Conditional mean embeddings as regressors S Grunewalder, G Lever, L Baldassarre, S Patterson, A Gretton, M Pontil Proceedings of the 29th International Conference on Machine Learning (ICML …, 2012 | 176* | 2012 |
Modelling transition dynamics in MDPs with RKHS embeddings S Grünewälder, G Lever, L Baldassarre, A Gretton, M Pontil Proceedings of the 29th International Conference on Machine Learning (ICML …, 2012 | 142 | 2012 |
Bandits with delayed, aggregated anonymous feedback C Pike-Burke, S Agrawal, C Szepesvari, S Grunewalder International Conference on Machine Learning, 4105-4113, 2018 | 133 | 2018 |
Regret bounds for Gaussian process bandit problems S Grünewälder, JY Audibert, M Opper, J Shawe–Taylor Proceedings of the thirteenth international conference on artificial …, 2010 | 112 | 2010 |
Movement activity based classification of animal behaviour with an application to data from cheetah (Acinonyx jubatus) S Grünewälder, F Broekhuis, DW Macdonald, AM Wilson, JW McNutt, ... PloS one 7 (11), e49120, 2012 | 94 | 2012 |
Analyzing short-term noise dependencies of spike-counts in macaque prefrontal cortex using copulas and the flashlight transformation A Onken, S Grünewälder, MHJ Munk, K Obermayer PLoS computational biology 5 (11), e1000577, 2009 | 67 | 2009 |
Optimal hunting conditions drive circalunar behavior of a diurnal carnivore F Broekhuis, S Grünewälder, JW McNutt, DW Macdonald Behavioral Ecology 25 (5), 1268-1275, 2014 | 65 | 2014 |
Recovering bandits C Pike-Burke, S Grunewalder Advances in Neural Information Processing Systems 32, 2019 | 48 | 2019 |
Construction of Approximation Spaces for Reinforcement Learning. W Böhmer, S Grünewälder, Y Shen, M Musial, K Obermayer Journal of Machine Learning Research 14 (7), 2013 | 30 | 2013 |
Regularized sparse kernel slow feature analysis W Böhmer, S Grünewälder, H Nickisch, K Obermayer Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011 | 23 | 2011 |
Generating feature spaces for linear algorithms with regularized sparse kernel slow feature analysis W Böhmer, S Grünewälder, H Nickisch, K Obermayer Machine Learning 89, 67-86, 2012 | 22 | 2012 |
Smooth operators S Grunewalder, G Arthur, J Shawe-Taylor International Conference on Machine Learning, 1184-1192, 2013 | 21 | 2013 |
Modeling short-term noise dependence of spike counts in macaque prefrontal cortex A Onken, S Grünewälder, M Munk, K Obermayer Advances in neural information processing systems 21, 2008 | 13 | 2008 |
Ivanov-regularised least-squares estimators over large RKHSs and their interpolation spaces S Page, S Grünewälder Journal of Machine Learning Research 20 (120), 1-49, 2019 | 11 | 2019 |
Approximations of the restless bandit problem S Grünewälder, A Khaleghi Journal of Machine Learning Research 20 (14), 1-37, 2019 | 11 | 2019 |
Plug-in estimators for conditional expectations and probabilities S Grunewalder International Conference on Artificial Intelligence and Statistics, 1513-1521, 2018 | 8 | 2018 |
The optimal unbiased value estimator and its relation to LSTD, TD and MC S Grünewälder, K Obermayer Machine learning 83, 289-330, 2011 | 8 | 2011 |
Optimistic planning for the stochastic knapsack problem C Pike-Burke, S Grunewalder Artificial Intelligence and Statistics, 1114-1122, 2017 | 7 | 2017 |
The Goldenshluger–Lepski method for constrained least-squares estimators over RKHSs S Page, S Grünewälder Bernoulli 27 (4), 2241-2266, 2021 | 5 | 2021 |
Compact convex projections S Grünewälder Journal of Machine Learning Research 18 (219), 1-43, 2018 | 5 | 2018 |