Multitask Learning

Cited by (1,024)

Items 701–800 of 1,024

1. Writer Adaptation with Style Transfer Mapping
   Xu-Yao Zhang, Cheng‐Lin Liu · 2012 · IEEE Transactions on Pattern Analysis and Machine Intelligence
2. Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches
   Liying Zhang, Alexander Sedykh, Ashutosh Tripathi, Hao Zhu, Antreas Afantitis, Varnavas D. Mouchlis, Georgia Melagraki, Ivan Rusyn, Alexander Tropsha · 2013 · Toxicology and Applied Pharmacology
3. QSAR Modeling of Tox21 Challenge Stress Response and Nuclear Receptor Signaling Toxicity Assays
   Stephen J. Capuzzi, Regina Politi, Olexandr Isayev, Sherif Farag, Alexander Tropsha · 2016 · Frontiers in Environmental Science
4. Multi-step virtual metrology for semiconductor manufacturing: A multilevel and regularization methods-based approach
   Gian Antonio Susto, Simone Pampuri, Andrea Schirru, Alessandro Beghi, Giuseppe De Nicolao · 2014 · Computers & Operations Research
5. Hyperspherical Prototype Networks
   Pascal Mettes, Elise van der Pol, Cees G. M. Snoek · 2019 · arXiv (Cornell University)
6. Transfer bounds for linear feature learning
   Andreas Maurer · 2009 · Machine Learning
7. Multitask Learning for Protein Subcellular Location Prediction
   Qian Xu, Sinno Jialin Pan, Hong Xue, Qiang Yang · 2010 · IEEE Transactions on Computational Biology and Bioinformatics
8. TA-CNN: Two-way attention models in deep convolutional neural network for plant recognition
   Youxiang Zhu, Weiming Sun, Xiangying Cao, Chunyan Wang, Dongyang Wu, Yin Yang, Ning Ye · 2019 · Neurocomputing
9. Self-Supervised Learning Across Domains
   Silvia Bucci, Antonio D’Innocente, Yujun Liao, Fabio Maria Carlucci, Barbara Caputo B, Tatiana Tommasi · 2021 · IEEE Transactions on Pattern Analysis and Machine Intelligence
10. Algorithmic encoding of protected characteristics in chest X-ray disease detection models
    Ben Glocker, Charles Jones, Mélanie Bernhardt, Stefan Winzeck · 2023 · EBioMedicine
11. Joint Feature Extraction and Classifier Design for ECG-Based Biometric Recognition
    Sandeep Gutta, Qi Cheng · 2015 · IEEE Journal of Biomedical and Health Informatics
12. Flexible Clustered Multi-Task Learning by Learning Representative Tasks
    Qiang Zhou, Qi Zhao · 2015 · IEEE Transactions on Pattern Analysis and Machine Intelligence
13. Group Sparsity Based Multi-Target Tracking in Passive Multi-Static Radar Systems Using Doppler-Only Measurements
    Saurav Subedi, Yimin Daniel Zhang, Moeness G. Amin, Braham Himed · 2016 · IEEE Transactions on Signal Processing
14. Multi-Task Multi-View Clustering
    Xiaotong Zhang, Xianchao Zhang, Han Liu, Xinyue Liu · 2016 · IEEE Transactions on Knowledge and Data Engineering
15. Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study
    Qi Liu, Qian Xu, Vincent Wenchen Zheng, Hong Xue, Zhiwei Cao, Qiang Yang · 2010 · BMC Bioinformatics
16. RATM: Recurrent Attentive Tracking Model
    Samira Ebrahimi Kahou, Vincent Michalski, Roland Memisevic, Christopher Pal, Pascal Vincent · 2017 · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
17. Extraction of Information Related to Adverse Drug Events from Electronic Health Record Notes: Design of an End-to-End Model Based on Deep Learning
    Fei Li, Weisong Liu, Hong Qing Yu · 2018 · JMIR Medical Informatics
18. Intelligent optical performance monitor using multi-task learning based artificial neural network
    Zhiquan Wan, Zhenming Yu, Liang Shu, Yilun Zhao, Haojie Zhang, Kun Xu · 2019 · Optics Express
19. Omnidirectional Image Quality Assessment by Distortion Discrimination Assisted Multi-Stream Network
    Yu Zhou, Yanjing Sun, Leida Li, Ke Gu, Yuming Fang · 2021 · IEEE Transactions on Circuits and Systems for Video Technology
20. Review of transfer learning in modeling additive manufacturing processes
    Yifan Tang, Mostafa Rahmani Dehaghani, G. Gary Wang · 2022 · Additive manufacturing
