دنبال کردن
Mark Rowland
Mark Rowland
Research Scientist, Google DeepMind
ایمیل تأیید شده در google.com - صفحهٔ اصلی
عنوان
نقل شده توسط
نقل شده توسط
سال
Distributional reinforcement learning with quantile regression‏
W Dabney, M Rowland, M Bellemare, R Munos‏
Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018‏
9672018
Gaussian process behaviour in wide deep neural networks‏
AGG Matthews, M Rowland, J Hron, RE Turner, Z Ghahramani‏
arXiv preprint arXiv:1804.11271, 2018‏
609*2018
A general theoretical paradigm to understand learning from human preferences‏
MG Azar, ZD Guo, B Piot, R Munos, M Rowland, M Valko, D Calandriello‏
International Conference on Artificial Intelligence and Statistics, 4447-4455, 2024‏
4352024
Revisiting fundamentals of experience replay‏
W Fedus, P Ramachandran, R Agarwal, Y Bengio, H Larochelle, ...‏
International conference on machine learning, 3061-3071, 2020‏
3412020
Black-box -divergence Minimization‏
JM Hernández-Lobato, Y Li, M Rowland, D Hernández-Lobato, T Bui, ...‏
arXiv preprint arXiv:1511.03243, 2015‏
2882015
Mastering the game of Stratego with model-free multiagent reinforcement learning‏
J Perolat, B De Vylder, D Hennes, E Tarassov, F Strub, V de Boer, ...‏
Science 378 (6623), 990-996, 2022‏
2682022
Distributional reinforcement learning‏
MG Bellemare, W Dabney, M Rowland‏
MIT Press, 2023‏
1842023
Structured evolution with compact architectures for scalable policy optimization‏
K Choromanski, M Rowland, V Sindhwani, R Turner, A Weller‏
International Conference on Machine Learning, 970-978, 2018‏
1602018
α-Rank: Multi-Agent Evaluation by Evolution‏
S Omidshafiei, C Papadimitriou, G Piliouras, K Tuyls, M Rowland, ...‏
Scientific reports 9 (1), 9937, 2019‏
1512019
An analysis of categorical distributional reinforcement learning‏
M Rowland, M Bellemare, W Dabney, R Munos, YW Teh‏
International Conference on Artificial Intelligence and Statistics, 29-37, 2018‏
1502018
Understanding and preventing capacity loss in reinforcement learning‏
C Lyle, M Rowland, W Dabney‏
arXiv preprint arXiv:2204.09560, 2022‏
1232022
A generalized training approach for multiagent learning‏
P Muller, S Omidshafiei, M Rowland, K Tuyls, J Perolat, S Liu, D Hennes, ...‏
arXiv preprint arXiv:1909.12823, 2019‏
1222019
Nash learning from human feedback‏
R Munos, M Valko, D Calandriello, MG Azar, M Rowland, ZD Guo, Y Tang, ...‏
arXiv preprint arXiv:2312.00886 18, 2023‏
1202023
Meta-learning of sequential strategies‏
PA Ortega, JX Wang, M Rowland, T Genewein, Z Kurth-Nelson, ...‏
arXiv preprint arXiv:1905.03030, 2019‏
1152019
Game Plan: What AI can do for Football, and What Football can do for AI‏
K Tuyls, S Omidshafiei, P Muller, Z Wang, J Connor, D Hennes, I Graham, ...‏
Journal of Artificial Intelligence Research 71, 41-88, 2021‏
1142021
Statistics and samples in distributional reinforcement learning‏
M Rowland, R Dadashi, S Kumar, R Munos, MG Bellemare, W Dabney‏
International Conference on Machine Learning, 5528-5536, 2019‏
1122019
From poincaré recurrence to convergence in imperfect information games: Finding equilibrium via regularization‏
J Perolat, R Munos, JB Lespiau, S Omidshafiei, M Rowland, P Ortega, ...‏
International Conference on Machine Learning, 8525-8535, 2021‏
1022021
The unreasonable effectiveness of structured random orthogonal embeddings‏
KM Choromanski, M Rowland, A Weller‏
Advances in neural information processing systems 30, 2017‏
1012017
On the effect of auxiliary tasks on representation dynamics‏
C Lyle, M Rowland, G Ostrovski, W Dabney‏
International Conference on Artificial Intelligence and Statistics, 1-9, 2021‏
822021
Generalized preference optimization: A unified approach to offline alignment‏
Y Tang, ZD Guo, Z Zheng, D Calandriello, R Munos, M Rowland, ...‏
arXiv preprint arXiv:2402.05749, 2024‏
732024
سیستم در حال حاضر قادر به انجام عملکرد نیست. بعداً دوباره امتحان کنید.
مقاله‌ها 1–20