Multitask Learning

Cited by (1,024)

Items 301–400 of 1,024

1. Multiscale Feature-Clustering-Based Fully Convolutional Autoencoder for Fast Accurate Visual Inspection of Texture Surface Defects
   Hua Shu Yang, Yifan Chen, Kaiyou Song, Zhouping Yin · 2019 · IEEE Transactions on Automation Science and Engineering
2. Adaptive Extreme Edge Computing for Wearable Devices
   Erika Covi, Elisa Donati, Xiangpeng Liang, David Kappel, Hadi Heidari, Melika Payvand, Wei Juan Wang · 2021 · Frontiers in Neuroscience
3. A Survey on Active Learning: State-of-the-Art, Practical Challenges and Research Directions
   Alaa Tharwat, Wolfram Schenck · 2023 · Mathematics
4. Learning Graph Embeddings for Compositional Zero-shot Learning
   Muhammad Ferjad Naeem, Yongqin Xian, Federico Tombari, Zeynep Akata · 2021 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
5. Modeling multiple land use changes using ANN, CART and MARS: Comparing tradeoffs in goodness of fit and explanatory power of data mining tools
   Amin Tayyebi, Bryan Christopher Pijanowski · 2013 · International Journal of Applied Earth Observation and Geoinformation
6. Reinforcement Learning with Tree-LSTM for Join Order Selection
   Xiang Yu, Guoliang Li, Chengliang Chai, Nan Tang · 2020 · IEEE International Conference on Data Engineering (ICDE)
7. Machine Learning in Polymer Research
   Wei Chun Ge, Ramindu De Silva, Yanan Fan, Scott A. Sisson, Martina H. Stenzel · 2025 · Advanced Materials
8. Skin disease diagnosis with deep learning: a review
   Li, Hongfeng, Pan, Yini, Zhao, Jie, Zhang, Li · 2021 · Neurocomputing
9. A Residual Based Attention Model for EEG Based Sleep Staging
   Wei Qu, Zhiyong Wang, Hong Hong, Zheru Chi, Dagan D. Feng, Ronald R. Grunstein, Christopher James Gordon · 2020 · IEEE Journal of Biomedical and Health Informatics
10. Heterogeneous transfer learning for image clustering via the social web
    Qiang Yang, Yuqiang Chen, Gui-Rong Xue, Wenyuan Dai, Yong Hai Yu · 2009
11. Neural End-to-End Learning for Computational Argumentation Mining
    Steffen Eger, Johannes Daxenberger, Iryna Gurevych · 2017 · Proceedings of the conference - Association for Computational Linguistics. Meeting
12. Adversarial Multi-Criteria Learning for Chinese Word Segmentation
    Xinchi Chen, Zhan Shi, Xipeng Qiu, Xuanjing Huang · 2017 · Proceedings of the conference - Association for Computational Linguistics. Meeting
13. A theory of transfer learning with applications to active learning
    Lin Forrest Yang, Steve Hanneke, Jaime Carbonell · 2012 · Machine Learning
14. A comprehensive review of deep learning-based single image super-resolution
    Syed Muhammad Arsalan Bashir, Yi Wang, Mahrukh Khan, Yilong Niu · 2021 · PeerJ Computer Science · Retracted
15. Storm-Based Probabilistic Hail Forecasting with Machine Learning Applied to Convection-Allowing Ensembles
    Gagne, David John, McGovern, Amy, Haupt, Sue Ellen, Sobash, Ryan A., Williams, John K., Xue, Ming · 2017 · Weather and Forecasting
16. Poly-encoders: Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring
    Samuel Humeau, Kurt Shuster, Marie-Anne Lachaux, Jason Weston · 2020 · International Conference on Learning Representations
17. Gene Expression Programming: A Survey [Review Article]
