Artykuły w czasopismach na temat „State representation learning”
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Xu, Cai, Wei Zhao, Jinglong Zhao, Ziyu Guan, Yaming Yang, Long Chen i Xiangyu Song. "Progressive Deep Multi-View Comprehensive Representation Learning". Proceedings of the AAAI Conference on Artificial Intelligence 37, nr 9 (26.06.2023): 10557–65. http://dx.doi.org/10.1609/aaai.v37i9.26254.
Pełny tekst źródłaYue, Yang, Bingyi Kang, Zhongwen Xu, Gao Huang i Shuicheng Yan. "Value-Consistent Representation Learning for Data-Efficient Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 37, nr 9 (26.06.2023): 11069–77. http://dx.doi.org/10.1609/aaai.v37i9.26311.
Pełny tekst źródłade Bruin, Tim, Jens Kober, Karl Tuyls i Robert Babuska. "Integrating State Representation Learning Into Deep Reinforcement Learning". IEEE Robotics and Automation Letters 3, nr 3 (lipiec 2018): 1394–401. http://dx.doi.org/10.1109/lra.2018.2800101.
Pełny tekst źródłaChen, Haoqiang, Yadong Liu, Zongtan Zhou i Ming Zhang. "A2C: Attention-Augmented Contrastive Learning for State Representation Extraction". Applied Sciences 10, nr 17 (26.08.2020): 5902. http://dx.doi.org/10.3390/app10175902.
Pełny tekst źródłaOng, Sylvie, Yuri Grinberg i Joelle Pineau. "Mixed Observability Predictive State Representations". Proceedings of the AAAI Conference on Artificial Intelligence 27, nr 1 (30.06.2013): 746–52. http://dx.doi.org/10.1609/aaai.v27i1.8680.
Pełny tekst źródłaMaier, Marc, Brian Taylor, Huseyin Oktay i David Jensen. "Learning Causal Models of Relational Domains". Proceedings of the AAAI Conference on Artificial Intelligence 24, nr 1 (3.07.2010): 531–38. http://dx.doi.org/10.1609/aaai.v24i1.7695.
Pełny tekst źródłaLesort, Timothée, Natalia Díaz-Rodríguez, Jean-Frano̧is Goudou i David Filliat. "State representation learning for control: An overview". Neural Networks 108 (grudzień 2018): 379–92. http://dx.doi.org/10.1016/j.neunet.2018.07.006.
Pełny tekst źródłaChornozhuk, S. "The New Geometric “State-Action” Space Representation for Q-Learning Algorithm for Protein Structure Folding Problem". Cybernetics and Computer Technologies, nr 3 (27.10.2020): 59–73. http://dx.doi.org/10.34229/2707-451x.20.3.6.
Pełny tekst źródłaZhang, Yujia, Lai-Man Po, Xuyuan Xu, Mengyang Liu, Yexin Wang, Weifeng Ou, Yuzhi Zhao i Wing-Yin Yu. "Contrastive Spatio-Temporal Pretext Learning for Self-Supervised Video Representation". Proceedings of the AAAI Conference on Artificial Intelligence 36, nr 3 (28.06.2022): 3380–89. http://dx.doi.org/10.1609/aaai.v36i3.20248.
Pełny tekst źródłaLi, Dongfen, Lichao Meng, Jingjing Li, Ke Lu i Yang Yang. "Domain adaptive state representation alignment for reinforcement learning". Information Sciences 609 (wrzesień 2022): 1353–68. http://dx.doi.org/10.1016/j.ins.2022.07.156.
Pełny tekst źródłaRazmi, Niloufar, i Matthew R. Nassar. "Adaptive Learning through Temporal Dynamics of State Representation". Journal of Neuroscience 42, nr 12 (1.02.2022): 2524–38. http://dx.doi.org/10.1523/jneurosci.0387-21.2022.
Pełny tekst źródłaLiu, Qiyuan, Qi Zhou, Rui Yang i Jie Wang. "Robust Representation Learning by Clustering with Bisimulation Metrics for Visual Reinforcement Learning with Distractions". Proceedings of the AAAI Conference on Artificial Intelligence 37, nr 7 (26.06.2023): 8843–51. http://dx.doi.org/10.1609/aaai.v37i7.26063.
