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From Reinforcement Learning to Deep Reinforcement Learning: An Overview

2018
This article provides a brief overview of reinforcement learning, from its origins to current research trends, including deep reinforcement learning, with an emphasis on first principles.
Pierre Baldi   +3 more
openaire   +1 more source

Reinforcement and Deep Reinforcement Machine Learning

2017
Data-driven learning is a very strong concept. This concept is chased and converted into wonderful applications. Whole stream of Data Engineering and Data Sciences emerged out of that. The data is collected from various sources. It is collected from big hospitals, data repositories, from cookies running in your machines, intelligent applications ...
openaire   +2 more sources

Deep Eutectic Solvents: A Review of Fundamentals and Applications

Chemical Reviews, 2021
Brian Chen, Yong Zhang, Jeffrey M Klein
exaly  

Soft wearable devices for deep-tissue sensing

Nature Reviews Materials, 2022
Muyang Lin, Hongjie Hu, Sai Zhou
exaly  

Deep neural networks for the evaluation and design of photonic devices

Nature Reviews Materials, 2020
Jiaqi Jiang   +2 more
exaly  

Epithelial ovarian cancer: Evolution of management in the era of precision medicine

Ca-A Cancer Journal for Clinicians, 2019
Stephanie Lheureux   +2 more
exaly  

Radiotherapy combination opportunities leveraging immunity for the next oncology practice

Ca-A Cancer Journal for Clinicians, 2017
Fernanda G Herrera   +2 more
exaly  

Staging Soft Tissue Sarcoma: Evolution and Change

Ca-A Cancer Journal for Clinicians, 2006
Alexander J F Lazar
exaly  

Deep learning

Nature, 2015
Yann Lecun   +2 more
exaly  

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