Journal articles on the topic 'Multitask learning'
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Qiuhua Liu, Xuejun Liao, Hui Li, J. R. Stack, and L. Carin. "Semisupervised Multitask Learning." IEEE Transactions on Pattern Analysis and Machine Intelligence 31, no. 6 (June 2009): 1074–86. http://dx.doi.org/10.1109/tpami.2008.296.
Full textYang, Peng, Peilin Zhao, Jiayu Zhou, and Xin Gao. "Confidence Weighted Multitask Learning." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 5636–43. http://dx.doi.org/10.1609/aaai.v33i01.33015636.
Full textLi, Guangxia, Steven C. H. Hoi, Kuiyu Chang, Wenting Liu, and Ramesh Jain. "Collaborative Online Multitask Learning." IEEE Transactions on Knowledge and Data Engineering 26, no. 8 (August 2014): 1866–76. http://dx.doi.org/10.1109/tkde.2013.139.
Full textLi, Zhen Xing, and Wei Hua Li. "Multitask Similarity Cluster." Advanced Materials Research 765-767 (September 2013): 1662–66. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.1662.
Full textLi, Zhen Xing, and Wei Hua Li. "Multitask Fuzzy Learning with Rule Weight." Advanced Materials Research 774-776 (September 2013): 1883–86. http://dx.doi.org/10.4028/www.scientific.net/amr.774-776.1883.
Full textMenghi, Nicholas, Kemal Kacar, and Will Penny. "Multitask learning over shared subspaces." PLOS Computational Biology 17, no. 7 (July 6, 2021): e1009092. http://dx.doi.org/10.1371/journal.pcbi.1009092.
Full textKato, Tsuyoshi, Hisashi Kashima, Masashi Sugiyama, and Kiyoshi Asai. "Conic Programming for Multitask Learning." IEEE Transactions on Knowledge and Data Engineering 22, no. 7 (July 2010): 957–68. http://dx.doi.org/10.1109/tkde.2009.142.
Full textKong, Yu, Ming Shao, Kang Li, and Yun Fu. "Probabilistic Low-Rank Multitask Learning." IEEE Transactions on Neural Networks and Learning Systems 29, no. 3 (March 2018): 670–80. http://dx.doi.org/10.1109/tnnls.2016.2641160.
Full textYin, Jichong, Fang Wu, Yue Qiu, Anping Li, Chengyi Liu, and Xianyong Gong. "A Multiscale and Multitask Deep Learning Framework for Automatic Building Extraction." Remote Sensing 14, no. 19 (September 22, 2022): 4744. http://dx.doi.org/10.3390/rs14194744.
Full textSzyszkowska, Joanna, Anna Kinga Zduńczyk-Kłos, Antonina Doroszewska, Barbara Banaszczak, Milena Michalska, and Katarzyna Potocka. "Zdolność do skupienia uwagi i wielozadaniowości u studentów uczelni wyższych w okresie pandemicznej nauki na odległość." Kwartalnik Pedagogiczny 68, no. 3 (2023): 71–90. http://dx.doi.org/10.31338/2657-6007.kp.2023-3.4.
Full textSaylam, Berrenur, and Özlem Durmaz İncel. "Multitask Learning for Mental Health: Depression, Anxiety, Stress (DAS) Using Wearables." Diagnostics 14, no. 5 (February 26, 2024): 501. http://dx.doi.org/10.3390/diagnostics14050501.
Full textYu, Qingtian, Haopeng Wang, Fedwa Laamarti, and Abdulmotaleb El Saddik. "Deep Learning-Enabled Multitask System for Exercise Recognition and Counting." Multimodal Technologies and Interaction 5, no. 9 (September 8, 2021): 55. http://dx.doi.org/10.3390/mti5090055.
Full textSun, Kai, Richong Zhang, Samuel Mensah, Yongyi Mao, and 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, no. 15 (May 18, 2021): 13851–59. http://dx.doi.org/10.1609/aaai.v35i15.17632.
Full textSu, Fang, Hai-Yang Shang, and Jing-Yan Wang. "Low-Rank Deep Convolutional Neural Network for Multitask Learning." Computational Intelligence and Neuroscience 2019 (May 20, 2019): 1–10. http://dx.doi.org/10.1155/2019/7410701.
Full textKim, Hyuncheol, and Joonki Paik. "Low-Rank Representation-Based Object Tracking Using Multitask Feature Learning with Joint Sparsity." Abstract and Applied Analysis 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/147353.
Full textJaśkowski, Wojciech, Krzysztof Krawiec, and Bartosz Wieloch. "Multitask Visual Learning Using Genetic Programming." Evolutionary Computation 16, no. 4 (December 2008): 439–59. http://dx.doi.org/10.1162/evco.2008.16.4.439.
Full textSkolidis, Grigorios, and Guido Sanguinetti. "Semisupervised Multitask Learning With Gaussian Processes." IEEE Transactions on Neural Networks and Learning Systems 24, no. 12 (December 2013): 2101–12. http://dx.doi.org/10.1109/tnnls.2013.2272403.