    Jinghui Zhong, Liang Feng, Yew-Soon Ong · 2017 · IEEE Computational Intelligence Magazine
18. . Hyper-class augmented and regularized deep learning for fine-grained image classification
    Xie, Saining, Yang, Tianbao, Xiaoyu Wang, Yuanqing Lin · 2015 · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
19. Transfer learning in heterogeneous collaborative filtering domains
    Weike Pan, Qiang Yang · 2013 · Artificial Intelligence
20. Multi-Source Domain Adaptation with Mixture of Experts
    Guo, Jiang, Shah, Darsh, Barzilay, Regina · 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
21. Multitask Air-Quality Prediction Based on LSTM-Autoencoder Model
    Xinghan Xu, Minoru Yoneda · 2019 · IEEE Transactions on Cybernetics
22. Extending machine learning beyond interatomic potentials for predicting molecular properties
    Nikita S. Fedik, R.I. Zubatyuk, Maksim Kulichenko, Nicholas Lubbers, Justin S. Smith, Benjamin T. Nebgen, Richard A. Messerly, Ying Wai Li, Alexander I. Boldyrev, Kipton M. Barros et al. · 2022 · Nature Reviews Chemistry
23. Multifactorial Genetic Programming for Symbolic Regression Problems
    Jinghui Zhong, Liang Feng, Wentong Cai, Yew-Soon Ong · 2018 · IEEE Transactions on Systems Man and Cybernetics Systems
24. Learning a Fixed-Length Fingerprint Representation
    Joshua J. Engelsma, Kai Cao, Anil K. Jain · 2019 · IEEE Transactions on Pattern Analysis and Machine Intelligence
25. An evaluation of machine-learning for predicting phenotype: studies in yeast, rice, and wheat
    Nastasiya F. Grinberg, Oghenejokpeme I. Orhobor, Ross D. King · 2019 · Machine Learning
26. Recall and Learn: Fine-tuning Deep Pretrained Language Models with Less Forgetting
    Sanyuan Chen, Yutai Hou, Yiming Cui, Wanxiang Che, Ting Liu, Xiangzhan Yu · 2020 · Conference on Empirical Methods in Natural Language Processing (EMNLP)
27. Learning With Case-Injected Genetic Algorithms
    Sushil J. Louis, John R. McDonnell · 2004 · IEEE Transactions on Evolutionary Computation
28. Learning a meta-level prior for feature relevance from multiple related tasks
    Su‐In Lee, Vassil Chatalbashev, David Vickrey, Daphne Koller · 2007 · International Conference on Machine Learning
29. Comprehensive strategies of machine-learning-based quantitative structure-activity relationship models
    Jiashun Mao, Javed Akhtar, Xiao Zhang, Liang Sun, Shenghui Guan, Xinyu Li, Guangming Chen, Jiaxin Liu, Hyeon-Nae Jeon, Min Sung Kim et al. · 2021 · iScience
30. Reinforcement learning to adjust parametrized motor primitives to new situations
    Jens Kober, Andreas Wilhelm, Erhan Öztop, Jan Peters · 2012 · Autonomous Robots
31. Hierarchical Bayesian domain adaptation
    Jenny Rose Finkel, Christopher D. Manning · 2009 · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT)
32. Yum-Me
    Longqi Yang, Cheng-Kang Hsieh, Hongjian Yang, John P. Pollak, Nicola Lee Dell, Serge Belongie, Curtis L. Cole, Deborah L. Estrin · 2017 · ACM Transactions on Information Systems
33. Personality-Assisted Multi-Task Learning for Generic and Personalized Image Aesthetics Assessment
    Leida Li, Hancheng Zhu, Sicheng Zhao, Guiguang Ding, Weisi Lin · 2020 · IEEE Transactions on Image Processing
34. A Survey of Multi-Task Deep Reinforcement Learning
    Nelson Vithayathil Varghese, Qusay H. Mahmoud · 2020 · Electronics