21. Inferring multiple graphical structures
    Julien Chiquet, Yves Grandvalet, Christophe Ambroise · 2010 · Statistics and Computing
22. Robust multi-task learning witht-processes
    Shipeng Yu, Volker Tresp, Kai Yu · 2007 · International Conference on Machine Learning
23. A multiple support vector machine approach to stock index forecasting with mixed frequency sampling
    Yuchen Pan, Zhi Xiao, Xianning Wang, Daoli Yang · 2017 · Knowledge-Based Systems
24. Fast reinforcement learning with generalized policy updates
    André da Motta Salles Barreto, Shaobo Hou, Diana Borsa, David Silver, Doina Precup · 2020 · Proceedings of the National Academy of Sciences
25. On the Theory of Transfer Learning: The Importance of Task Diversity
    Nilesh Tripuraneni, Michael I. Jordan, Chi Jin · 2020 · arXiv (Cornell University)
26. Complex ratio masking for joint enhancement of magnitude and phase
    Donald S. Williamson, Yuxuan Wang, DeLiang Wang · 2016 · IEEE International Conference on Acoustics Speech and Signal Processing
27. Incremental Relabeling for Active Learning with Noisy Crowdsourced Annotations
    Liyue Zhao, Gita Sukthankar, Rahul Sukthankar · 2011 · International Conference on Social Computing
28. Coevolutionary multitasking for concurrent global optimization: With case studies in complex engineering design
    Meiying Cheng, Abhishek Gupta, Yew-Soon Ong, Zhiwei Ni · 2017 · Engineering Applications of Artificial Intelligence
29. Iterative multi-task learning for time-series modeling of solar panel PV outputs
    Tahasin Shireen, Chenhui Shao, Hui Wang, Jingjing Li, Xi Zhang, Mingyang Li · 2017 · Applied Energy
30. Recurrent Neural Networks in Linguistic Theory: Revisiting Pinker and Prince (1988) and the Past Tense Debate
    Christo Kirov, Ryan Cotterell · 2018 · Transactions of the Association for Computational Linguistics
31. DeepDiff: DEEP-learning for predicting DIFFerential gene expression from histone modifications
    Arshdeep Sekhon, Ritambhara Singh, Yanjun Qi · 2018 · Bioinformatics
32. Learning Geo-Contextual Embeddings for Commuting Flow Prediction
    Zhicheng Liu, Fábio Miranda, Weiting Xiong, Junyan Yang, Qiao Wang, Claudio T. Silva · 2020 · Proceedings of the AAAI Conference on Artificial Intelligence
33. Reparameterizing Convolutions for Incremental Multi-Task Learning Without Task Interference
    Menelaos Kanakis, David Brüggemann, Suman Saha, Stamatios Georgoulis, Anton Obukhov, Luc Van Gool · 2020 · Lecture notes in computer science
34. A machine learning framework for accelerating the design process using CAE simulations: An application to finite element analysis in structural crashworthiness
    Christopher P. Kohar, Lars Greve, Tom Eller, Daniel S. Connolly, Kaan Inal · 2021 · Computer Methods in Applied Mechanics and Engineering
35. Multitask dictionary learning and sparse representation based single-image super-resolution reconstruction
    Shuyuan Yang, Zhizhou Liu, Min Wang, Fenghua Sun, Licheng Jiao · 2011 · Neurocomputing
36. A Public-Private-Partnership Model for National Cyber Situational Awareness
    Tímea Páhi, Florian Skopik · 2016 · International Journal on Cyber Situational Awareness
37. Combining deep neural network and traditional image features to improve survival prediction accuracy for lung cancer patients from diagnostic CT
    Rahul Paul, Samuel H. Hawkins, Lawrence Hall, Dmitry B. Goldgof, Robert J. Gillies · 2016 · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics
38. Learning Multiple Tasks with Deep Relationship Networks
    Mingsheng Long, Jianmin Wang, Philip S. Yu · 2015 · arXiv (Cornell University)
39. Learning Tree Structure in Multi-Task Learning
    Lei Han, Yu Zhang · 2015 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
40. Learning incoherent sparse and low-rank patterns from multiple tasks
    Jianhui Chen, Ji yin Liu, Jieping Ye · 2010 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
