Search Results - Clustered Multi-Task Learning

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  1. 1

    Quality prediction for multi-grade batch process using sparse flexible clustered multi-task learning by Yamaguchi, Takafumi, Yamashita, Yoshiyuki

    ISSN: 0098-1354
    Published: Elsevier Ltd 01.07.2021
    Published in Computers & chemical engineering (01.07.2021)
    “… These methods combine the features of two techniques: the first is a flexible clustered multi-task learning method, which utilizes data from other grades effectively…”
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    Journal Article
  2. 2

    Adaptive dual graph regularization for clustered multi-task learning by Liu, Cheng, Li, Rui, Chen, Sentao, Zheng, Lin, Jiang, Dazhi

    ISSN: 0925-2312, 1872-8286
    Published: Elsevier B.V 14.03.2024
    Published in Neurocomputing (Amsterdam) (14.03.2024)
    “… Toward this aim, we propose a clustered multi-task learning approach that collaboratively learns the cluster structure for both task and feature level effects…”
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    Journal Article
  3. 3

    Clustered Multi-Task Learning for Automatic Radar Target Recognition by Li, Cong, Bao, Weimin, Xu, Luping, Zhang, Hua

    ISSN: 1424-8220, 1424-8220
    Published: Switzerland MDPI AG 27.09.2017
    Published in Sensors (Basel, Switzerland) (27.09.2017)
    “… In this paper, we propose a clustered multi-task learning, which can reveal and share the multi-task relationships for radar target recognition…”
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    Journal Article
  4. 4

    HEp-2 cells Classification via clustered multi-task learning by Liu, Anan, Lu, Yao, Nie, Weizhi, Su, Yuting, Yang, Zhaoxuan

    ISSN: 0925-2312, 1872-8286
    Published: Elsevier B.V 26.06.2016
    Published in Neurocomputing (Amsterdam) (26.06.2016)
    “…This paper proposes a clustered multi-task learning-based method for automated HEp-2 cells Classification…”
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    Journal Article
  5. 5

    Clustered Federated Multi-Task Learning: A Communication-and-Computation Efficient Sparse Sharing Approach by Ai, Yuhan, Chen, Qimei, Zhu, Guangxu, Wen, Dingzhu, Jiang, Hao, Zeng, Jun, Li, Ming

    ISSN: 1536-1276, 1558-2248
    Published: New York IEEE 01.06.2025
    “…Federated multi-task learning (FMTL) is a promising technology to tackle one of the most severe non-independent and identically distributed (non-IID…”
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    Journal Article
  6. 6

    Flexible Clustered Multi-Task Learning by Learning Representative Tasks by Zhou, Qiang, Zhao, Qi

    ISSN: 0162-8828, 1939-3539, 2160-9292, 1939-3539
    Published: United States IEEE 01.02.2016
    “… Among various MTL methods, clustered multi-task learning (CMTL) assumes that all tasks can be clustered into groups and attempts to learn the underlying cluster structure from the training data…”
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    Journal Article
  7. 7

    A Two-stage Clustered Multi-Task Learning method for operational optimization in Chemical Mechanical Polishing by Duan, Yunqiang, Liu, Min, Dong, Mingyu, Wu, Cheng

    ISSN: 0959-1524, 1873-2771
    Published: Elsevier Ltd 01.11.2015
    Published in Journal of process control (01.11.2015)
    “… In this paper, a Two-stage Clustered Multi-Task Learning method is proposed for the above modelling problem with small sample size, in which the proposed Probability-based Task Clustering algorithm…”
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    Journal Article
  8. 8

    Clustered Federated Multi-Task Learning with Non-IID Data by Xiao, Yao, Shu, Jiangang, Jia, Xiaohua, Huang, Hejiao

    ISSN: 2690-5965
    Published: IEEE 01.12.2021
    “… To achieve the communication-efficiency and high accuracy with non-IID data, we propose a clustered federated multi-task learning by exploring client clustering and multi-task learning…”
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    Conference Proceeding
  9. 9

    Clustered Federated Multi-Task Learning on Non-IID Data with Enhanced Privacy by Shu, Jiangang, Yang, Tingting, Liao, Xinying, Chen, Farong, Xiao, Yao, Yang, Kan, Jia, Xiaohua

    ISSN: 2327-4662
    Published: IEEE 13.12.2022
    Published in IEEE internet of things journal (13.12.2022)
    “… To eliminate the limitation of full-participation, we explore multi-task learning associated with model clustering, and first propose a clustered federated multi-task learning to achieve the multual…”
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    Journal Article
  10. 10

    Clustered Multi-Task Sequence-to-Sequence Learning for Autonomous Vehicle Repositioning by Lee, Sangmin, Lim, Dae-Eun, Kang, Younkook, Kim, Hae Joong

    ISSN: 2169-3536, 2169-3536
    Published: Piscataway IEEE 2021
    Published in IEEE access (2021)
    “…Clustered multi-task learning, which aims to leverage the generalization performance over clustered tasks, has shown an outstanding performance in various machine learning applications…”
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    Journal Article
  11. 11