35. Lifelong Learning for Sentiment Classification
    Zhiyuan Chen, Nianzu Ma, Bing Liu · 2015
36. Loss of plasticity in deep continual learning
    Dohare, Shibhansh, Hernandez-Garcia, J. Fernando, Lan, Qingfeng, Rahman, Parash, Mahmood, A. Rupam, Sutton, Richard S. · 2024 · Nature
37. COMPOSE: A Semisupervised Learning Framework for Initially Labeled Nonstationary Streaming Data
    Karl B. Dyer, Robert Capo, Robi Polikar A · 2013 · IEEE Transactions on Neural Networks and Learning Systems
38. Reinforcement Learning to adjust Robot Movements to New Situations
    Jens Kober, Erhan Öztop, Jan Peters · 2010 · Robotics: Science and Systems
39. Healthcare Predictive Analytics for Risk Profiling in Chronic Care: A Bayesian Multitask Learning Approach1
    Yu-Kai Lin, Hsinchun Chen, Randall A. Brown, Shu‐Hsing Li, Hung‐Jen Yang · 2017 · MIS Quarterly
40. Dynamic Feature Integration for Simultaneous Detection of Salient Object, Edge, and Skeleton
    Jiangjiang Liu, Qibin Hou, Ming‐Ming Cheng · 2020 · IEEE Transactions on Image Processing
41. An overview of deep learning methods for multimodal medical data mining
    Fatemeh Behrad, Mohammad Saniee Abadeh · 2022 · Expert Systems with Applications
42. SVMs Classification Based Two-side Cross Domain Collaborative Filtering by inferring intrinsic user and item features
    Xu Yu, Yan Chu, Feng Xian Jiang, Ying Guo, Dunwei Gong · 2017 · Knowledge-Based Systems
43. Towards Robust Pattern Recognition: A Review
    Xu-Yao Zhang, Cheng‐Lin Liu, Ching Y. Suen · 2020 · Proceedings of the IEEE
44. A systematic review of federated learning: Challenges, aggregation methods, and development tools
    Souhila Badra Guendouzi, Samir Ouchani, Hiba El Assaad, Madeleine El Zaher · 2023 · Journal of Network and Computer Applications
45. Poly-encoders: Transformer Architectures and Pre-training Strategies for Fast and Accurate Multi-sentence Scoring
    Samuel Humeau, Kurt Shuster, Marie-Anne Lachaux, Jason Weston · 2019 · arXiv (Cornell University)
46. Learning the Shared Subspace for Multi-task Clustering and Transductive Transfer Classification
    Quanquan Gu, Jie Zhou · 2009 · Proceedings
47. Reinforcement Learning and Deep Learning Based Lateral Control for Autonomous Driving [Application Notes]
    Dong Li, Dongbin Zhao, Qichao Zhang, Yaran Chen · 2019 · IEEE Computational Intelligence Magazine
48. Towards Adversarially Robust Object Detection
    Haichao Zhang, Jianyu Wang · 2019 · IEEE/CVF International Conference on Computer Vision (ICCV)
49. Exploring Inter-feature and Inter-class Relationships with Deep Neural Networks for Video Classification
    Zuxuan Wu, Yu–Gang Jiang, Jun Wang, Jian Pu, Xiangyang Xue · 2014 · ACM International Conference on Multimedia (ACM MM)
50. CollaboNet: collaboration of deep neural networks for biomedical named entity recognition
    Wonjin Yoon, Chan Ho So, Jinhyuk Lee, Jaewoo Kang · 2019 · BMC Bioinformatics
51. A survey of recommender systems with multi-objective optimization
    Yong Zheng, David (Xuejun) Wang · 2021 · Neurocomputing
52. Domain Generalization by Marginal Transfer Learning
    Gilles Blanchard, Aniket Anand Deshmukh, Ürün Doǧan, Gyemin Lee, Clayton D. Scott · 2017 · arXiv (Cornell University)
