Michael Schaarschmidt

According to our database, Michael Schaarschmidt authored at least 22 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

PartIR: Composing SPMD Partitioning Strategies for Machine Learning.

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

CoRR, 2024

2023

Pre-training via Denoising for Molecular Property Prediction.

Sheheryar Zaidi, Michael Schaarschmidt, James Martens, Hyunjik Kim, Yee Whye Teh, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Razvan Pascanu, Jonathan Godwin

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Automatic Discovery of Composite SPMD Partitioning Strategies in PartIR.

Sami Alabed, Dominik Grewe, Juliana Franco, Bart Chrzaszcz, Tom Natan, Tamara Norman, Norman A. Rink, Dimitrios Vytiniotis, Michael Schaarschmidt

CoRR, 2022

Learned Force Fields Are Ready For Ground State Catalyst Discovery.

Michael Schaarschmidt, Morgane Riviere, Alex M. Ganose, James S. Spencer, Alexander L. Gaunt, James Kirkpatrick, Simon Axelrod, Peter W. Battaglia, Jonathan Godwin

CoRR, 2022

Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond.

Jonathan Godwin, Michael Schaarschmidt, Alexander L. Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Velickovic, James Kirkpatrick, Peter W. Battaglia

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Automap: Towards Ergonomic Automated Parallelism for ML Models.

Michael Schaarschmidt, Dominik Grewe, Dimitrios Vytiniotis, Adam Paszke, Georg Stefan Schmid, Tamara Norman, James Molloy, Jonathan Godwin, Norman Alexander Rink, Vinod Nair, Dan Belov

CoRR, 2021

Very Deep Graph Neural Networks Via Noise Regularisation.

Jonathan Godwin, Michael Schaarschmidt, Alexander L. Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Velickovic, James Kirkpatrick, Peter W. Battaglia

CoRR, 2021

2020

End-to-end deep reinforcement learning in computer systems.

Michael Schaarschmidt

PhD thesis, 2020

Reinforcement Learning for the Adaptive Scheduling of Educational Activities.

Jonathan Bassen, Bharathan Balaji, Michael Schaarschmidt, Candace Thille, Jay Painter, Dawn Zimmaro, Alex Games, Ethan Fast, John C. Mitchell

Proceedings of the CHI '20: CHI Conference on Human Factors in Computing Systems, 2020

2019

Learning Index Selection with Structured Action Spaces.

Jeremy Welborn, Michael Schaarschmidt, Eiko Yoneki

CoRR, 2019

Wield: Systematic Reinforcement Learning With Progressive Randomization.

Michael Schaarschmidt, Kai Fricke, Eiko Yoneki

CoRR, 2019

RLgraph: Modular Computation Graphs for Deep Reinforcement Learning.

Michael Schaarschmidt, Sven Mika, Kai Fricke, Eiko Yoneki

Proceedings of Machine Learning and Systems 2019, 2019

2018

RLgraph: Flexible Computation Graphs for Deep Reinforcement Learning.

Michael Schaarschmidt, Sven Mika, Kai Fricke, Eiko Yoneki

CoRR, 2018

LIFT: Reinforcement Learning in Computer Systems by Learning From Demonstrations.

Michael Schaarschmidt, Alexander Kuhnle, Ben Ellis, Kai Fricke, Felix Gessert, Eiko Yoneki

CoRR, 2018

2017

Quaestor: Query Web Caching for Database-as-a-Service Providers.

Felix Gessert, Michael Schaarschmidt, Wolfram Wingerath, Erik Witt, Eiko Yoneki, Norbert Ritter

Proc. VLDB Endow., 2017

BOAT: Building Auto-Tuners with Structured Bayesian Optimization.

Valentin Dalibard, Michael Schaarschmidt, Eiko Yoneki

Proceedings of the 26th International Conference on World Wide Web, 2017

2016

Learning Runtime Parameters in Computer Systems with Delayed Experience Injection.

Michael Schaarschmidt, Felix Gessert, Valentin Dalibard, Eiko Yoneki

CoRR, 2016

Tuning the Scheduling of Distributed Stochastic Gradient Descent with Bayesian Optimization.

Valentin Dalibard, Michael Schaarschmidt, Eiko Yoneki

CoRR, 2016

2015

Towards Automated Polyglot Persistence.

Michael Schaarschmidt, Felix Gessert, Norbert Ritter

Proceedings of the Datenbanksysteme für Business, 2015

The Cache Sketch: Revisiting Expiration-based Caching in the Age of Cloud Data Management.

Felix Gessert, Michael Schaarschmidt, Wolfram Wingerath, Steffen Friedrich, Norbert Ritter

Proceedings of the Datenbanksysteme für Business, 2015

2014

Towards a Scalable and Unified REST API for Cloud Data Stores.

Felix Gessert, Steffen Friedrich, Wolfram Wingerath, Michael Schaarschmidt, Norbert Ritter

Proceedings of the 44. Jahrestagung der Gesellschaft für Informatik, Big Data, 2014

2006

Automatic Checking of Component Protocols in Component-Based Systems.

Wolf Zimmermann, Michael Schaarschmidt

Proceedings of the Software Composition - 5th International Symposium, 2006