Martin Wistuba
Martin Wistuba
IBM Research
Vahvistettu sähköpostiosoite verkkotunnuksessa ismll.de - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
Learning time-series shapelets
J Grabocka, N Schilling, M Wistuba, L Schmidt-Thieme
Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014
2822014
A survey on neural architecture search
M Wistuba, A Rawat, T Pedapati
arXiv preprint arXiv:1905.01392, 2019
852019
Adversarial Robustness Toolbox v1. 0.0
MI Nicolae, M Sinn, MN Tran, B Buesser, A Rawat, M Wistuba, ...
arXiv preprint arXiv:1807.01069, 2018
772018
Ultra-fast shapelets for time series classification
M Wistuba, J Grabocka, L Schmidt-Thieme
arXiv preprint arXiv:1503.05018, 2015
622015
Learning hyperparameter optimization initializations
M Wistuba, N Schilling, L Schmidt-Thieme
2015 IEEE international conference on data science and advanced analytics …, 2015
502015
Scalable gaussian process-based transfer surrogates for hyperparameter optimization
M Wistuba, N Schilling, L Schmidt-Thieme
Machine Learning 107 (1), 43-78, 2018
472018
Adversarial Robustness Toolbox v0. 2.2
MI Nicolae, M Sinn, TN Minh, A Rawat, M Wistuba, V Zantedeschi, ...
442018
Personalized deep learning for tag recommendation
HTH Nguyen, M Wistuba, J Grabocka, LR Drumond, L Schmidt-Thieme
Pacific-Asia Conference on Knowledge Discovery and Data Mining, 186-197, 2017
402017
Fast classification of univariate and multivariate time series through shapelet discovery
J Grabocka, M Wistuba, L Schmidt-Thieme
Knowledge and information systems 49 (2), 429-454, 2016
372016
Hyperparameter search space pruning–a new component for sequential model-based hyperparameter optimization
M Wistuba, N Schilling, L Schmidt-Thieme
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015
322015
Learning DTW-shapelets for time-series classification
M Shah, J Grabocka, N Schilling, M Wistuba, L Schmidt-Thieme
Proceedings of the 3rd IKDD Conference on Data Science, 2016, 1-8, 2016
302016
Hyperparameter optimization with factorized multilayer perceptrons
N Schilling, M Wistuba, L Drumond, L Schmidt-Thieme
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015
282015
Practical Deep Learning Architecture Optimization
M Wistuba
2018 IEEE 5th International Conference on Data Science and Advanced …, 2018
24*2018
Personalized tag recommendation for images using deep transfer learning
HTH Nguyen, M Wistuba, L Schmidt-Thieme
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017
242017
Deep learning architecture search by neuro-cell-based evolution with function-preserving mutations
M Wistuba
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2018
232018
Automatic Frankensteining: Creating complex ensembles autonomously
M Wistuba, N Schilling, L Schmidt-Thieme
Proceedings of the 2017 SIAM International Conference on Data Mining, 741-749, 2017
232017
Adversarial phenomenon in the eyes of Bayesian deep learning
A Rawat, M Wistuba, MI Nicolae
arXiv preprint arXiv:1711.08244, 2017
222017
Optimal exploitation of clustering and history information in multi-armed bandit
D Bouneffouf, S Parthasarathy, H Samulowitz, M Wistub
arXiv preprint arXiv:1906.03979, 2019
212019
Two-stage transfer surrogate model for automatic hyperparameter optimization
M Wistuba, N Schilling, L Schmidt-Thieme
Joint European conference on machine learning and knowledge discovery in …, 2016
192016
Scalable classification of repetitive time series through frequencies of local polynomials
J Grabocka, M Wistuba, L Schmidt-Thieme
IEEE Transactions on Knowledge and Data Engineering 27 (6), 1683-1695, 2014
192014
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