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pro vyhledávání: '"Green, Sam"'
The Graph Protocol indexes historical blockchain transaction data and makes it available for querying. As the protocol is decentralized, there are many independent Indexers that index and compete with each other for serving queries to the Consumers.
Externí odkaz:
http://arxiv.org/abs/2212.07942
Autor:
Heaton, Howard, Green, Sam
Organizations are often unable to align the interests of all stakeholders with the financial success of the organization (e.g. due to regulation). However, continuous organizations (COs) introduce a paradigm shift. COs offer immediate liquidity, are
Externí odkaz:
http://arxiv.org/abs/2203.10644
Autor:
Williams, Kyle R., Schlossman, Rachel, Whitten, Daniel, Ingram, Joe, Musuvathy, Srideep, Patel, Anirudh, Pagan, James, Williams, Kyle A., Green, Sam, Mazumdar, Anirban, Parish, Julie
Publikováno v:
IEEE Transactions on Aerospace and Electronic Systems, 59 (2023) 2513-2529
This paper presents a technique for trajectory planning based on continuously parameterized high-level actions (motion primitives) of variable duration. This technique leverages deep reinforcement learning (Deep RL) to formulate a policy which is sui
Externí odkaz:
http://arxiv.org/abs/2110.00044
Publikováno v:
Proceedings of the 7th Workshop on Socio-Technical Aspects in Security and Trust (STAST'17), ACM Press, December 2018, pp. 3-15
Background. The current cognitive state, such as cognitive effort and depletion, incidental affect or stress may impact the strength of a chosen password unconsciously. Aim. We investigate the effect of incidental fear and stress on the measured stre
Externí odkaz:
http://arxiv.org/abs/2009.12150
Early neural network architectures were designed by so-called "grad student descent". Since then, the field of Neural Architecture Search (NAS) has developed with the goal of algorithmically designing architectures tailored for a dataset of interest.
Externí odkaz:
http://arxiv.org/abs/1911.05704
Vision-based deep reinforcement learning (RL) typically obtains performance benefit by using high capacity and relatively large convolutional neural networks (CNN). However, a large network leads to higher inference costs (power, latency, silicon are
Externí odkaz:
http://arxiv.org/abs/1901.08128
Modern vision-based reinforcement learning techniques often use convolutional neural networks (CNN) as universal function approximators to choose which action to take for a given visual input. Until recently, CNNs have been treated like black-box fun
Externí odkaz:
http://arxiv.org/abs/1809.06781
Autor:
Eliezer, Dilharan D., Holmes, Merran, Sullivan, Gavin, Gani, Jon, Pockney, Peter, Gould, Tiffany, Gramlick, Madelyn, Rugendyke, Anya, Ming, Joyce, Jones, Shaun, Coleman, Hannah, Hawthorne, Jacqueline, Green, Sam, Zardawi, Daniel, Hampton, Jacob, Francis, Gabrielle
Publikováno v:
In Journal of Surgical Research February 2020 246:300-304
Akademický článek
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