Artículos de revistas sobre el tema "Task-specific representation learnining"
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Wang, Chaoqun, Xuejin Chen, Shaobo Min, Xiaoyan Sun y Houqiang Li. "Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 3 (18 de mayo de 2021): 2710–18. http://dx.doi.org/10.1609/aaai.v35i3.16375.
Texto completoLi, Yingcong y Samet Oymak. "Provable Pathways: Learning Multiple Tasks over Multiple Paths". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 7 (26 de junio de 2023): 8701–10. http://dx.doi.org/10.1609/aaai.v37i7.26047.
Texto completoWang, Gerui y Sheng Tang. "Generalized Zero-Shot Image Classification via Partially-Shared Multi-Task Representation Learning". Electronics 12, n.º 9 (3 de mayo de 2023): 2085. http://dx.doi.org/10.3390/electronics12092085.
Texto completoBasu Roy Chowdhury, Somnath y Snigdha Chaturvedi. "Sustaining Fairness via Incremental Learning". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 6 (26 de junio de 2023): 6797–805. http://dx.doi.org/10.1609/aaai.v37i6.25833.
Texto completoDavvetas, Athanasios, Iraklis A. Klampanos, Spiros Skiadopoulos y Vangelis Karkaletsis. "Evidence Transfer: Learning Improved Representations According to External Heterogeneous Task Outcomes". ACM Transactions on Knowledge Discovery from Data 16, n.º 5 (31 de octubre de 2022): 1–22. http://dx.doi.org/10.1145/3502732.
Texto completoKonidaris, George, Leslie Pack Kaelbling y Tomas Lozano-Perez. "From Skills to Symbols: Learning Symbolic Representations for Abstract High-Level Planning". Journal of Artificial Intelligence Research 61 (31 de enero de 2018): 215–89. http://dx.doi.org/10.1613/jair.5575.
Texto completoGu, Jie, Feng Wang, Qinghui Sun, Zhiquan Ye, Xiaoxiao Xu, Jingmin Chen y Jun Zhang. "Exploiting Behavioral Consistence for Universal User Representation". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 5 (18 de mayo de 2021): 4063–71. http://dx.doi.org/10.1609/aaai.v35i5.16527.
Texto completoYu, Wenmeng, Hua Xu, Ziqi Yuan y Jiele Wu. "Learning Modality-Specific Representations with Self-Supervised Multi-Task Learning for Multimodal Sentiment Analysis". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 12 (18 de mayo de 2021): 10790–97. http://dx.doi.org/10.1609/aaai.v35i12.17289.
Texto completoAhmed, Mahtab y Robert E. Mercer. "Modelling Sentence Pairs via Reinforcement Learning: An Actor-Critic Approach to Learn the Irrelevant Words". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 05 (3 de abril de 2020): 7358–66. http://dx.doi.org/10.1609/aaai.v34i05.6230.
Texto completoMehmood, Tahir, Ivan Serina, Alberto Lavelli, Luca Putelli y Alfonso Gerevini. "On the Use of Knowledge Transfer Techniques for Biomedical Named Entity Recognition". Future Internet 15, n.º 2 (17 de febrero de 2023): 79. http://dx.doi.org/10.3390/fi15020079.
Texto completoJeannerod, M. "The representing brain: Neural correlates of motor intention and imagery". Behavioral and Brain Sciences 17, n.º 2 (junio de 1994): 187–202. http://dx.doi.org/10.1017/s0140525x00034026.
Texto completoChen, Yuhao, Alexander Wong, Yuan Fang, Yifan Wu y Linlin Xu. "Deep Residual Transform for Multi-scale Image Decomposition". Journal of Computational Vision and Imaging Systems 6, n.º 1 (15 de enero de 2021): 1–5. http://dx.doi.org/10.15353/jcvis.v6i1.3537.
Texto completoLu, Su, Han-Jia Ye y De-Chuan Zhan. "Tailoring Embedding Function to Heterogeneous Few-Shot Tasks by Global and Local Feature Adaptors". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 10 (18 de mayo de 2021): 8776–83. http://dx.doi.org/10.1609/aaai.v35i10.17063.
