Výsledky vyhledávání - "Huang, Victoria"

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Learning to Optimise Climate Sensor Placement using a Transformer

Autor: Wang, Chen, Huang, Victoria, Chen, Gang, Ma, Hui, Chen, Bryce, Schmidt, Jochen

The optimal placement of sensors for environmental monitoring and disaster management is a challenging problem due to its NP-hard nature. Traditional methods for sensor placement involve exact, approximation, or heuristic approaches, with the latter

Externí odkaz: http://arxiv.org/abs/2310.12387

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Deep Metric Tensor Regularized Policy Gradient

Autor: Chen, Gang, Huang, Victoria

Policy gradient algorithms are an important family of deep reinforcement learning techniques. Many past research endeavors focused on using the first-order policy gradient information to train policy networks. Different from these works, we conduct r

Externí odkaz: http://arxiv.org/abs/2305.11017

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Keep It Simple: Fault Tolerance Evaluation of Federated Learning with Unreliable Clients

Autor: Huang, Victoria, Sohail, Shaleeza, Mayo, Michael, Botran, Tania Lorido, Rodrigues, Mark, Anderson, Chris, Ooi, Melanie

Federated learning (FL), as an emerging artificial intelligence (AI) approach, enables decentralized model training across multiple devices without exposing their local training data. FL has been increasingly gaining popularity in both academia and i

Externí odkaz: http://arxiv.org/abs/2305.09856

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Ensemble Reinforcement Learning in Continuous Spaces -- A Hierarchical Multi-Step Approach for Policy Training

Autor: Chen, Gang, Huang, Victoria

Actor-critic deep reinforcement learning (DRL) algorithms have recently achieved prominent success in tackling various challenging reinforcement learning (RL) problems, particularly complex control tasks with high-dimensional continuous state and act

Externí odkaz: http://arxiv.org/abs/2209.14488

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Akademický článek

Pediatric cerebrospinal fluid rhinorrhea caused by low flow vascular anomaly of the temporal bone: A case series

Autor: Huang, Victoria W., Ruiz-Gutierrez, Melisa, Spera, Erin, Adil, Eelam, Poe, Dennis S., Robson, Caroline D., Shearer, A. Eliot

Publikováno v: In International Journal of Pediatric Otorhinolaryngology July 2024 182

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Multi-Agent Deep Reinforcement Learning for Request Dispatching in Distributed-Controller Software-Defined Networking

Autor: Huang, Victoria, Chen, Gang, Fu, Qiang

Recently, distributed controller architectures have been quickly gaining popularity in Software-Defined Networking (SDN). However, the use of distributed controllers introduces a new and important Request Dispatching (RD) problem with the goal for ev

Externí odkaz: http://arxiv.org/abs/2103.03022

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