Mark Rowland
Mark Rowland
Research Scientist, DeepMind
在 google.com 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Distributional reinforcement learning with quantile regression
W Dabney, M Rowland, MG Bellemare, R Munos
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
2572018
Gaussian process behaviour in wide deep neural networks
AGG Matthews, M Rowland, J Hron, RE Turner, Z Ghahramani
arXiv preprint arXiv:1804.11271, 2018
2052018
Black-box -divergence Minimization
JM Hernández-Lobato, Y Li, M Rowland, D Hernández-Lobato, T Bui, ...
arXiv preprint arXiv:1511.03243, 2015
1712015
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
832018
α-rank: Multi-agent evaluation by evolution
S Omidshafiei, C Papadimitriou, G Piliouras, K Tuyls, M Rowland, ...
Scientific reports 9 (1), 1-29, 2019
602019
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
602018
The unreasonable effectiveness of structured random orthogonal embeddings
K Choromanski, M Rowland, A Weller
arXiv preprint arXiv:1703.00864, 2017
422017
Revisiting fundamentals of experience replay
W Fedus, P Ramachandran, R Agarwal, Y Bengio, H Larochelle, ...
International Conference on Machine Learning, 3061-3071, 2020
332020
Meta-learning of sequential strategies
PA Ortega, JX Wang, M Rowland, T Genewein, Z Kurth-Nelson, ...
arXiv preprint arXiv:1905.03030, 2019
332019
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
312019
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
262019
Magnetic hamiltonian monte carlo
N Tripuraneni, M Rowland, Z Ghahramani, R Turner
International Conference on Machine Learning, 3453-3461, 2017
252017
Tightness of LP relaxations for almost balanced models
A Weller, M Rowland, D Sontag
Artificial Intelligence and Statistics, 47-55, 2016
252016
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
232021
Geometrically Coupled Monte Carlo Sampling.
M Rowland, K Choromanski, F Chalus, A Pacchiano, T Sarlos, RE Turner, ...
NeurIPS, 195-205, 2018
232018
Multiagent evaluation under incomplete information
M Rowland, S Omidshafiei, K Tuyls, J Perolat, M Valko, G Piliouras, ...
arXiv preprint arXiv:1909.09849, 2019
202019
The geometry of random features
K Choromanski, M Rowland, T Sarlós, V Sindhwani, R Turner, A Weller
International Conference on Artificial Intelligence and Statistics, 1-9, 2018
182018
Unifying orthogonal monte carlo methods
K Choromanski, M Rowland, W Chen, A Weller
International Conference on Machine Learning, 1203-1212, 2019
162019
Orthogonal estimation of wasserstein distances
M Rowland, J Hron, Y Tang, K Choromanski, T Sarlos, A Weller
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
142019
Adaptive trade-offs in off-policy learning
M Rowland, W Dabney, R Munos
International Conference on Artificial Intelligence and Statistics, 34-44, 2020
102020
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