53. Object Recognition in 3D Point Clouds Using Web Data and Domain Adaptation
    Lai, Kevin, Fox, Dieter · 2010 · The International Journal of Robotics Research
54. LUVLi Face Alignment: Estimating Landmarks’ Location, Uncertainty, and Visibility Likelihood
    Kumar, Abhinav, Marks, Tim K., Mou, Wenxuan, Wang, Ye, Jones, Michael, Cherian, Anoop, Koike-Akino, Toshiaki, Liu, Xiaoming, Feng, Chen · 2020 · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
55. Multi-target support vector regression via correlation regressor chains
    Gabriella Melki, Alberto Cano, Vojislav Kecman, Sebastián Ventura · 2017 · Information Sciences
56. Egocentric Daily Activity Recognition via Multitask Clustering
    Yan Yan, Elisa Ricci, Gaowen Liu, Nicu Sebe · 2015 · IEEE Transactions on Image Processing
57. Deep Learning Methods and Applications
    Jamil Ahmad, Haleem Farman, Zahoor Jan · 2018 · SpringerBriefs in computer science
58. A comprehensive overview of knowledge graph completion
    Tong Shen, Fu Zhang, Jingwei Cheng · 2022 · Knowledge-Based Systems
59. Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
    Amr AbdelFatah Ahmed, Kai Yu, Wei Hong Xu, Yihong Gong, Eric P. Xing · 2008 · Lecture notes in computer science
60. Transferring Knowledge of Activity Recognition across Sensor Networks
    Tim L. M. van Kasteren, Gwenn Englebienne, Ben Kröse · 2010 · Lecture notes in computer science
61. Semi-supervised multi-task learning for predicting interactions between HIV-1 and human proteins
    Yanjun Qi, Öznur Taştan, Jaime G. Carbonell, Judith Klein‐Seetharaman, Jason Weston · 2010 · Bioinformatics
62. One model is all you need: Multi-task learning enables simultaneous histology image segmentation and classification
    Simon Graham, Quoc Dang Vu, Mostafa Jahanifar, Shan E Ahmed Raza, Fayyaz Minhas, David R. J. Snead, Nasir Rajpoot · 2022 · Medical Image Analysis
63. Improving Multi-Task Deep Neural Networks via Knowledge Distillation for Natural Language Understanding
    Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao · 2019 · arXiv (Cornell University)
64. Attributes for Improved Attributes: A Multi-Task Network Utilizing Implicit and Explicit Relationships for Facial Attribute Classification
    Emily Hand, Rama Chellappa · 2017 · Proceedings of the AAAI Conference on Artificial Intelligence
65. Learning Sparse Sharing Architectures for Multiple Tasks
    Tianxiang Sun, Yunfan Shao, Xiaonan Li, Pengfei Liu, Hang Rui Yan, Xipeng Qiu, Xuanjing Huang · 2020 · Proceedings of the AAAI Conference on Artificial Intelligence
66. Generalized Zero-Shot Learning via Over-Complete Distribution
    Rohit Keshari, Richa Singh, Mayank Vatsa A · 2020 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
67. State-of-Health Estimation for Lithium-Ion Batteries Using Domain Adversarial Transfer Learning
    Zhuang Ye, Jianbo Yu · 2021 · IEEE Transactions on Power Electronics
68. Feature-Level Attention-Guided Multitask CNN for Fault Diagnosis and Working Conditions Identification of Rolling Bearing
    Huan Wang, Zhiliang Liu, Dandan Peng, Mei Yang, Yong Qin · 2021 · IEEE Transactions on Neural Networks and Learning Systems
69. Fast-adapting and privacy-preserving federated recommender system
    Qinyong Wang, Hongzhi Yin, Tong Chen, Junliang Yu, Alexander Zhou, Xiangliang Zhang · 2021 · The VLDB Journal
