Kamyar Azizzadenesheli

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University of California, Irvine

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Off-Policy Risk Assessment in Contextual Bandits

To evaluate prospective contextual bandit policies when experimentation ...
04/18/2021 ∙ by Audrey Huang, et al. ∙ 0 ∙ share

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On the Convergence and Optimality of Policy Gradient for Markov Coherent Risk

In order to model risk aversion in reinforcement learning, an emerging l...
03/04/2021 ∙ by Audrey Huang, et al. ∙ 0 ∙ share

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Multi-Agent Multi-Armed Bandits with Limited Communication

We consider the problem where N agents collaboratively interact with an ...
02/10/2021 ∙ by Mridul Agarwal, et al. ∙ 0 ∙ share

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HypoSVI: Hypocenter inversion with Stein variational inference and Physics Informed Neural Networks

We introduce a scheme for probabilistic hypocenter inversion with Stein ...
01/09/2021 ∙ by Jonathan D. Smith, et al. ∙ 7 ∙ share

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Importance Weight Estimation and Generalization in Domain Adaptation under Label Shift

We study generalization under label shift in domain adaptation where the...
11/29/2020 ∙ by Kamyar Azizzadenesheli, et al. ∙ 0 ∙ share

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Fourier Neural Operator for Parametric Partial Differential Equations

The classical development of neural networks has primarily focused on le...
10/18/2020 ∙ by Zongyi Li, et al. ∙ 170 ∙ share

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Explore More and Improve Regret in Linear Quadratic Regulators

Stabilizing the unknown dynamics of a control system and minimizing regr...
07/23/2020 ∙ by Sahin Lale, et al. ∙ 27 ∙ share

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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

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Competitive Policy Optimization

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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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