Suchergebnisse - Clustered Multi-Task Learning

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

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

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

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

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

“… This paper proposes a clustered multi-task learning-based method for automated HEp-2 cells Classification …”
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Clustered Federated Multi-Task Learning: A Communication-and-Computation Efficient Sparse Sharing Approach von Ai, Yuhan, Chen, Qimei, Zhu, Guangxu, Wen, Dingzhu, Jiang, Hao, Zeng, Jun, Li, Ming

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

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

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

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

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

“… To address this issue, we present clustered FL (CFL), a novel federated multitask learning (FMTL …”
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Learning to segment clustered amoeboid cells from brightfield microscopy via multi-task learning with adaptive weight selection von Sarkar, Rituparna, Mukherjee, Suvadip, Labruyere, Elisabeth, Olivo-Marin, Jean-Christophe

“… In this regard, we introduce a novel supervised technique for cell segmentation in a multitask learning paradigm …”
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CMA-BP: A Clustered Multi-Task Learning and Branch Attention Based Branch Predictor von Li, Ming, Xu, Rucong, Zhang, Hexu, Li, Lin, Li, Yun

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

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

“… This paper proposes a hierarchical clustering multi-task learning (HC-MTL) method for joint human action grouping and recognition …”
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Clustered Federated Multitask Learning on Non-IID Data With Enhanced Privacy von Shu, Jiangang, Yang, Tingting, Liao, Xinying, Chen, Farong, Xiao, Yao, Yang, Kan, Jia, Xiaohua

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

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

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

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

“… 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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