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2020 – today
- 2024
[i12]Sami Alabed, Bart Chrzaszcz, Juliana Franco, Dominik Grewe, Dougal Maclaurin, James Molloy, Tom Natan, Tamara Norman, Xiaoyue Pan, Adam Paszke, Norman A. Rink, Michael Schaarschmidt, Timur Sitdikov, Agnieszka Swietlik, Dimitrios Vytiniotis, Joel Wee:
PartIR: Composing SPMD Partitioning Strategies for Machine Learning. CoRR abs/2401.11202 (2024)- 2023
- [c9]Sheheryar Zaidi, Michael Schaarschmidt, James Martens, Hyunjik Kim, Yee Whye Teh, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Razvan Pascanu, Jonathan Godwin:
Pre-training via Denoising for Molecular Property Prediction. ICLR 2023 - 2022
- [c8]Jonathan Godwin, Michael Schaarschmidt, Alexander L. Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Velickovic, James Kirkpatrick, Peter W. Battaglia:
Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond. ICLR 2022 - [i11]Sheheryar Zaidi, Michael Schaarschmidt, James Martens, Hyunjik Kim, Yee Whye Teh, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Razvan Pascanu, Jonathan Godwin:
Pre-training via Denoising for Molecular Property Prediction. CoRR abs/2206.00133 (2022) - [i10]Michael Schaarschmidt, Morgane Riviere, Alex M. Ganose, James S. Spencer, Alexander L. Gaunt, James Kirkpatrick, Simon Axelrod, Peter W. Battaglia, Jonathan Godwin:
Learned Force Fields Are Ready For Ground State Catalyst Discovery. CoRR abs/2209.12466 (2022) - [i9]Sami Alabed, Dominik Grewe, Juliana Franco, Bart Chrzaszcz, Tom Natan, Tamara Norman, Norman A. Rink, Dimitrios Vytiniotis, Michael Schaarschmidt:
Automatic Discovery of Composite SPMD Partitioning Strategies in PartIR. CoRR abs/2210.06352 (2022) - 2021
- [i8]Jonathan Godwin, Michael Schaarschmidt, Alexander L. Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Velickovic, James Kirkpatrick, Peter W. Battaglia:
Very Deep Graph Neural Networks Via Noise Regularisation. CoRR abs/2106.07971 (2021) - [i7]Michael Schaarschmidt, Dominik Grewe, Dimitrios Vytiniotis, Adam Paszke, Georg Stefan Schmid, Tamara Norman, James Molloy, Jonathan Godwin, Norman Alexander Rink, Vinod Nair, Dan Belov:
Automap: Towards Ergonomic Automated Parallelism for ML Models. CoRR abs/2112.02958 (2021) - 2020
- [b1]Michael Schaarschmidt:
End-to-end deep reinforcement learning in computer systems. University of Cambridge, UK, 2020 - [c7]Jonathan Bassen, Bharathan Balaji, Michael Schaarschmidt, Candace Thille, Jay Painter, Dawn Zimmaro, Alex Games, Ethan Fast, John C. Mitchell
:
Reinforcement Learning for the Adaptive Scheduling of Educational Activities. CHI 2020: 1-12
2010 – 2019
- 2019
- [c6]Michael Schaarschmidt, Sven Mika, Kai Fricke, Eiko Yoneki:
RLgraph: Modular Computation Graphs for Deep Reinforcement Learning. SysML 2019 - [i6]Michael Schaarschmidt, Kai Fricke, Eiko Yoneki:
Wield: Systematic Reinforcement Learning With Progressive Randomization. CoRR abs/1909.06844 (2019) - [i5]Jeremy Welborn, Michael Schaarschmidt, Eiko Yoneki:
Learning Index Selection with Structured Action Spaces. CoRR abs/1909.07440 (2019) - 2018
- [i4]Michael Schaarschmidt, Alexander Kuhnle, Ben Ellis, Kai Fricke, Felix Gessert, Eiko Yoneki:
LIFT: Reinforcement Learning in Computer Systems by Learning From Demonstrations. CoRR abs/1808.07903 (2018) - [i3]Michael Schaarschmidt, Sven Mika, Kai Fricke, Eiko Yoneki:
RLgraph: Flexible Computation Graphs for Deep Reinforcement Learning. CoRR abs/1810.09028 (2018) - 2017
- [j1]Felix Gessert, Michael Schaarschmidt, Wolfram Wingerath, Erik Witt, Eiko Yoneki, Norbert Ritter:
Quaestor: Query Web Caching for Database-as-a-Service Providers. Proc. VLDB Endow. 10(12): 1670-1681 (2017) - [c5]Valentin Dalibard, Michael Schaarschmidt, Eiko Yoneki:
BOAT: Building Auto-Tuners with Structured Bayesian Optimization. WWW 2017: 479-488 - 2016
- [i2]Michael Schaarschmidt, Felix Gessert, Valentin Dalibard, Eiko Yoneki:
Learning Runtime Parameters in Computer Systems with Delayed Experience Injection. CoRR abs/1610.09903 (2016) - [i1]Valentin Dalibard, Michael Schaarschmidt, Eiko Yoneki:
Tuning the Scheduling of Distributed Stochastic Gradient Descent with Bayesian Optimization. CoRR abs/1612.00383 (2016) - 2015
- [c4]Felix Gessert, Michael Schaarschmidt, Wolfram Wingerath, Steffen Friedrich, Norbert Ritter:
The Cache Sketch: Revisiting Expiration-based Caching in the Age of Cloud Data Management. BTW 2015: 53-72 - [c3]Michael Schaarschmidt, Felix Gessert, Norbert Ritter:
Towards Automated Polyglot Persistence. BTW 2015: 73-82 - 2014
- [c2]Felix Gessert, Steffen Friedrich, Wolfram Wingerath, Michael Schaarschmidt, Norbert Ritter:
Towards a Scalable and Unified REST API for Cloud Data Stores. GI-Jahrestagung 2014: 723-734
2000 – 2009
- 2006
- [c1]Wolf Zimmermann, Michael Schaarschmidt:
Automatic Checking of Component Protocols in Component-Based Systems. SC@ETAPS 2006: 1-17
Coauthor Index
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