information leakages FX Standaert, C Archambeau International Workshop on Cryptographic Hardware and Embedded Systems, 411-425, 2008 | 278 | 2008 |
| System and method for supporting targeted sharing and early curation of information G Convertino, EH Chi, BV Hanrahan, NCY Kong, G Bouchard, ... US Patent 8,380,743, 2013 | 254 | 2013 |
| Leep: A new measure to evaluate transferability of learned representations C Nguyen, T Hassner, M Seeger, C Archambeau International Conference on Machine Learning, 7294-7305, 2020 | 234 | 2020 |
| Gaussian process approximations of stochastic differential equations C Archambeau, D Cornford, M Opper, J Shawe-Taylor Gaussian Processes in Practice, 1-16, 2007 | 195 | 2007 |
| Sparse probabilistic projections C Archambeau, F Bach Advances in neural information processing systems 21, 2008 | 188 | 2008 |
| Scalable hyperparameter transfer learning V Perrone, R Jenatton, MW Seeger, C Archambeau Advances in neural information processing systems 31, 2018 | 182 | 2018 |
| Adaptive algorithms for online convex optimization with long-term constraints R Jenatton, J Huang, C Archambeau International Conference on Machine Learning, 402-411, 2016 | 169 | 2016 |
| Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods S Lise, C Archambeau, M Pontil, DT Jones BMC bioinformatics 10, 1-17, 2009 | 137 | 2009 |
| A stochastic memoizer for sequence data F Wood, C Archambeau, J Gasthaus, L James, YW Teh Proceedings of the 26th annual international conference on machine learning …, 2009 | 136 | 2009 |
| Width optimization of the Gaussian kernels in Radial Basis Function Networks. N Benoudjit, C Archambeau, A Lendasse, JA Lee, M Verleysen ESANN 2, 425-432, 2002 | 133 | 2002 |
| Learning search spaces for bayesian optimization: Another view of hyperparameter transfer learning V Perrone, H Shen, MW Seeger, C Archambeau, R Jenatton Advances in neural information processing systems 32, 2019 | 126 | 2019 |
| Robust bayesian clustering C Archambeau, M Verleysen Neural Networks 20 (1), 129-138, 2007 | 123 | 2007 |
| Robust probabilistic projections C Archambeau, N Delannay, M Verleysen Proceedings of the 23rd International conference on machine learning, 33-40, 2006 | 123 | 2006 |
| Variational inference for diffusion processes C Archambeau, M Opper, Y Shen, D Cornford, J Shawe-Taylor Advances in neural information processing systems 20, 2007 | 118 | 2007 |
| Fair bayesian optimization V Perrone, M Donini, MB Zafar, R Schmucker, K Kenthapadi, ... Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 854-863, 2021 | 92 | 2021 |
| The sequence memoizer F Wood, J Gasthaus, C Archambeau, L James, YW Teh Communications of the ACM 54 (2), 91-98, 2011 | 91 | 2011 |
| Robust Bayesian matrix factorisation B Lakshminarayanan, G Bouchard, C Archambeau Proceedings of the Fourteenth International Conference on Artificial …, 2011 | 82 | 2011 |
| Mixtures of robust probabilistic principal component analyzers C Archambeau, N Delannay, M Verleysen Neurocomputing 71 (7-9), 1274-1282, 2008 | 77 | 2008 |
Matthias SeegerPrincipal Applied Scientist, Amazon, Berlin確認したメール アドレス: amazon.de