Pełny tekst źródłaJin, Xu, Teng Huang, Ke Wen, Mengxian Chi i Hong An. "HistoSSL: Self-Supervised Representation Learning for Classifying Histopathology Images". Mathematics 11, nr 1 (26.12.2022): 110. http://dx.doi.org/10.3390/math11010110.
Pełny tekst źródłaLuo, Dezhao, Chang Liu, Yu Zhou, Dongbao Yang, Can Ma, Qixiang Ye i Weiping Wang. "Video Cloze Procedure for Self-Supervised Spatio-Temporal Learning". Proceedings of the AAAI Conference on Artificial Intelligence 34, nr 07 (3.04.2020): 11701–8. http://dx.doi.org/10.1609/aaai.v34i07.6840.
Pełny tekst źródłaPark, Deog-Yeong, i Ki-Hoon Lee. "Practical Algorithmic Trading Using State Representation Learning and Imitative Reinforcement Learning". IEEE Access 9 (2021): 152310–21. http://dx.doi.org/10.1109/access.2021.3127209.
Pełny tekst źródłaChen, Hanxiao. "Robotic Manipulation with Reinforcement Learning, State Representation Learning, and Imitation Learning (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence 35, nr 18 (18.05.2021): 15769–70. http://dx.doi.org/10.1609/aaai.v35i18.17881.
Pełny tekst źródłaWang, Xingqi, Mengrui Zhang, Bin Chen, Dan Wei i Yanli Shao. "Dynamic Weighted Multitask Learning and Contrastive Learning for Multimodal Sentiment Analysis". Electronics 12, nr 13 (7.07.2023): 2986. http://dx.doi.org/10.3390/electronics12132986.
Pełny tekst źródłaRives, Alexander, Joshua Meier, Tom Sercu, Siddharth Goyal, Zeming Lin, Jason Liu, Demi Guo i in. "Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences". Proceedings of the National Academy of Sciences 118, nr 15 (5.04.2021): e2016239118. http://dx.doi.org/10.1073/pnas.2016239118.
Pełny tekst źródłaChang, Xinglong, Jianrong Wang, Rui Guo, Yingkui Wang i Weihao Li. "Asymmetric Graph Contrastive Learning". Mathematics 11, nr 21 (31.10.2023): 4505. http://dx.doi.org/10.3390/math11214505.
Pełny tekst źródłaXing, Jinwei, Takashi Nagata, Kexin Chen, Xinyun Zou, Emre Neftci i Jeffrey L. Krichmar. "Domain Adaptation In Reinforcement Learning Via Latent Unified State Representation". Proceedings of the AAAI Conference on Artificial Intelligence 35, nr 12 (18.05.2021): 10452–59. http://dx.doi.org/10.1609/aaai.v35i12.17251.
Pełny tekst źródłaZhu, Yi, Lei Li i Xindong Wu. "Stacked Convolutional Sparse Auto-Encoders for Representation Learning". ACM Transactions on Knowledge Discovery from Data 15, nr 2 (kwiecień 2021): 1–21. http://dx.doi.org/10.1145/3434767.
Pełny tekst źródłaWang, Sheng, Liyong Chen i Furong Peng. "Multiview Latent Representation Learning with Feature Diversity for Clustering". Mathematical Problems in Engineering 2022 (11.07.2022): 1–12. http://dx.doi.org/10.1155/2022/1866636.
Pełny tekst źródłaKeller, Patrick, Abdoul Kader Kaboré, Laura Plein, Jacques Klein, Yves Le Traon i Tegawendé F. Bissyandé. "What You See is What it Means! Semantic Representation Learning of Code based on Visualization and Transfer Learning". ACM Transactions on Software Engineering and Methodology 31, nr 2 (30.04.2022): 1–34. http://dx.doi.org/10.1145/3485135.
Pełny tekst źródłaSCARPETTA, SILVIA, ZHAOPING LI i JOHN HERTZ. "LEARNING IN AN OSCILLATORY CORTICAL MODEL". Fractals 11, supp01 (luty 2003): 291–300. http://dx.doi.org/10.1142/s0218348x03001951.
Pełny tekst źródłaZang, Hongyu, Xin Li i Mingzhong Wang. "SimSR: Simple Distance-Based State Representations for Deep Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 36, nr 8 (28.06.2022): 8997–9005. http://dx.doi.org/10.1609/aaai.v36i8.20883.