41. A distance map regularized CNN for cardiac cine MR image segmentation
    Shusil Dangi, Cristian A. Linte, Ziv Yaniv · 2019 · Medical Physics
42. Does Learning Specific Features for Related Parts Help Human Pose Estimation?
    Wei Tang, Ying Nian Wu · 2019 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
43. The power of deep learning to ligand-based novel drug discovery
    Igor I. Baskin · 2020 · Expert Opinion on Drug Discovery
44. Multi-Loss Weighting with Coefficient of Variations
    Rick W. Groenendijk, Sezer Karaoğlu, Theo Gevers, Thomas Mensink · 2021 · IEEE Winter Conference on Applications of Computer Vision
45. Convolutional neural networks for the automatic diagnosis of melanoma: An extensive experimental study
    Eduardo Pérez, Óscar Reyes, Sebastián Ventura · 2020 · Medical Image Analysis
46. MRENet: Simultaneous Extraction of Road Surface and Road Centerline in Complex Urban Scenes from Very High-Resolution Images
    Zhenfeng Shao, Zifan Zhou, Xiao Huang, Ya Zhang · 2021 · Remote Sensing
47. Towards Impartial Multi-task Learning
    Liyang Liu, Yi Li, Zhanghui Kuang, Jing‐Hao Xue, Yimin Chen, Wenming Yang, Qingmin Liao, Wayne Zhang · 2021 · UCL Discovery (University College London)
48. Pedestrian intention prediction: A convolutional bottom-up multi-task approach
    Haziq Razali, Taylor Mordan, Alexandre Alahi · 2021 · Transportation Research Part C Emerging Technologies
49. Multitask Machine Learning to Predict Polymer–Solvent Miscibility Using Flory–Huggins Interaction Parameters
    Yuta Aoki, Stephen Wu, Teruki Tsurimoto, Yoshihiro Hayashi, Shunya Minami, Okubo Tadamichi, Kazuya Shiratori, Ryo Yoshida · 2023 · Macromolecules
50. Searching for Complex Human Activities with No Visual Examples
    Nazlı İkizler-Cinbiş, David Alexander Forsyth · 2008 · International Journal of Computer Vision
51. How to Train Neural Networks
    Ralph Neuneier, Hans-Georg Zimmermann · 2012 · Lecture notes in computer science
52. ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning
    Vamsi Aribandi, Yi Tay, Tal Schuster, Jinfeng Rao, Huaixiu Zheng, Sanket Vaibhav Mehta, Honglei Zhuang, Vinh Q. Tran, Dara Bahri, Jianmo Ni et al. · 2021 · arXiv (Cornell University)
53. Multi-Task Self-Training for Learning General Representations
    Ghiasi, Golnaz, Zoph, Barret, Cubuk, Ekin D., Le, Quoc V., Lin, Tsung-Yi · 2021 · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
54. Online Multitask Learning
    Ofer Dekel, Philip M. Long, Yoram Singer · 2006 · Lecture notes in computer science
55. Multi-Stage Multi-Task Learning with Reduced Rank
    Lei Han, Yu Zhang · 2016 · Proceedings of the AAAI Conference on Artificial Intelligence
56. Optimal carbon storage reservoir management through deep reinforcement learning
    Alexander Y. Sun · 2020 · Applied Energy
57. Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks
    Trapit Bansal, Rishikesh Jha, Tsendsuren Munkhdalai, Andrew McCallum · 2020 · Conference on Empirical Methods in Natural Language Processing (EMNLP)
58. When Self-Supervised Learning Meets Scene Classification: Remote Sensing Scene Classification Based on a Multitask Learning Framework
    Zhicheng Zhao, Ze Luo, Jian Li, Can Chen, Yingchao Piao · 2020 · Remote Sensing
59. A Hierarchical BERT-Based Transfer Learning Approach for Multi-Dimensional Essay Scoring
    Jin Xue, Xiaoyi Tang, Liyan Zheng · 2021 · IEEE Access
60. Conceptual challenges for interpretable machine learning
    Watson, David S. · 2022 · Synthese
61. Machine learning for passive mental health symptom prediction: Generalization across different longitudinal mobile sensing studies
    Daniel A. Adler, Fei Wang, David C. Mohr, Tanzeem Choudhury · 2022 · PLoS ONE