Texto completoZhang, Yu y Dit-Yan Yeung. "Multi-Task Learning in Heterogeneous Feature Spaces". Proceedings of the AAAI Conference on Artificial Intelligence 25, n.º 1 (4 de agosto de 2011): 574–79. http://dx.doi.org/10.1609/aaai.v25i1.7909.
Texto completoXu, Huatao, Pengfei Zhou, Rui Tan, Mo Li y Guobin Shen. "LIMU-BERT". GetMobile: Mobile Computing and Communications 26, n.º 3 (7 de octubre de 2022): 39–42. http://dx.doi.org/10.1145/3568113.3568124.
Texto completoJha, Ritesh, Vandana Bhattacharjee y Abhijit Mustafi. "Transfer Learning with Feature Extraction Modules for Improved Classifier Performance on Medical Image Data". Scientific Programming 2022 (23 de agosto de 2022): 1–10. http://dx.doi.org/10.1155/2022/4983174.
Texto completoAnam, Mamoona, Dr Kantilal P. Rane, Ali Alenezi, Ruby Mishra, Dr Swaminathan Ramamurthy y Ferdin Joe John Joseph. "Content Classification Tasks with Data Preprocessing Manifestations". Webology 19, n.º 1 (20 de enero de 2022): 1413–30. http://dx.doi.org/10.14704/web/v19i1/web19094.
Texto completoYuan, Zixuan, Hao Liu, Renjun Hu, Denghui Zhang y Hui Xiong. "Self-Supervised Prototype Representation Learning for Event-Based Corporate Profiling". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 5 (18 de mayo de 2021): 4644–52. http://dx.doi.org/10.1609/aaai.v35i5.16594.
Texto completoHeyes, C. M. y C. L. Foster. "Motor learning by observation: Evidence from a serial reaction time task". Quarterly Journal of Experimental Psychology Section A 55, n.º 2 (abril de 2002): 593–607. http://dx.doi.org/10.1080/02724980143000389.
Texto completoNishida, Satoshi, Yusuke Nakano, Antoine Blanc, Naoya Maeda, Masataka Kado y Shinji Nishimoto. "Brain-Mediated Transfer Learning of Convolutional Neural Networks". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 04 (3 de abril de 2020): 5281–88. http://dx.doi.org/10.1609/aaai.v34i04.5974.
Texto completoRAJENDRAN, SRIVIDHYA y MANFRED HUBER. "LEARNING TASK-SPECIFIC SENSING, CONTROL AND MEMORY POLICIES". International Journal on Artificial Intelligence Tools 14, n.º 01n02 (febrero de 2005): 303–27. http://dx.doi.org/10.1142/s0218213005002119.
Texto completoSun, Kai, Richong Zhang, Samuel Mensah, Yongyi Mao y Xudong Liu. "Progressive Multi-task Learning with Controlled Information Flow for Joint Entity and Relation Extraction". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 15 (18 de mayo de 2021): 13851–59. http://dx.doi.org/10.1609/aaai.v35i15.17632.
Texto completoZhao, Jiabao, Yifan Yang, Xin Lin, Jing Yang y Liang He. "Looking Wider for Better Adaptive Representation in Few-Shot Learning". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 12 (18 de mayo de 2021): 10981–89. http://dx.doi.org/10.1609/aaai.v35i12.17311.
Texto completoKumar, Sajit, Alicia Nanelia, Ragunathan Mariappan, Adithya Rajagopal y Vaibhav Rajan. "Patient Representation Learning From Heterogeneous Data Sources and Knowledge Graphs Using Deep Collective Matrix Factorization: Evaluation Study". JMIR Medical Informatics 10, n.º 1 (20 de enero de 2022): e28842. http://dx.doi.org/10.2196/28842.
Texto completoGong, Letian, Youfang Lin, Shengnan Guo, Yan Lin, Tianyi Wang, Erwen Zheng, Zeyu Zhou y Huaiyu Wan. "Contrastive Pre-training with Adversarial Perturbations for Check-In Sequence Representation Learning". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 4 (26 de junio de 2023): 4276–83. http://dx.doi.org/10.1609/aaai.v37i4.25546.