Pełny tekst źródłaZhu, Zixin, Le Wang, Wei Tang, Ziyi Liu, Nanning Zheng i Gang Hua. "Learning Disentangled Classification and Localization Representations for Temporal Action Localization". Proceedings of the AAAI Conference on Artificial Intelligence 36, nr 3 (28.06.2022): 3644–52. http://dx.doi.org/10.1609/aaai.v36i3.20277.
Pełny tekst źródłaZeng, Fanrui, Yingjie Sun i Yizhou Li. "MRLBot: Multi-Dimensional Representation Learning for Social Media Bot Detection". Electronics 12, nr 10 (19.05.2023): 2298. http://dx.doi.org/10.3390/electronics12102298.
Pełny tekst źródłaYang, Di, Yaohui Wang, Quan Kong, Antitza Dantcheva, Lorenzo Garattoni, Gianpiero Francesca i François Brémond. "Self-Supervised Video Representation Learning via Latent Time Navigation". Proceedings of the AAAI Conference on Artificial Intelligence 37, nr 3 (26.06.2023): 3118–26. http://dx.doi.org/10.1609/aaai.v37i3.25416.
Pełny tekst źródłaLi, Xiutian, Siqi Sun i Rui Feng. "Causal Representation Learning via Counterfactual Intervention". Proceedings of the AAAI Conference on Artificial Intelligence 38, nr 4 (24.03.2024): 3234–42. http://dx.doi.org/10.1609/aaai.v38i4.28108.
Pełny tekst źródłaKim, Jung-Hoon, Yizhen Zhang, Kuan Han, Zheyu Wen, Minkyu Choi i Zhongming Liu. "Representation learning of resting state fMRI with variational autoencoder". NeuroImage 241 (listopad 2021): 118423. http://dx.doi.org/10.1016/j.neuroimage.2021.118423.
Pełny tekst źródłaHumbert, Pierre, Clement Dubost, Julien Audiffren i Laurent Oudre. "Apprenticeship Learning for a Predictive State Representation of Anesthesia". IEEE Transactions on Biomedical Engineering 67, nr 7 (lipiec 2020): 2052–63. http://dx.doi.org/10.1109/tbme.2019.2954348.
Pełny tekst źródłaLiu, Feng, Ruiming Tang, Xutao Li, Weinan Zhang, Yunming Ye, Haokun Chen, Huifeng Guo, Yuzhou Zhang i Xiuqiang He. "State representation modeling for deep reinforcement learning based recommendation". Knowledge-Based Systems 205 (październik 2020): 106170. http://dx.doi.org/10.1016/j.knosys.2020.106170.
Pełny tekst źródłaMo, Yujie, Liang Peng, Jie Xu, Xiaoshuang Shi i Xiaofeng Zhu. "Simple Unsupervised Graph Representation Learning". Proceedings of the AAAI Conference on Artificial Intelligence 36, nr 7 (28.06.2022): 7797–805. http://dx.doi.org/10.1609/aaai.v36i7.20748.
Pełny tekst źródłaAchille, Alessandro, i Stefano Soatto. "A Separation Principle for Control in the Age of Deep Learning". Annual Review of Control, Robotics, and Autonomous Systems 1, nr 1 (28.05.2018): 287–307. http://dx.doi.org/10.1146/annurev-control-060117-105140.
Pełny tekst źródłaLi, Zhengyi, Menglu Li, Lida Zhu i Wen Zhang. "Improving PTM Site Prediction by Coupling of Multi-Granularity Structure and Multi-Scale Sequence Representation". Proceedings of the AAAI Conference on Artificial Intelligence 38, nr 1 (24.03.2024): 188–96. http://dx.doi.org/10.1609/aaai.v38i1.27770.
Pełny tekst źródłaGrigoryeva, Lyudmila, Allen Hart i Juan-Pablo Ortega. "Learning strange attractors with reservoir systems". Nonlinearity 36, nr 9 (27.07.2023): 4674–708. http://dx.doi.org/10.1088/1361-6544/ace492.
Pełny tekst źródłaKefato, Zekarias, i Sarunas Girdzijauskas. "Gossip and Attend: Context-Sensitive Graph Representation Learning". Proceedings of the International AAAI Conference on Web and Social Media 14 (26.05.2020): 351–59. http://dx.doi.org/10.1609/icwsm.v14i1.7305.
