Michael Schaarschmidt
Michael Schaarschmidt
Research Scientist, DeepMind
Verified email at cam.ac.uk
Title
Cited by
Cited by
Year
BOAT: Building auto-tuners with structured Bayesian optimization
V Dalibard, M Schaarschmidt, E Yoneki
Proceedings of the 26th International Conference on World Wide Web, 479-488, 2017
732017
Tensorforce: A tensorflow library for applied reinforcement learning
M Schaarschmidt, A Kuhnle, K Fricke
Web page, 2017
402017
Tensorforce: a tensorflow library for applied reinforcement learning
A Kuhnle, M Schaarschmidt, K Fricke
Web page, 2017
362017
Towards automated polyglot persistence
M Schaarschmidt, F Gessert, N Ritter
Datenbanksysteme für Business, Technologie und Web (BTW 2015), 2015
292015
Lift: Reinforcement learning in computer systems by learning from demonstrations
M Schaarschmidt, A Kuhnle, B Ellis, K Fricke, F Gessert, E Yoneki
arXiv preprint arXiv:1808.07903, 2018
232018
Towards a Scalable and Unified REST API for Cloud Data Stores.
F Gessert, S Friedrich, W Wingerath, M Schaarschmidt, N Ritter
GI-Jahrestagung, 723-734, 2014
212014
Reinforcement learning for the adaptive scheduling of educational activities
J Bassen, B Balaji, M Schaarschmidt, C Thille, J Painter, D Zimmaro, ...
Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems …, 2020
192020
Quaestor: Query web caching for database-as-a-service providers
F Gessert, M Schaarschmidt, W Wingerath, E Witt, E Yoneki, N Ritter
Proceedings of the VLDB Endowment 10 (12), 1670-1681, 2017
192017
RLgraph: Modular Computation Graphs for Deep Reinforcement Learning
M Schaarschmidt, S Mika, K Fricke, E Yoneki
arXiv preprint arXiv:1810.09028, 2018
16*2018
The cache sketch: Revisiting expiration-based caching in the age of cloud data management
F Gessert, M Schaarschmidt, W Wingerath, S Friedrich, N Ritter
Datenbanksysteme für Business, Technologie und Web (BTW 2015), 2015
112015
Learning runtime parameters in computer systems with delayed experience injection
M Schaarschmidt, F Gessert, V Dalibard, E Yoneki
arXiv preprint arXiv:1610.09903, 2016
72016
Tensorforce: a tensorflow library for applied reinforcement learning (2017)
A Kuhnle, M Schaarschmidt, K Fricke
URL https://github. com/tensorforce/tensorforce, 2019
52019
Learning index selection with structured action spaces
J Welborn, M Schaarschmidt, E Yoneki
arXiv preprint arXiv:1909.07440, 2019
42019
Very Deep Graph Neural Networks Via Noise Regularisation
J Godwin, M Schaarschmidt, A Gaunt, A Sanchez-Gonzalez, Y Rubanova, ...
arXiv preprint arXiv:2106.07971, 2021
22021
Tuning the scheduling of distributed stochastic gradient descent with Bayesian optimization
V Dalibard, M Schaarschmidt, E Yoneki
arXiv preprint arXiv:1612.00383, 2016
22016
Wield: Systematic Reinforcement Learning With Progressive Randomization
M Schaarschmidt, K Fricke, E Yoneki
arXiv preprint arXiv:1909.06844, 2019
2019
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Articles 1–16