70. Emerging trends in federated learning: from model fusion to federated X learning
    Shaoxiong Ji, Yue Tan, Teemu Saravirta, Z. Q. Yang, Yixin Liu, Lauri Vasankari, Shirui Pan, Guodong Long, Anwar Walid · 2024 · International Journal of Machine Learning and Cybernetics
71. From Audio to Semantics: Approaches to End-to-End Spoken Language Understanding
    Parisa Haghani, Arun Narayanan, Michiel Bacchiani, Galen Chuang, Neeraj Gaur, Pedro J. Moreno, Rohit Prabhavalkar, Zhongdi Qu, Austin Waters · 2018 · IEEE Spoken Language Technology Workshop (SLT)
72. Deep Learning and Virtual Drug Screening
    Kristy A. Carpenter, David S Cohen, Juliet T. Jarrell, Xudong Huang · 2018 · Future Medicinal Chemistry
73. Deep Multitask Learning for Semantic Dependency Parsing
    Hao Peng, Sam Thomson, Noah A. Smith · 2017 · Proceedings of the conference - Association for Computational Linguistics. Meeting
74. A large and rich EEG dataset for modeling human visual object recognition
    Alessandro T. Gifford, Kshitij Dwivedi, Gemma Roig, Radoslaw Martin Cichy · 2022 · NeuroImage
75. Multitask TSK Fuzzy System Modeling by Mining Intertask Common Hidden Structure
    Yizhang Jiang, Fu-Lai Chung, Hisao Ishibuchi, Zhaohong Deng, Shitong Wang · 2014 · IEEE Transactions on Cybernetics
76. Multi-Task Learning for Spatio-Temporal Event Forecasting
    Liang Zhao, Qian Sun, Jieping Ye, Feng Chen, Chang‐Tien Lu, Naren Ramakrishnan · 2015 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
77. Deep learning-inferred multiplex immunofluorescence for immunohistochemical image quantification
    Parmida Ghahremani, Yanyun Li, Arie E. Kaufman, R. Vanguri, Noah F. Greenwald, Michael Angelo, Travis J. Hollmann, Saad Nadeem · 2022 · Nature Machine Intelligence
78. Leveraging Heterogeneous Auxiliary Tasks to Assist Crowd Counting
    Muming Zhao, Jian Zhang, Chongyang Zhang, Wenjun Zhang · 2019 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
79. Incremental Learning for Semantic Segmentation of Large-Scale Remote Sensing Data
    Onur Taşar, Yuliya Tarabalka, Pierre Alliez · 2019 · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
80. Multi-Task Learning in Natural Language Processing: An Overview
    Shijie Chen, Yu Zhang, Qiang Yang · 2024 · ACM Computing Surveys
81. Multi-Target Regression via Robust Low-Rank Learning
    Xiantong Zhen, Mengyang Yu, Xiaofei He, Shuo Li · 2017 · IEEE Transactions on Pattern Analysis and Machine Intelligence
82. Association of Artificial Intelligence–Aided Chest Radiograph Interpretation With Reader Performance and Efficiency
    Ahn, Jong Seok, Ebrahimian, Shadi, McDermott, Shaunagh, Lee, Sanghyup, Naccarato, Laura, Di Capua, John F., Wu, Markus Y., Zhang, Eric W., Muse, Victorine, Miller, Benjamin et al. · 2022 · JAMA Network Open
83. CNN-based Density Estimation and Crowd Counting: A Survey
    Guangshuai Gao, Junyu Gao, Qingjie Liu, Qi Wang, Yunhong Wang · 2020 · arXiv (Cornell University)
84. A Convex Optimization Approach to Modeling Consumer Heterogeneity in Conjoint Estimation
    Theodoros Evgeniou, Massimiliano Pontil, Olivier Toubia · 2007 · Marketing Science
85. A Review of Artificial Intelligence in the Internet of Things