62. Autotelic Agents with Intrinsically Motivated Goal-Conditioned Reinforcement Learning: A Short Survey
    Cédric Colas, Tristan Karch, Olivier Sigaud, Pierre‐Yves Oudeyer · 2022 · Journal of Artificial Intelligence Research
63. A metalearning approach for Physics-Informed Neural Networks (PINNs): Application to parameterized PDEs
    Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby · 2023 · Journal of Computational Physics
64. MTSCD-Net: A network based on multi-task learning for semantic change detection of bitemporal remote sensing images
    Fengzhi Cui, Jie Jiang · 2023 · International Journal of Applied Earth Observation and Geoinformation
65. Distilling Accurate Descriptors from Multi-Source Experimental Data for Discovering Highly Active Perovskite OER Catalysts
    Jingzhou Wang, Huachao Xie, Yuanqing Wang, Runhai Ouyang · 2023 · Journal of the American Chemical Society
66. Model Recommendation with Virtual Probes for Egocentric Hand Detection
    Cheng Li, Kris Kitani · 2013 · IEEE/CVF International Conference on Computer Vision (ICCV)
67. Proximity Without Consensus in Online Multiagent Optimization
    Alec Koppel, Brian M. Sadler, Alejandro Ribeiro · 2017 · IEEE Transactions on Signal Processing
68. A Comprehensive Study of ImageNet Pre-Training for Historical Document Image Analysis
    Linda Studer, Michele Alberti, Vinaychandran Pondenkandath, Pinar Goktepe, Thomas Kolonko, Andreas Fischer, Marcus Liwicki, Rolf Ingold · 2019 · IAPR International Conference on Document Analysis and Recognition (ICDAR)
69. Bi-Directional Neural Machine Translation with Synthetic Parallel Data
    Xing Niu, Michael Denkowski, Marine Jacinthe Carpuat · 2018
70. Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels
    Felix Bragman, Ryutaro Tanno, Sebastien Ourselin A, Daniel C. Alexander, M. Jorge Cardoso · 2019 · IEEE/CVF International Conference on Computer Vision (ICCV)
71. GJ 367b: A dense, ultrashort-period sub-Earth planet transiting a nearby red dwarf star
    Kristine W. F. Lam, Szilárd Csizmadia, N. Astudillo-Defru, Xavier Bonfils, D. Gandolfi, Sebastiano Padovan, M. Esposito, Coel Hellier, Teruyuki Hirano, John H. Livingston et al. · 2021 · Science
72. A Survey on Event Extraction for Natural Language Understanding: Riding the Biomedical Literature Wave
    Giacomo Frisoni, Gianluca Moro, Antonella Carbonaro · 2021 · IEEE Access
73. AIONER: all-in-one scheme-based biomedical named entity recognition using deep learning
    Ling Luo, Chih-Hsuan Wei, Po‐Ting Lai, Robert Leaman, Qingyu Chen, Zhiyong Lu · 2023 · Bioinformatics
74. GlassNet: A multitask deep neural network for predicting many glass properties
    Daniel R. Cassar · 2023 · Ceramics International
75. Advancing horizons in remote sensing: a comprehensive survey of deep learning models and applications in image classification and beyond
    Sidike Paheding, Ashraf I. Saleem, Mohammad Faridul Haque Siddiqui, Nathir A. Rawashdeh, Almabrok E. Essa, Abel A. Reyes-Angulo · 2024 · Neural Computing and Applications
76. An Algorithm for Transfer Learning in a Heterogeneous Environment
    Andreas Argyriou, Andreas Maurer, Massimiliano Pontil · 2008 · Lecture notes in computer science
77. Coupling semi-supervised learning of categories and relations
    Andrew Carlson, Justin Betteridge, Estevam Rafael Hruschka Junior, Tom M. Mitchell · 2009
78. Inductive transfer for learning Bayesian networks
    Roger Luis, Luis Enrique Sucar, Eduardo F. Morales · 2009 · Machine Learning
79. Second Language Acquisition Modeling
    Burr Settles, Chris Brust, Erin Gustafson, Masato Hagiwara, Nitin Madnani · 2018 · Workshop on Innovative Use of NLP for Building Educational Applications