Full textLi, Cong, Michael Georgiopoulos, and Georgios C. Anagnostopoulos. "Pareto-Path Multitask Multiple Kernel Learning." IEEE Transactions on Neural Networks and Learning Systems 26, no. 1 (January 2015): 51–61. http://dx.doi.org/10.1109/tnnls.2014.2309939.
Full textLee, Jeong Yoon, Youngmin Oh, Sung Shin Kim, Robert A. Scheidt, and Nicolas Schweighofer. "Optimal Schedules in Multitask Motor Learning." Neural Computation 28, no. 4 (April 2016): 667–85. http://dx.doi.org/10.1162/neco_a_00823.
Full textDahan, Elay, and Israel Cohen. "Deep-Learning-Based Multitask Ultrasound Beamforming." Information 14, no. 10 (October 23, 2023): 582. http://dx.doi.org/10.3390/info14100582.
Full textPan, Haixia, Yanan Li, Hongqiang Wang, and Xiaomeng Tian. "Railway Obstacle Intrusion Detection Based on Convolution Neural Network Multitask Learning." Electronics 11, no. 17 (August 28, 2022): 2697. http://dx.doi.org/10.3390/electronics11172697.
Full textZhang, Wenzheng, Chenyan Xiong, Karl Stratos, and Arnold Overwijk. "Improving Multitask Retrieval by Promoting Task Specialization." Transactions of the Association for Computational Linguistics 11 (2023): 1201–12. http://dx.doi.org/10.1162/tacl_a_00597.
Full textLi, Lu, Yongjiu Dai, Zhongwang Wei, Wei Shangguan, Yonggen Zhang, Nan Wei, and Qingliang Li. "Enforcing Water Balance in Multitask Deep Learning Models for Hydrological Forecasting." Journal of Hydrometeorology 25, no. 1 (January 2024): 89–103. http://dx.doi.org/10.1175/jhm-d-23-0073.1.
Full textWang, Xiaoqi, Yingjie Cheng, Yaning Yang, Yue Yu, Fei Li, and Shaoliang Peng. "Multitask joint strategies of self-supervised representation learning on biomedical networks for drug discovery." Nature Machine Intelligence 5, no. 4 (April 24, 2023): 445–56. http://dx.doi.org/10.1038/s42256-023-00640-6.
Full textForouzannezhad, Parisa, Dominic Maes, Daniel S. Hippe, Phawis Thammasorn, Reza Iranzad, Jie Han, Chunyan Duan, et al. "Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer." Cancers 14, no. 5 (February 26, 2022): 1228. http://dx.doi.org/10.3390/cancers14051228.
Full textWang, Yan, Lei Zhang, Lituan Wang, and Zizhou Wang. "Multitask Learning for Object Localization With Deep Reinforcement Learning." IEEE Transactions on Cognitive and Developmental Systems 11, no. 4 (December 2019): 573–80. http://dx.doi.org/10.1109/tcds.2018.2885813.
Full textTseng, Shao-Yen, Brian Baucom, and Panayiotis Georgiou. "Unsupervised online multitask learning of behavioral sentence embeddings." PeerJ Computer Science 5 (June 10, 2019): e200. http://dx.doi.org/10.7717/peerj-cs.200.
Full textZhang, Linjuan, Jiaqi Shi, Lili Wang, and Changqing Xu. "Electricity, Heat, and Gas Load Forecasting Based on Deep Multitask Learning in Industrial-Park Integrated Energy System." Entropy 22, no. 12 (November 30, 2020): 1355. http://dx.doi.org/10.3390/e22121355.
Full textLiu, Jiafei, Qingsong Wang, Jianda Cheng, Deliang Xiang, and Wenbo Jing. "Multitask Learning-Based for SAR Image Superpixel Generation." Remote Sensing 14, no. 4 (February 14, 2022): 899. http://dx.doi.org/10.3390/rs14040899.
Full textZheng, Weiping, Zhenyao Mo, and Gansen Zhao. "Clustering by Errors: A Self-Organized Multitask Learning Method for Acoustic Scene Classification." Sensors 22, no. 1 (December 22, 2021): 36. http://dx.doi.org/10.3390/s22010036.
Full textNimbal, Pratik, and Gopal Krishna Shyam. "Multitask sparse Learning based Facial Expression Classification." International Journal of Computer Sciences and Engineering 7, no. 6 (June 30, 2019): 197–202. http://dx.doi.org/10.26438/ijcse/v7i6.197202.
Full textYao, Chunhua, Xinyu Song, Xuelei Zhang, Weicheng Zhao, and Ao Feng. "Multitask Learning for Aspect-Based Sentiment Classification." Scientific Programming 2021 (November 29, 2021): 1–9. http://dx.doi.org/10.1155/2021/2055555.
Full textJin, Ran, Tengda Hou, Tongrui Yu, Min Luo, and Haoliang Hu. "A Multitask Deep Learning Framework for DNER." Computational Intelligence and Neuroscience 2022 (April 16, 2022): 1–10. http://dx.doi.org/10.1155/2022/3321296.
