Daniel Graves
Daniel Graves
Unknown affiliation
Verified email at ualberta.ca
Title
Cited by
Cited by
Year
Kernel-based fuzzy clustering and fuzzy clustering: A comparative experimental study
D Graves, W Pedrycz
Fuzzy sets and systems 161 (4), 522-543, 2010
3542010
Fuzzy prediction architecture using recurrent neural networks
D Graves, W Pedrycz
Neurocomputing 72 (7-9), 1668-1678, 2009
632009
Fuzzy c-means, gustafson-kessel fcm, and kernel-based fcm: A comparative study
D Graves, W Pedrycz
Analysis and design of intelligent systems using soft computing techniques …, 2007
472007
A clustering-based graph Laplacian framework for value function approximation in reinforcement learning
X Xu, Z Huang, D Graves, W Pedrycz
IEEE Transactions on Cybernetics 44 (12), 2613-2625, 2014
322014
Performance of kernel-based fuzzy clustering
D Graves, W Pedrycz
Electronics Letters 43 (25), 1445-1446, 2007
302007
Smarts: Scalable multi-agent reinforcement learning training school for autonomous driving
M Zhou, J Luo, J Villella, Y Yang, D Rusu, J Miao, W Zhang, M Alban, ...
arXiv preprint arXiv:2010.09776, 2020
292020
Multivariate Segmentation of Time Series with Differential Evolution.
D Graves, W Pedrycz
IFSA/EUSFLAT Conf., 1108-1113, 2009
202009
Importance resampling for off-policy prediction
M Schlegel, W Chung, D Graves, J Qian, M White
arXiv preprint arXiv:1906.04328, 2019
192019
Mapless Navigation among Dynamics with Social-safety-awareness: a reinforcement learning approach from 2D laser scans
J Jin, NM Nguyen, N Sakib, D Graves, H Yao, M Jagersand
2020 IEEE International Conference on Robotics and Automation (ICRA), 6979-6985, 2020
142020
Clustering with proximity knowledge and relational knowledge
D Graves, J Noppen, W Pedrycz
Pattern recognition 45 (7), 2633-2644, 2012
142012
Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems
Y Yang, J Luo, Y Wen, O Slumbers, D Graves, HB Ammar, J Wang, ...
arXiv preprint arXiv:2102.07659, 2021
102021
Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems
Y Yang, J Luo, Y Wen, O Slumbers, D Graves, HB Ammar, J Wang, ...
arXiv preprint arXiv:2102.07659, 2021
102021
A survey and formal analyses on sequence learning methodologies and deep neural networks
Y Wang, H Leung, M Gavrilova, O Zatarain, D Graves, J Lu, N Howard, ...
2018 IEEE 17th International Conference on Cognitive Informatics & Cognitive …, 2018
102018
Fixed-horizon temporal difference methods for stable reinforcement learning
K De Asis, A Chan, S Pitis, R Sutton, D Graves
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3741-3748, 2020
82020
Perception as prediction using general value functions in autonomous driving applications
D Graves, K Rezaee, S Scheideman
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019
82019
Learning predictive representations in autonomous driving to improve deep reinforcement learning
D Graves, NM Nguyen, K Hassanzadeh, J Jin
arXiv preprint arXiv:2006.15110, 2020
62020
Proximity fuzzy clustering and its application to time series clustering and prediction
D Graves, W Pedrycz
2010 10th International Conference on Intelligent Systems Design and …, 2010
52010
Structural segmentation of music with fuzzy clustering
D Graves, W Pedrycz
Canadian Acoustics 36 (3), 84-85, 2008
52008
Offline Learning of Counterfactual Perception as Prediction for Real-World Robotic Reinforcement Learning
J Jin, D Graves, C Haigh, J Luo, M Jagersand
arXiv preprint arXiv:2011.05857, 2020
32020
Method and system for adaptively controlling object spacing
DM Graves, K Rezaee
US Patent App. 15/965,182, 2019
22019
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