Michael Schaarschmidt

24 papers A* 4A 1Misc 2Journal 13Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	PartIR: Composing SPMD Partitioning Strategies for Machine Learning. ASPLOS (1) Sami Alabed, Daniel Belov, 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
2024	J	`jnl`	PartIR: Composing SPMD Partitioning Strategies for Machine Learning. CoRR 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
2023	A*	`conf`	Pre-training via Denoising for Molecular Property Prediction. ICLR Sheheryar Zaidi, Michael Schaarschmidt, James Martens, Hyunjik Kim, Yee Whye Teh, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Razvan Pascanu, Jonathan Godwin
2022	J	`jnl`	Automatic Discovery of Composite SPMD Partitioning Strategies in PartIR. CoRR Sami Alabed, Dominik Grewe, Juliana Franco, Bart Chrzaszcz, Tom Natan, Tamara Norman, Norman A. Rink, Dimitrios Vytiniotis, Michael Schaarschmidt
2022	J	`jnl`	Learned Force Fields Are Ready For Ground State Catalyst Discovery. CoRR Michael Schaarschmidt, Morgane Riviere, Alex M. Ganose, James S. Spencer, Alexander L. Gaunt, James Kirkpatrick, Simon Axelrod, Peter W. Battaglia, Jonathan Godwin
2022	J	`jnl`	Pre-training via Denoising for Molecular Property Prediction. CoRR Sheheryar Zaidi, Michael Schaarschmidt, James Martens, Hyunjik Kim, Yee Whye Teh, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Razvan Pascanu, Jonathan Godwin
2022	A*	`conf`	Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond. ICLR Jonathan Godwin, Michael Schaarschmidt, Alexander L. Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Velickovic, James Kirkpatrick, Peter W. Battaglia
2021	J	`jnl`	Automap: Towards Ergonomic Automated Parallelism for ML Models. CoRR Michael Schaarschmidt, Dominik Grewe, Dimitrios Vytiniotis, Adam Paszke, Georg Stefan Schmid, Tamara Norman, James Molloy, Jonathan Godwin, Norman Alexander Rink, Vinod Nair, Dan Belov
2021	J	`jnl`	Very Deep Graph Neural Networks Via Noise Regularisation. CoRR Jonathan Godwin, Michael Schaarschmidt, Alexander L. Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Velickovic, James Kirkpatrick, Peter W. Battaglia
2020	—	`—`	End-to-end deep reinforcement learning in computer systems. Michael Schaarschmidt
2020	A*	`conf`	Reinforcement Learning for the Adaptive Scheduling of Educational Activities. CHI Jonathan Bassen, Bharathan Balaji, Michael Schaarschmidt, Candace Thille, Jay Painter, Dawn Zimmaro, Alex Games, Ethan Fast, John C. Mitchell
2019	J	`jnl`	Learning Index Selection with Structured Action Spaces. CoRR Jeremy Welborn, Michael Schaarschmidt, Eiko Yoneki
2019	—	`conf`	RLgraph: Modular Computation Graphs for Deep Reinforcement Learning. SysML Michael Schaarschmidt, Sven Mika, Kai Fricke, Eiko Yoneki
2019	J	`jnl`	Wield: Systematic Reinforcement Learning With Progressive Randomization. CoRR Michael Schaarschmidt, Kai Fricke, Eiko Yoneki
2018	J	`jnl`	LIFT: Reinforcement Learning in Computer Systems by Learning From Demonstrations. CoRR Michael Schaarschmidt, Alexander Kuhnle, Ben Ellis, Kai Fricke, Felix Gessert, Eiko Yoneki
2018	J	`jnl`	RLgraph: Flexible Computation Graphs for Deep Reinforcement Learning. CoRR Michael Schaarschmidt, Sven Mika, Kai Fricke, Eiko Yoneki
2017	A*	`conf`	BOAT: Building Auto-Tuners with Structured Bayesian Optimization. WWW Valentin Dalibard, Michael Schaarschmidt, Eiko Yoneki
2017	J	`jnl`	Quaestor: Query Web Caching for Database-as-a-Service Providers. Proc. VLDB Endow. Felix Gessert, Michael Schaarschmidt, Wolfram Wingerath, Erik Witt, Eiko Yoneki, Norbert Ritter
2016	J	`jnl`	Learning Runtime Parameters in Computer Systems with Delayed Experience Injection. CoRR Michael Schaarschmidt, Felix Gessert, Valentin Dalibard, Eiko Yoneki
2016	J	`jnl`	Tuning the Scheduling of Distributed Stochastic Gradient Descent with Bayesian Optimization. CoRR Valentin Dalibard, Michael Schaarschmidt, Eiko Yoneki
2015	Misc	`conf`	The Cache Sketch: Revisiting Expiration-based Caching in the Age of Cloud Data Management. BTW Felix Gessert, Michael Schaarschmidt, Wolfram Wingerath, Steffen Friedrich, Norbert Ritter
2015	Misc	`conf`	Towards Automated Polyglot Persistence. BTW Michael Schaarschmidt, Felix Gessert, Norbert Ritter
2014	—	`conf`	Towards a Scalable and Unified REST API for Cloud Data Stores. GI-Jahrestagung Felix Gessert, Steffen Friedrich, Wolfram Wingerath, Michael Schaarschmidt, Norbert Ritter
2006	A	`conf`	Automatic Checking of Component Protocols in Component-Based Systems. SC Wolf Zimmermann, Michael Schaarschmidt