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Yonadav Shavit
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Journal Articles
- 2018
- [j1]Yonadav Shavit
, Nadia Figueroa
, Seyed Sina Mirrazavi Salehian
, Aude Billard
:
Learning Augmented Joint-Space Task-Oriented Dynamical Systems: A Linear Parameter Varying and Synergetic Control Approach. IEEE Robotics Autom. Lett. 3(3): 2718-2725 (2018)
Conference and Workshop Papers
- 2023
- [c2]Dami Choi, Yonadav Shavit, David Kristjanson Duvenaud:
Tools for Verifying Neural Models' Training Data. NeurIPS 2023 - 2020
- [c1]Yonadav Shavit, Benjamin L. Edelman, Brian Axelrod:
Causal Strategic Linear Regression. ICML 2020: 8676-8686
Informal and Other Publications
- 2023
- [i6]Yonadav Shavit:
What does it take to catch a Chinchilla? Verifying Rules on Large-Scale Neural Network Training via Compute Monitoring. CoRR abs/2303.11341 (2023) - [i5]Dami Choi, Yonadav Shavit, David Duvenaud:
Tools for Verifying Neural Models' Training Data. CoRR abs/2307.00682 (2023) - [i4]Markus Anderljung, Joslyn Barnhart, Anton Korinek, Jade Leung, Cullen O'Keefe, Jess Whittlestone, Shahar Avin, Miles Brundage, Justin Bullock, Duncan Cass-Beggs, Ben Chang, Tantum Collins, Tim Fist, Gillian K. Hadfield, Alan Hayes, Lewis Ho, Sara Hooker, Eric Horvitz, Noam Kolt, Jonas Schuett, Yonadav Shavit, Divya Siddarth, Robert Trager, Kevin Wolf:
Frontier AI Regulation: Managing Emerging Risks to Public Safety. CoRR abs/2307.03718 (2023) - 2022
- [i3]Andi Peng, Jessica Zosa Forde, Yonadav Shavit, Jonathan Frankle:
Strengthening Subcommunities: Towards Sustainable Growth in AI Research. CoRR abs/2204.08377 (2022) - 2020
- [i2]Yonadav Shavit, Benjamin L. Edelman, Brian Axelrod:
Learning From Strategic Agents: Accuracy, Improvement, and Causality. CoRR abs/2002.10066 (2020) - 2019
- [i1]Yonadav Shavit, William S. Moses:
Extracting Incentives from Black-Box Decisions. CoRR abs/1910.05664 (2019)
Coauthor Index
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