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Alistair Letcher
Alistair Letcher
Verified email at maths.ox.ac.uk - Homepage
Title
Cited by
Cited by
Year
Stable opponent shaping in differentiable games
A Letcher, J Foerster, D Balduzzi, T Rocktäschel, S Whiteson
International Conference on Learning Representations, 2019
1222019
Differentiable game mechanics
A Letcher, D Balduzzi, S Racaniere, J Martens, J Foerster, K Tuyls, ...
Journal of Machine Learning Research 20 (84), 1-40, 2019
962019
Discovered policy optimisation
C Lu, J Kuba, A Letcher, L Metz, C Schroeder de Witt, J Foerster
Advances in Neural Information Processing Systems 35, 16455-16468, 2022
612022
COLA: consistent learning with opponent-learning awareness
T Willi, AH Letcher, J Treutlein, J Foerster
International Conference on Machine Learning, 23804-23831, 2022
472022
On the impossibility of global convergence in multi-loss optimization
A Letcher
International Conference on Learning Representations, 2020
332020
Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian
J Parker-Holder, L Metz, C Resnick, H Hu, A Lerer, A Letcher, ...
Advances in Neural Information Processing Systems 33, 2020
302020
Adversarial cheap talk
C Lu, T Willi, A Letcher, JN Foerster
International Conference on Machine Learning, 22917-22941, 2023
202023
From tight gradient bounds for parameterized quantum circuits to the absence of barren plateaus in QGANs
A Letcher, S Woerner, C Zoufal
arXiv preprint arXiv:2309.12681, 2023
142023
Stability and Exploitation in Differentiable Games
A Letcher
Master’s thesis, University of Oxford., 2018
62018
Tight and Efficient Gradient Bounds for Parameterized Quantum Circuits
A Letcher, S Woerner, C Zoufal
Quantum 8, 1484, 2024
52024
Automatic Conflict Detection in Police Body-Worn Audio
A Letcher, J Trišović, C Cademartori, X Chen, J Xu
IEEE International Conference on Acoustics, Speech and Signal Processing …, 2018
52018
Polymatrix Competitive Gradient Descent
J Ma, A Letcher, F Schäfer, Y Shi, A Anandkumar
arXiv preprint arXiv:2111.08565, 2021
12021
Higher Order and Self-Referential Evolution for Population-based Methods
S Coward, C Lu, A Letcher, M Jiang, J Parker-Holder, JN Foerster
Automated Reinforcement Learning: Exploring Meta-Learning, AutoML, and LLMs, 0
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Articles 1–13