Kamyar Azizzadenesheli

verfied profile

∙ 0 followers
University of California, Irvine

Featured Co-authors

Anima Anandkumar
91 publications
Joelle Pineau
84 publications
Yisong Yue
51 publications
Zachary C Lipton
48 publications
Mohammad Ghavamzadeh
45 publications
Emma Brunskill
44 publications
Alessandro Lazaric
37 publications
Yu-Xiang Wang
33 publications
Prabhat
29 publications
Babak Hassibi
25 publications
Amy Zhang
15 publications

Deep Bayesian Quadrature Policy Optimization

We study the problem of obtaining accurate policy gradient estimates. Th...
06/28/2020 ∙ by Akella Ravi Tej, et al. ∙ 6 ∙ share

read it
Competitive Policy Optimization

A core challenge in policy optimization in competitive Markov decision p...
06/18/2020 ∙ by Manish Prajapat, et al. ∙ 16 ∙ share

read it
Multipole Graph Neural Operator for Parametric Partial Differential Equations

One of the main challenges in using deep learning-based methods for simu...
06/16/2020 ∙ by Zongyi Li, et al. ∙ 5 ∙ share

read it
MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework

We propose MeshfreeFlowNet, a novel deep learning-based super-resolution...
05/01/2020 ∙ by Chiyu "Max" Jiang, et al. ∙ 3 ∙ share

read it
Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems

We study the problem of adaptive control in partially observable linear ...
03/25/2020 ∙ by Sahin Lale, et al. ∙ 4 ∙ share

read it
EikoNet: Solving the Eikonal equation with Deep Neural Networks

The recent deep learning revolution has created an enormous opportunity ...
03/25/2020 ∙ by Jonathan D. Smith, et al. ∙ 31 ∙ share

read it
Regret Bound of Adaptive Control in Linear Quadratic Gaussian (LQG) Systems

We study the problem of adaptive control in partially observable linear ...
03/12/2020 ∙ by Sahin Lale, et al. ∙ 4 ∙ share

read it
Neural Operator: Graph Kernel Network for Partial Differential Equations

The classical development of neural networks has been primarily for mapp...
03/07/2020 ∙ by Zongyi Li, et al. ∙ 22 ∙ share

read it
Regret Minimization in Partially Observable Linear Quadratic Control

We study the problem of regret minimization in partially observable line...
01/31/2020 ∙ by Sahin Lale, et al. ∙ 13 ∙ share

read it
Directivity Modes of Earthquake Populations with Unsupervised Learning

We present a novel approach for resolving modes of rupture directivity i...
06/30/2019 ∙ by Zachary E. Ross, et al. ∙ 0 ∙ share

read it
Learning Causal State Representations of Partially Observable Environments

Intelligent agents can cope with sensory-rich environments by learning t...
06/25/2019 ∙ by Amy Zhang, et al. ∙ 68 ∙ share

read it
Regularized Learning for Domain Adaptation under Label Shifts

We propose Regularized Learning under Label shifts (RLLS), a principled ...
03/22/2019 ∙ by Kamyar Azizzadenesheli, et al. ∙ 0 ∙ share

read it
Stochastic Linear Bandits with Hidden Low Rank Structure

High-dimensional representations often have a lower dimensional underlyi...
01/28/2019 ∙ by Sahin Lale, et al. ∙ 18 ∙ share

read it
Neural Lander: Stable Drone Landing Control using Learned Dynamics

Precise trajectory control near ground is difficult for multi-rotor dron...
11/19/2018 ∙ by Guanya Shi, et al. ∙ 0 ∙ share

read it
Trust Region Policy Optimization of POMDPs

We propose Generalized Trust Region Policy Optimization (GTRPO), a Reinf...
10/18/2018 ∙ by Kamyar Azizzadenesheli, et al. ∙ 0 ∙ share

read it
signSGD with Majority Vote is Communication Efficient And Byzantine Fault Tolerant

Training neural networks on large datasets can be accelerated by distrib...
10/11/2018 ∙ by Jeremy Bernstein, et al. ∙ 0 ∙ share

read it
Sample-Efficient Deep RL with Generative Adversarial Tree Search

We propose Generative Adversarial Tree Search (GATS), a sample-efficient...
06/15/2018 ∙ by Kamyar Azizzadenesheli, et al. ∙ 4 ∙ share

read it
Stochastic Activation Pruning for Robust Adversarial Defense

Neural networks are known to be vulnerable to adversarial examples. Care...
03/05/2018 ∙ by Guneet S. Dhillon, et al. ∙ 0 ∙ share

read it
signSGD: compressed optimisation for non-convex problems

Training large neural networks requires distributing learning across mul...
02/13/2018 ∙ by Jeremy Bernstein, et al. ∙ 0 ∙ share

read it
Efficient Exploration through Bayesian Deep Q-Networks

We propose Bayesian Deep Q-Network (BDQN), a practical Thompson sampling...
02/13/2018 ∙ by Kamyar Azizzadenesheli, et al. ∙ 0 ∙ share

read it
Experimental results : Reinforcement Learning of POMDPs using Spectral Methods

We propose a new reinforcement learning algorithm for partially observab...
05/07/2017 ∙ by Kamyar Azizzadenesheli, et al. ∙ 0 ∙ share

read it
Reinforcement Learning in Rich-Observation MDPs using Spectral Methods

Designing effective exploration-exploitation algorithms in Markov decisi...
11/11/2016 ∙ by Kamyar Azizzadenesheli, et al. ∙ 0 ∙ share

read it
Reinforcement Learning of POMDPs using Spectral Methods

We propose a new reinforcement learning algorithm for partially observab...
02/25/2016 ∙ by Kamyar Azizzadenesheli, et al. ∙ 0 ∙ share

read it