Kamyar Azizzadenesheli
Kamyar Azizzadenesheli
Postdoctoral fellow at Caltech
Verified email at caltech.edu - Homepage
Title
Cited by
Cited by
Year
Stochastic activation pruning for robust adversarial defense
GS Dhillon, K Azizzadenesheli, ZC Lipton, J Bernstein, J Kossaifi, ...
International Conference on Learning Representations (ICLR) 2018, 2018
1992018
signSGD: compressed optimisation for non-convex problems
J Bernstein, YX Wang, K Azizzadenesheli, A Anandkumar
International Conference on Machine Learning (ICML) 2018, 2018
1472018
Efficient Exploration through Bayesian Deep Q-Networks
K Azizzadenesheli, A Anandkumar
Neural Information Processing Systems (NIPS) 2017 Workshop, 2018
642018
Reinforcement learning of POMDPs using spectral methods
K Azizzadenesheli, A Lazaric, A Anandkumar
29th Annual Conference on Learning Theory (COLT) 2016, 2016
542016
Combating Reinforcement Learning's Sisyphean Curse with Intrinsic Fear
ZC Lipton, K Azizzadenesheli, A Kumar, L Li, J Gao, L Deng
Neural Information Processing Systems (NIPS) 2016 Workshop, 2016
49*2016
Neural Lander: Stable Drone Landing Control using Learned Dynamics
G Shi, X Shi, M O'Connell, R Yu, K Azizzadenesheli, A Anandkumar, ...
International Conference on Robotics and Automation (ICRA) 2019, 2018
442018
signSGD with Majority Vote is Communication Efficient and Fault Tolerant
J Bernstein, J Zhao, K Azizzadenesheli, A Anandkumar
International Conference on Learning Representations (ICLR) 2019, 2018
242018
Regularized Learning for Domain Adaptation under Label Shifts
K Azizzadenesheli, A Liu, F Yang, A Anandkumar
International Conference on Learning Representations (ICLR) 2018, 2018
242018
Surprising Negative Results for Generative Adversarial Tree Search
K Azizzadenesheli, B Yang, W Liu, Z Lipton, A Anandkumar
Neural Information Processing Systems (NeurIPS) 2018 Workshop, 2018
22*2018
Reinforcement learning in rich-observation MDPs using spectral methods
K Azizzadenesheli, A Lazaric, A Anandkumar
Multi-disciplinary Conference on Reinforcement Learning and Decision Making …, 2016
152016
Maybe a few considerations in Reinforcement Learning Research?
K Azizzadenesheli
52019
Stochastic linear bandits with hidden low rank structure
S Lale, K Azizzadenesheli, A Anandkumar, B Hassibi
arXiv preprint arXiv:1901.09490, 2019
52019
Open problem: Approximate planning of POMDPs in the class of memoryless policies
K Azizzadenesheli, A Lazaric, A Anandkumar
Conference on Learning Theory (COLT) 2016, 1639-1642, 1639-1642, 2016
52016
Neural Operator: Graph Kernel Network for Partial Differential Equations
Z Li, N Kovachki, K Azizzadenesheli, B Liu, K Bhattacharya, A Stuart, ...
The International Conference on Learning Representations (ICLR) 2020, Workshop, 2020
42020
Learning causal state representations of partially observable environments
A Zhang, ZC Lipton, L Pineda, K Azizzadenesheli, A Anandkumar, L Itti, ...
arXiv preprint arXiv:1906.10437, 2019
42019
Experimental results: Reinforcement learning of pomdps using spectral methods
K Azizzadenesheli, A Lazaric, A Anandkumar
arXiv preprint arXiv:1705.02553, 2017
42017
Eikonet: Solving the eikonal equation with deep neural networks
JD Smith, K Azizzadenesheli, ZE Ross
arXiv preprint arXiv:2004.00361, 2020
32020
Policy Gradient in Partially Observable Environments: Approximation and Convergence
K Azizzadenesheli, Y Yue, A Anandkumar
arXiv preprint arXiv:1810.07900, 2018
3*2018
Regret Bound of Adaptive Control in Linear Quadratic Gaussian (LQG) Systems
S Lale, K Azizzadenesheli, B Hassibi, A Anandkumar
arXiv preprint arXiv:2003.05999, 2020
22020
Regret minimization in partially observable linear quadratic control
S Lale, K Azizzadenesheli, B Hassibi, A Anandkumar
Appeared at Neural Information Processing Systems (NeurIPS) 2019 Workshop, 2020
22020
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Articles 1–20