    Clustered Federated Learning: Model-Agnostic Distributed Multitask Optimization Under Privacy Constraints by Sattler, Felix, Muller, Klaus-Robert, Samek, Wojciech

    ISSN: 2162-237X, 2162-2388, 2162-2388
    Published: Piscataway IEEE 01.08.2021
    “… To address this issue, we present clustered FL (CFL), a novel federated multitask learning (FMTL…”
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    Journal Article
  12. 12

    Learning to segment clustered amoeboid cells from brightfield microscopy via multi-task learning with adaptive weight selection by Sarkar, Rituparna, Mukherjee, Suvadip, Labruyere, Elisabeth, Olivo-Marin, Jean-Christophe

    Published: IEEE 10.01.2021
    “… In this regard, we introduce a novel supervised technique for cell segmentation in a multitask learning paradigm…”
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    Conference Proceeding
  13. 13

    CMA-BP: A Clustered Multi-Task Learning and Branch Attention Based Branch Predictor by Li, Ming, Xu, Rucong, Zhang, Hexu, Li, Lin, Li, Yun

    Published: IEEE 06.10.2024
    “…) branches per benchmark in SPEC 2017 by current neural network methods. To improve, this paper proposed a Clustered Multi-task Learning and Branch Attention Mechanism-Based Branch Predictor (CMA-BP…”
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    Conference Proceeding
  14. 14

    GIFGIF+: Collecting emotional animated GIFs with clustered multi-task learning by Chen, Weixuan, Rudovic, Ognjen Oggi, Picard, Rosalind W.

    ISSN: 2156-8111
    Published: IEEE 01.10.2017
    “… Existing GIF datasets with emotion labels are too small for training contemporary machine learning models, so we propose a semi-automatic method to collect emotional animated GIFs from the Internet…”
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    Conference Proceeding
  15. 15

    Hierarchical Clustering Multi-Task Learning for Joint Human Action Grouping and Recognition by Liu, An-An, Su, Yu-Ting, Nie, Wei-Zhi, Kankanhalli, Mohan

    ISSN: 0162-8828, 1939-3539, 2160-9292, 1939-3539
    Published: United States IEEE 01.01.2017
    “…This paper proposes a hierarchical clustering multi-task learning (HC-MTL) method for joint human action grouping and recognition…”
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    Journal Article
  16. 16

    Clustered Federated Multitask Learning on Non-IID Data With Enhanced Privacy by Shu, Jiangang, Yang, Tingting, Liao, Xinying, Chen, Farong, Xiao, Yao, Yang, Kan, Jia, Xiaohua

    ISSN: 2327-4662, 2327-4662
    Published: Piscataway The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 15.02.2023
    Published in IEEE internet of things journal (15.02.2023)
    “… To eliminate the limitation of full-participation, we explore multitask learning associated with model clustering, and first propose a clustered FMTL to achieve the multual-task learning on non-IID…”
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    Journal Article
  17. 17

    Fair Selection of Edge Nodes to Participate in Clustered Federated Multitask Learning by Albaseer, Abdullatif Mohammed, Abdallah, Mohamed, Al-Fuqaha, Ala, Seid, Abegaz Mohammed, Erbad, Aiman, Dobre, Octavia A.

    ISSN: 1932-4537, 1932-4537
    Published: New York IEEE 01.06.2023
    “…Clustered federated Multitask learning is introduced as an efficient technique when data is unbalanced and distributed amongst clients in a non-independent and identically distributed manner…”
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    Journal Article
  18. 18

    Bi-label Propagation for Generic Multiple Object Tracking by Wenhan Luo, Tae-kyun Kim, Stenger, Bjorn, Xiaowei Zhao, Cipolla, Roberto

    ISSN: 1063-6919, 1063-6919
    Published: IEEE 01.06.2014
    “… To propagate the class label, we adopt clustered Multiple Task Learning (cMTL) while enforcing spatio-temporal consistency and show that this improves the performance when given limited training data…”
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    Conference Proceeding Journal Article
  19. 19

    User-Sensitive Recommendation Ensemble with Clustered Multi-Task Learning by Wang, Menghan, Zheng, Xiaolin, Zhang, Kun

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 28.04.2018
    Published in arXiv.org (28.04.2018)
    “… We first cluster users based on the recommendation predictions, then we use multi-task learning to learn the user-sensitive ensemble function for the users…”
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    Paper
  20. 20

    Distributed Clustering for Cooperative Multi-Task Learning Networks by Li, Jiani, Wang, Weihan, Abbas, Waseem, Koutsoukos, Xenofon

    ISSN: 2327-4697, 2334-329X
    Published: Piscataway IEEE 01.11.2023
    “… This paper focuses on clustered multi-task learning, where agents are partitioned into clusters with distinct objectives, and agents in the same cluster share the same objective…”
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    Journal Article