    Cristian González García, Edward Rolando Núñez‐Valdéz, Vicente García‐Díaz, B. Cristina Pelayo G‐Bustelo, Juan Manuel Cueva Lovelle · 2018 · International Journal of Interactive Multimedia and Artificial Intelligence
86. A multi-energy load prediction model based on deep multi-task learning and ensemble approach for regional integrated energy systems
    Wang Xuan, Shouxiang Wang, Zhao Qianyu, Wang Shaomin, Fu Liwei · 2020 · International Journal of Electrical Power & Energy Systems
87. GEME: Dual-stream multi-task GEnder-based micro-expression recognition
    Xuan Nie, Madhumita A. Takalkar, Mengyang Duan, Haimin Zhang, Min Gang Xu · 2020 · Neurocomputing
88. A PAC-Bayesian bound for Lifelong Learning
    Anastasia Pentina, Christoph H. Lampert · 2013 · arXiv (Cornell University)
89. Probabilistic Multisite Precipitation Downscaling by an Expanded Bernoulli–Gamma Density Network
    Alex J. Cannon · 2008 · Journal of Hydrometeorology
90. Predicting with Proxies: Transfer Learning in High Dimension
    Hamsa Bastani · 2020 · Management Science
91. Graph Neural Networks for Prediction of Fuel Ignition Quality
    Artur M. Schweidtmann, Jan G. Rittig, Andrea Anna König, Martin Grohe, Alexander Mitsos, Manuel Dahmen · 2020 · Energy & Fuels
92. Multitask Learning Based on Lightweight 1DCNN for Fault Diagnosis of Wheelset Bearings
    Zhiliang Liu, Huan Wang, Junjie Liu, Yong Qin, Dandan Peng · 2020 · IEEE Transactions on Instrumentation and Measurement
93. Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks
    Jianhui Chen, Ji yin Liu, Jieping Ye · 2012 · ACM Transactions on Knowledge Discovery from Data
94. Predicting students' happiness from physiology, phone, mobility, and behavioral data
    Natasha Jaques, Sara Taylor, Asaph Azaria, Asma Ghandeharioun, Akane Sano, Rosalind W. Picard · 2015 · International Conference on Affective Computing and Intelligent Interaction and workshops
95. Overview and Evaluation of Sound Event Localization and Detection in DCASE 2019
    Archontis Politis, Annamaria Mesaros, Sharath Adavanne, Toni Heittola, Tuomas I. Virtanen · 2020 · IEEE/ACM Transactions on Audio Speech and Language Processing
96. Exhaustive QSPR Studies of a Large Diverse Set of Ionic Liquids: How Accurately Can We Predict Melting Points?
    Alexandre A. Varnek, Natalia V. Kireeva, Igor V. Tetko, Igor I. Baskin, Vitaly P. Solov’ev · 2007 · Journal of Chemical Information and Modeling
97. Deep Learning Approaches for Data Augmentation and Classification of Breast Masses using Ultrasound Images
    Walid Al-Dhabyani, Mohammed Mohammed Mohammed Gomaa, Hussien Khaled, Aly Fahmy · 2019 · International Journal of Advanced Computer Science and Applications
98. Evolving scenario of big data and Artificial Intelligence (AI) in drug discovery
    Manish Kumar Tripathi, Abhigyan Nath, Tej Pal Singh, Abdul Samath Ethayathulla, Punit Kaur · 2021 · Molecular Diversity
99. ML-Decoder: Scalable and Versatile Classification Head
    Tal Ridnik, Gilad Sharir, Avi Ben-Cohen, Emanuel Ben-Baruch, Asaf Noy · 2023 · IEEE Winter Conference on Applications of Computer Vision
100. Bayesian Spatiotemporal Multitask Learning for Radar HRRP Target Recognition
     Lan Du, Penghui Wang, Hongwei Liu, Mian Pan, Feng Chen, Zheng Bao · 2011 · IEEE Transactions on Signal Processing