Kamyar Azizzadenesheli
Kamyar Azizzadenesheli
Assistant Professor at Purdue University
Verified email at purdue.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
2692018
signSGD: compressed optimisation for non-convex problems
J Bernstein, YX Wang, K Azizzadenesheli, A Anandkumar
International Conference on Machine Learning (ICML) 2018, 2018
2642018
Efficient Exploration through Bayesian Deep Q-Networks
K Azizzadenesheli, A Anandkumar
Neural Information Processing Systems (NIPS) 2017 Workshop, 2018
892018
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
722018
Reinforcement learning of POMDPs using spectral methods
K Azizzadenesheli, A Lazaric, A Anandkumar
29th Annual Conference on Learning Theory (COLT) 2016, 2016
642016
Regularized Learning for Domain Adaptation under Label Shifts
K Azizzadenesheli, A Liu, F Yang, A Anandkumar
International Conference on Learning Representations (ICLR) 2018, 2018
562018
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
53*2016
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
442018
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
21*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
162016
Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems
S Lale, K Azizzadenesheli, B Hassibi, A Anandkumar
Neural Information Processing Systems (Neurips) 2020, 2020
142020
MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework
CM Jiang, S Esmaeilzadeh, K Azizzadenesheli, K Kashinath, M Mustafa, ...
SC20 The International Conference for High Performance Computing, Networking …, 2020
10*2020
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
102019
Fourier neural operator for parametric partial differential equations
Z Li, N Kovachki, K Azizzadenesheli, B Liu, K Bhattacharya, A Stuart, ...
arXiv preprint arXiv:2010.08895, 2020
92020
Eikonet: Solving the eikonal equation with deep neural networks
JD Smith, K Azizzadenesheli, ZE Ross
IEEE Transactions on Geoscience and Remote Sensing 2020, 2020
82020
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
82020
Stochastic linear bandits with hidden low rank structure
S Lale, K Azizzadenesheli, A Anandkumar, B Hassibi
arXiv preprint arXiv:1901.09490, 2019
82019
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
82016
Policy Gradient in Partially Observable Environments: Approximation and Convergence
K Azizzadenesheli, Y Yue, A Anandkumar
arXiv preprint arXiv:1810.07900, 2018
6*2018
Adaptive Control and Regret Minimization in Linear Quadratic Gaussian (LQG) Setting
S Lale, K Azizzadenesheli, B Hassibi, A Anandkumar
American Control Conference (ACC) 2021, 2020
5*2020
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Articles 1–20