80. Convex Discriminative Multitask Clustering
    Xiao-Lei Zhang · 2014 · IEEE Transactions on Pattern Analysis and Machine Intelligence
81. Scaling up Open Tagging from Tens to Thousands: Comprehension Empowered Attribute Value Extraction from Product Title
    Huimin Xu, Meng Wan, Xin Mao, Xinyu Jiang, Man Lan · 2019 · Proceedings of the conference - Association for Computational Linguistics. Meeting
82. Multi-style Generative Reading Comprehension
    Kyosuke Nishida, Itsumi Saito, Kosuke Nishida, Kazutoshi Shinoda, Atsushi Otsuka, Hisako Asano, Junji Tomita · 2019 · Proceedings of the conference - Association for Computational Linguistics. Meeting
83. Massive Choice, Ample Tasks (MaChAmp): A Toolkit for Multi-task Learning in NLP
    Rob van der Goot, Ahmet Üstün, Alan Ramponi, Ibrahim Sharaf, Barbara Plank · 2021 · Conference of the European Chapter of the Association for Computational Linguistics
84. Ensemble of multi-task deep convolutional neural networks using transfer learning for fruit freshness classification
    Jaeyong Kang, Jeonghwan Gwak · 2021 · Multimedia Tools and Applications
85. KG-SP: Knowledge Guided Simple Primitives for Open World Compositional Zero-Shot Learning
    Shyamgopal Karthik, Massimiliano Mancini, Zeynep Akata · 2022 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
86. Boosted multi-task learning
    Olivier Chapelle, Pannagadatta K. Shivaswamy, Srinivas Vadrevu, Kilian Q. Weinberger, Ya Zhang, Belle L. Tseng · 2010 · Machine Learning
87. Computational Foundations of Natural Intelligence
    Marcel A. J. van Gerven · 2017 · Frontiers in Computational Neuroscience
88. Activity recognition: linking low-level sensors to high-level intelligence
    Qiang Yang · 2009
89. Joint training of convolutional and non-convolutional neural networks
    Hagen Soltau, George Saon, Tara N. Sainath · 2014 · IEEE International Conference on Acoustics Speech and Signal Processing
90. Multi-task deep convolutional neural network for cancer diagnosis
    Qing Liao, Ye Ding, Zoe L. Jiang, Xuan Wang, Chunkai Zhang, Qian Zhang · 2018 · Neurocomputing
91. Multi-task least squares twin support vector machine for classification
    Benshan Mei, Yitian Xu · 2019 · Neurocomputing
92. Attention-Based Autism Spectrum Disorder Screening With Privileged Modality
    Shi Chen, Qi Zhao · 2019 · IEEE/CVF International Conference on Computer Vision (ICCV)
93. Computer-Aided Diagnosis of Alzheimer’s Disease through Weak Supervision Deep Learning Framework with Attention Mechanism
    Shuang Liang, Yu Gu · 2020 · Sensors
94. Deep learning for named entity recognition: a survey
    Zhentao Hu, Wei Zhou Hou, Xianxing Liu · 2024 · Neural Computing and Applications
95. A multi-energy load forecasting method based on complementary ensemble empirical model decomposition and composite evaluation factor reconstruction
    Kang Li, Pengfei Duan, Xiaodong Cao, Yuanda Cheng, Bingxu Zhao, Qingwen Xue, Mengdan Feng · 2024 · Applied Energy
96. A Convex Formulation for Learning from Crowds
    Hiroshi Kajino, Yuta Tsuboi, Hisashi Kashima · 2021 · Proceedings of the AAAI Conference on Artificial Intelligence
97. Untitled work
    Chen Ling · 2020 · 10.1145/3381012
98. Semi-Supervised Multi-Task Regression
    Yu Zhang, Dit‐Yan Yeung · 2009 · Lecture notes in computer science
99. Online Learning of Multiple Tasks with a Shared Loss
    Ofer Dekel, Philip M. Long, Yoram Singer · 2007
100. When is multitask learning effective? Semantic sequence prediction under varying data conditions
     Héctor Martínez Alonso, Barbara Plank · 2017 · Conference of the European Chapter of the Association for Computational Linguistics