Pełny tekst źródłaBREEDEN, JOSEPH L., i NORMAN H. PACKARD. "A LEARNING ALGORITHM FOR OPTIMAL REPRESENTATION OF EXPERIMENTAL DATA". International Journal of Bifurcation and Chaos 04, nr 02 (kwiecień 1994): 311–26. http://dx.doi.org/10.1142/s0218127494000228.
Pełny tekst źródłaLiu, Shengli, Xiaowen Zhu, Zewei Cao i Gang Wang. "Deep 1D Landmark Representation Learning for Space Target Pose Estimation". Remote Sensing 14, nr 16 (18.08.2022): 4035. http://dx.doi.org/10.3390/rs14164035.
Pełny tekst źródłaZhang, Jingran, Xing Xu, Fumin Shen, Huimin Lu, Xin Liu i Heng Tao Shen. "Enhancing Audio-Visual Association with Self-Supervised Curriculum Learning". Proceedings of the AAAI Conference on Artificial Intelligence 35, nr 4 (18.05.2021): 3351–59. http://dx.doi.org/10.1609/aaai.v35i4.16447.
Pełny tekst źródłaHan, Ruijiang, Wei Wang, Yuxi Long i Jiajie Peng. "Deep Representation Debiasing via Mutual Information Minimization and Maximization (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence 36, nr 11 (28.06.2022): 12965–66. http://dx.doi.org/10.1609/aaai.v36i11.21619.
Pełny tekst źródłaLi, Fengpeng, Jiabao Li, Wei Han, Ruyi Feng i Lizhe Wang. "Unsupervised Representation High-Resolution Remote Sensing Image Scene Classification via Contrastive Learning Convolutional Neural Network". Photogrammetric Engineering & Remote Sensing 87, nr 8 (1.08.2021): 577–91. http://dx.doi.org/10.14358/pers.87.8.577.
Pełny tekst źródłaHallac, Ibrahim Riza, Betul Ay i Galip Aydin. "User Representation Learning for Social Networks: An Empirical Study". Applied Sciences 11, nr 12 (13.06.2021): 5489. http://dx.doi.org/10.3390/app11125489.
Pełny tekst źródłaLiu, Jiexi, i Songcan Chen. "TimesURL: Self-Supervised Contrastive Learning for Universal Time Series Representation Learning". Proceedings of the AAAI Conference on Artificial Intelligence 38, nr 12 (24.03.2024): 13918–26. http://dx.doi.org/10.1609/aaai.v38i12.29299.
Pełny tekst źródłaPerrinet, Laurent U. "Role of Homeostasis in Learning Sparse Representations". Neural Computation 22, nr 7 (lipiec 2010): 1812–36. http://dx.doi.org/10.1162/neco.2010.05-08-795.
Pełny tekst źródłaNaseem, Usman, Imran Razzak, Shah Khalid Khan i Mukesh Prasad. "A Comprehensive Survey on Word Representation Models: From Classical to State-of-the-Art Word Representation Language Models". ACM Transactions on Asian and Low-Resource Language Information Processing 20, nr 5 (23.06.2021): 1–35. http://dx.doi.org/10.1145/3434237.
Pełny tekst źródłaJanner, Michael, Karthik Narasimhan i Regina Barzilay. "Representation Learning for Grounded Spatial Reasoning". Transactions of the Association for Computational Linguistics 6 (grudzień 2018): 49–61. http://dx.doi.org/10.1162/tacl_a_00004.
Pełny tekst źródłaXu, Xiao, Chenfei Wu, Shachar Rosenman, Vasudev Lal, Wanxiang Che i Nan Duan. "BridgeTower: Building Bridges between Encoders in Vision-Language Representation Learning". Proceedings of the AAAI Conference on Artificial Intelligence 37, nr 9 (26.06.2023): 10637–47. http://dx.doi.org/10.1609/aaai.v37i9.26263.
Pełny tekst źródłaUmar Jamshaid, Umar Jamshaid. "Optimal Query Execution Plan with Deep Reinforcement Learning". International Journal for Electronic Crime Investigation 5, nr 3 (6.04.2022): 23–28. http://dx.doi.org/10.54692/ijeci.2022.050386.
Pełny tekst źródłaGuo, Jifeng, Zhiqi Pang, Wenbo Sun, Shi Li i Yu Chen. "Redundancy Removal Adversarial Active Learning Based on Norm Online Uncertainty Indicator". Computational Intelligence and Neuroscience 2021 (25.10.2021): 1–10. http://dx.doi.org/10.1155/2021/4752568.
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