Full textXiong, Fangzhou, Biao Sun, Xu Yang, Hong Qiao, Kaizhu Huang, Amir Hussain, and Zhiyong Liu. "Guided Policy Search for Sequential Multitask Learning." IEEE Transactions on Systems, Man, and Cybernetics: Systems 49, no. 1 (January 2019): 216–26. http://dx.doi.org/10.1109/tsmc.2018.2800040.
Full textPillonetto, G., F. Dinuzzo, and G. De Nicolao. "Bayesian Online Multitask Learning of Gaussian Processes." IEEE Transactions on Pattern Analysis and Machine Intelligence 32, no. 2 (February 2010): 193–205. http://dx.doi.org/10.1109/tpami.2008.297.
Full textSingh, Loitongbam Gyanendro, Akash Anil, and Sanasam Ranbir Singh. "SHE: Sentiment Hashtag Embedding Through Multitask Learning." IEEE Transactions on Computational Social Systems 7, no. 2 (April 2020): 417–24. http://dx.doi.org/10.1109/tcss.2019.2962718.
Full textQian Xu, Sinno Jialin Pan, Hannah Hong Xue, and Qiang Yang. "Multitask Learning for Protein Subcellular Location Prediction." IEEE/ACM Transactions on Computational Biology and Bioinformatics 8, no. 3 (May 2011): 748–59. http://dx.doi.org/10.1109/tcbb.2010.22.
Full textGibert, Xavier, Vishal M. Patel, and Rama Chellappa. "Deep Multitask Learning for Railway Track Inspection." IEEE Transactions on Intelligent Transportation Systems 18, no. 1 (January 2017): 153–64. http://dx.doi.org/10.1109/tits.2016.2568758.
Full textHabic, Vuk, Alexander Semenov, and Eduardo L. Pasiliao. "Multitask deep learning for native language identification." Knowledge-Based Systems 209 (December 2020): 106440. http://dx.doi.org/10.1016/j.knosys.2020.106440.
Full textRamsundar, Bharath, Bowen Liu, Zhenqin Wu, Andreas Verras, Matthew Tudor, Robert P. Sheridan, and Vijay Pande. "Is Multitask Deep Learning Practical for Pharma?" Journal of Chemical Information and Modeling 57, no. 8 (August 2017): 2068–76. http://dx.doi.org/10.1021/acs.jcim.7b00146.
Full textYang, Haiqin, Michael R. Lyu, and Irwin King. "Efficient online learning for multitask feature selection." ACM Transactions on Knowledge Discovery from Data 7, no. 2 (July 2013): 1–27. http://dx.doi.org/10.1145/2499907.2499909.
Full textFujii, Keisuke, and Yoshinobu Kawahara. "Supervised dynamic mode decomposition via multitask learning." Pattern Recognition Letters 122 (May 2019): 7–13. http://dx.doi.org/10.1016/j.patrec.2019.02.010.
Full textLiu, Huaping, Fuchun Sun, and Yuanlong Yu. "Multitask Extreme Learning Machine for Visual Tracking." Cognitive Computation 6, no. 3 (January 8, 2014): 391–404. http://dx.doi.org/10.1007/s12559-013-9242-z.
Full textXu, Yong-Li, Di-Rong Chen, and Han-Xiong Li. "Least Square Regularized Regression for Multitask Learning." Abstract and Applied Analysis 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/715275.
Full textXu, Luhui, Jingying Chen, and Yanling Gan. "Head pose estimation using deep multitask learning." Journal of Electronic Imaging 28, no. 01 (February 7, 2019): 1. http://dx.doi.org/10.1117/1.jei.28.1.013029.
Full textDinuzzo, F., G. Pillonetto, and G. De Nicolao. "Client–Server Multitask Learning From Distributed Datasets." IEEE Transactions on Neural Networks 22, no. 2 (February 2011): 290–303. http://dx.doi.org/10.1109/tnn.2010.2095882.
Full textYang, Min, Wei Zhao, Wei Xu, Yabing Feng, Zhou Zhao, Xiaojun Chen, and Kai Lei. "Multitask Learning for Cross-Domain Image Captioning." IEEE Transactions on Multimedia 21, no. 4 (April 2019): 1047–61. http://dx.doi.org/10.1109/tmm.2018.2869276.
Full textLuo, Yong, Yonggang Wen, and Dacheng Tao. "Heterogeneous Multitask Metric Learning Across Multiple Domains." IEEE Transactions on Neural Networks and Learning Systems 29, no. 9 (September 2018): 4051–64. http://dx.doi.org/10.1109/tnnls.2017.2750321.
Full textZhao, Qian, Xiangyu Rui, Zhi Han, and Deyu Meng. "Multilinear Multitask Learning by Rank-Product Regularization." IEEE Transactions on Neural Networks and Learning Systems 31, no. 4 (April 2020): 1336–50. http://dx.doi.org/10.1109/tnnls.2019.2919774.
Full textSu, Jing, Yafei Yuan, Chunmin Liu, and Jing Li. "Multitask Learning by Multiwave Optical Diffractive Network." Mathematical Problems in Engineering 2020 (July 10, 2020): 1–7. http://dx.doi.org/10.1155/2020/9748380.
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