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Landmark-Based Shape Encoding and Sparse-Dictionary Learning in the Continuous Domain

机译：基于地标的形状编码和稀疏字典学习在连续域中

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Daniel Schmitter; Michael Unser;
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年度 2018
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1. Skill based transfer learning with domain adaptation for continuous reinforcement learning domains [J] . Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies . 2020,第2期

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2. Graph based skill acquisition and transfer Learning for continuous reinforcement learning domains [J] . Shoeleh Farzaneh, Asadpour Masoud Pattern recognition letters . 2017,第FEBa1期

机译：基于图的技能获取和转移学习，用于连续强化学习领域
3. Progressive Shape-Distribution-Encoder for Learning 3D Shape Representation [J] . Jin Xie, Fan Zhu, Guoxian Dai, IEEE Transactions on Image Processing . 2017,第3期

机译：用于学习3D形状表示的渐进形状分布编码器
4. Learning Integrated Symbolic and Continuous Action Models for Continuous Domains [C] . Joseph Z. Xu, John E. Laird AAAI conference on artificial intelligence;Innovative applications of artificial intelligence conference;Symposium on educational advances in artificial intelligence . 2013

机译：学习连续域的集成符号和连续动作模型
5. An integrated approach to hierarchical planning, plan execution, and on-line learning in uncertain continuous domains. [D] . Berger, Torsten. 1998

机译：在不确定的连续域中进行分层计划，计划执行和在线学习的集成方法。
6. Pulse Shape Discrimination and Classification Methods for Continuous Depth of Interaction Encoding PET Detectors [O] . Emilie Roncali, Jennifer E. Phipps, Laura Marcu, -1

机译：脉冲形状辨别与分类方法用于连续拍摄宠物检测器
7. Learning Graph-based Representations for Continuous Reinforcement Learning Domains [O] . Jan Hendrik Metzen 2013

机译：学习基于图形的连续强化学习表示
8. Beyond a Principal Limitation of Reinforcement Learning in Continuous Domains. [R] . Linden, A. 1992

机译：超越连续领域强化学习的主要限制。

Landmark-Based Shape Encoding and Sparse-Dictionary Learning in the Continuous Domain

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