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ORCIDGabriel Krummenacher
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2010 – 2019
- 2019
[j3]Ðorðe Miladinovic, Christine Muheim
, Stefan Bauer, Andrea Spinnler, Daniela Noain, Mojtaba Bandarabadi, Benjamin Gallusser, Gabriel Krummenacher, Christian R. Baumann, Antoine Adamantidis, Steven A. Brown, Joachim M. Buhmann:
SPINDLE: End-to-end learning from EEG/EMG to extrapolate animal sleep scoring across experimental settings, labs and species. PLoS Comput. Biol. 15(4) (2019)- 2018
- [j2]Gabriel Krummenacher, Cheng Soon Ong, Stefan Koller, Seijin Kobayashi, Joachim M. Buhmann:
Wheel Defect Detection With Machine Learning. IEEE Trans. Intell. Transp. Syst. 19(4): 1176-1187 (2018) - 2016
- [b1]Gabriel Krummenacher:
Scalable and Robust Supervised Learning Through Random Approximations. ETH Zurich, Zürich, Switzerland, 2016 - [c3]Gabriel Krummenacher, Brian McWilliams, Yannic Kilcher, Joachim M. Buhmann, Nicolai Meinshausen:
Scalable Adaptive Stochastic Optimization Using Random Projections. NIPS 2016: 1750-1758 - [i1]Gabriel Krummenacher, Brian McWilliams, Yannic Kilcher, Joachim M. Buhmann, Nicolai Meinshausen:
Scalable Adaptive Stochastic Optimization Using Random Projections. CoRR abs/1611.06652 (2016) - 2014
- [c2]Brian McWilliams, Gabriel Krummenacher, Mario Lucic, Joachim M. Buhmann:
Fast and Robust Least Squares Estimation in Corrupted Linear Models. NIPS 2014: 415-423 - 2013
- [j1]Alberto Giovanni Busetto, Alain Hauser, Gabriel Krummenacher, Mikael Sunnåker, Sotiris Dimopoulos, Cheng Soon Ong, Jörg Stelling, Joachim M. Buhmann:
Near-optimal experimental design for model selection in systems biology. Bioinform. 29(20): 2625-2632 (2013) - [c1]Gabriel Krummenacher, Cheng Soon Ong, Joachim M. Buhmann:
Ellipsoidal Multiple Instance Learning. ICML (2) 2013: 73-81
Coauthor Index
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