Texto completoLu, Yuxun y Ryutaro Ichise. "ProtoE: Enhancing Knowledge Graph Completion Models with Unsupervised Type Representation Learning". Information 13, n.º 8 (25 de julio de 2022): 354. http://dx.doi.org/10.3390/info13080354.
Texto completoQin, Libo, Fuxuan Wei, Minheng Ni, Yue Zhang, Wanxiang Che, Yangming Li y Ting Liu. "Multi-domain Spoken Language Understanding Using Domain- and Task-aware Parameterization". ACM Transactions on Asian and Low-Resource Language Information Processing 21, n.º 4 (31 de julio de 2022): 1–17. http://dx.doi.org/10.1145/3502198.
Texto completoReinert, Sandra, Mark Hübener, Tobias Bonhoeffer y Pieter M. Goltstein. "Mouse prefrontal cortex represents learned rules for categorization". Nature 593, n.º 7859 (21 de abril de 2021): 411–17. http://dx.doi.org/10.1038/s41586-021-03452-z.
Texto completoJung, Jinhong, Jaemin Yoo y U. Kang. "Signed random walk diffusion for effective representation learning in signed graphs". PLOS ONE 17, n.º 3 (17 de marzo de 2022): e0265001. http://dx.doi.org/10.1371/journal.pone.0265001.
Texto completoChambers, Claire, Hugo Fernandes y Konrad Paul Kording. "Policies or knowledge: priors differ between a perceptual and sensorimotor task". Journal of Neurophysiology 121, n.º 6 (1 de junio de 2019): 2267–75. http://dx.doi.org/10.1152/jn.00035.2018.
Texto completoRusso, Alessio y Alexandre Proutiere. "On the Sample Complexity of Representation Learning in Multi-Task Bandits with Global and Local Structure". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 8 (26 de junio de 2023): 9658–67. http://dx.doi.org/10.1609/aaai.v37i8.26155.
Texto completoLiu, Fenglin, Xian Wu, Shen Ge, Wei Fan y Yuexian Zou. "Federated Learning for Vision-and-Language Grounding Problems". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 07 (3 de abril de 2020): 11572–79. http://dx.doi.org/10.1609/aaai.v34i07.6824.
Texto completoAnderson, Brian A. y Haena Kim. "On the representational nature of value-driven spatial attentional biases". Journal of Neurophysiology 120, n.º 5 (1 de noviembre de 2018): 2654–58. http://dx.doi.org/10.1152/jn.00489.2018.
Texto completoWang, Zhongming, Jiahui Dong, Lianlian Wu, Chong Dai, Jing Wang, Yuqi Wen, Yixin Zhang, Xiaoxi Yang, Song He y Xiaochen Bo. "DEML: Drug Synergy and Interaction Prediction Using Ensemble-Based Multi-Task Learning". Molecules 28, n.º 2 (14 de enero de 2023): 844. http://dx.doi.org/10.3390/molecules28020844.
Texto completoSong, Kaisong, Yangyang Kang, Jiawei Liu, Xurui Li, Changlong Sun y Xiaozhong Liu. "A Speaker Turn-Aware Multi-Task Adversarial Network for Joint User Satisfaction Estimation and Sentiment Analysis". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 11 (26 de junio de 2023): 13582–90. http://dx.doi.org/10.1609/aaai.v37i11.26592.
Texto completoLeón, Fabian y Fabio Martínez. "A multitask deep representation for Gleason score classification to support grade annotations". Biomedical Physics & Engineering Express 8, n.º 3 (8 de abril de 2022): 035021. http://dx.doi.org/10.1088/2057-1976/ac60c4.
Texto completoXu, Yao, Xueshuang Xiang y Meiyu Huang. "Task-Driven Common Representation Learning via Bridge Neural Network". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 de julio de 2019): 5573–80. http://dx.doi.org/10.1609/aaai.v33i01.33015573.
Texto completoTrofimov, Assya, Joseph Paul Cohen, Yoshua Bengio, Claude Perreault y Sébastien Lemieux. "Factorized embeddings learns rich and biologically meaningful embedding spaces using factorized tensor decomposition". Bioinformatics 36, Supplement_1 (1 de julio de 2020): i417—i426. http://dx.doi.org/10.1093/bioinformatics/btaa488.
Texto completoZhang, Liyi, Zengguang Tian, Yi Tang y Zuo Jiang. "Task-Covariant Representations for Few-Shot Learning on Remote Sensing Images". Mathematics 11, n.º 8 (19 de abril de 2023): 1930. http://dx.doi.org/10.3390/math11081930.
Texto completoDUNN, JONATHAN. "Computational learning of construction grammars". Language and Cognition 9, n.º 2 (28 de marzo de 2016): 254–92. http://dx.doi.org/10.1017/langcog.2016.7.
Texto completoGuo, Yiyou y Chao Wei. "Multi-Task Learning Using Gradient Balance and Clipping with an Application in Joint Disparity Estimation and Semantic Segmentation". Electronics 11, n.º 8 (12 de abril de 2022): 1217. http://dx.doi.org/10.3390/electronics11081217.
Texto completoLampinen, Andrew K. y James L. McClelland. "Transforming task representations to perform novel tasks". Proceedings of the National Academy of Sciences 117, n.º 52 (10 de diciembre de 2020): 32970–81. http://dx.doi.org/10.1073/pnas.2008852117.
Texto completoSitaula, Chiranjibi, Anish Basnet y Sunil Aryal. "Vector representation based on a supervised codebook for Nepali documents classification". PeerJ Computer Science 7 (3 de marzo de 2021): e412. http://dx.doi.org/10.7717/peerj-cs.412.
Texto completoJaiswal, Mimansa y Emily Mower Provost. "Privacy Enhanced Multimodal Neural Representations for Emotion Recognition". Proceedings of the AAAI Conference on Artificial Intelligence 34, n.º 05 (3 de abril de 2020): 7985–93. http://dx.doi.org/10.1609/aaai.v34i05.6307.
Texto completoCerda, Vanessa R., Paola Montufar Soria y Nicole Y. Wicha. "Reevaluating the Language of Learning Advantage in Bilingual Arithmetic: An ERP Study on Spoken Multiplication Verification". Brain Sciences 12, n.º 5 (21 de abril de 2022): 532. http://dx.doi.org/10.3390/brainsci12050532.
Texto completoLu, Wenpeng, Rui Yu, Shoujin Wang, Can Wang, Ping Jian y Heyan Huang. "Sentence Semantic Matching Based on 3D CNN for Human–Robot Language Interaction". ACM Transactions on Internet Technology 21, n.º 4 (16 de julio de 2021): 1–24. http://dx.doi.org/10.1145/3450520.
Texto completoZeng, Te y Francis C. M. Lau. "Automatic Melody Harmonization via Reinforcement Learning by Exploring Structured Representations for Melody Sequences". Electronics 10, n.º 20 (11 de octubre de 2021): 2469. http://dx.doi.org/10.3390/electronics10202469.
Texto completoClegg, Benjamin A. "Stimulus-Specific Sequence Representation in Serial Reaction Time Tasks". Quarterly Journal of Experimental Psychology Section A 58, n.º 6 (agosto de 2005): 1087–101. http://dx.doi.org/10.1080/02724980443000485.
Texto completoVangheluwe, Sophie, Nicole Wenderoth y Stephan P. Swinnen. "Learning and Transfer of an Ipsilateral Coordination Task: Evidence for a Dual-layer Movement Representation". Journal of Cognitive Neuroscience 17, n.º 9 (septiembre de 2005): 1460–70. http://dx.doi.org/10.1162/0898929054985392.
Texto completoChen, Chen, Yuchen Hu, Qiang Zhang, Heqing Zou, Beier Zhu y Eng Siong Chng. "Leveraging Modality-Specific Representations for Audio-Visual Speech Recognition via Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 37, n.º 11 (26 de junio de 2023): 12607–15. http://dx.doi.org/10.1609/aaai.v37i11.26484.
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