Results 31 to 40 of about 603,409 (311)
Distributed Multi-Task Relationship Learning [PDF]
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2017 To appear in KDD ...
Sulin Liu, Sinno Jialin Pan, Qirong Ho
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VOGUE: Answer Verbalization Through Multi-Task Learning
, 2021 S.563-579In recent years, there have been significant developments in Question Answering over Knowledge Graphs (KGQA). Despite all the notable advancements, current KGQA systems only focus on answer generation techniques and not on answer verbalization ...
Kacupaj, E. +9 more
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Design of Efficient Speech Emotion Recognition Based on Multi Task Learning
IEEE Access, 2023 Speech emotion recognition technology includes feature extraction and classifier construction. However, the recognition efficiency is reduced due to noise interference and gender differences. To solve this problem, this paper used two multi-task learning
Liu Yunxiang, Zhang Kexin
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Multi-task Learning with Modular Reinforcement Learning
, 2022 The ability to learn compositional strategies in multi-task learning and to exert them appropriately is crucial to the development of artificial intelligence. However, there exist several challenges: (i) how to maintain the independence of modules in learning their own sub-tasks; (ii) how to avoid performance degradation in situations where modules ...
Jianyong Xue, Frédéric Alexandre
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Multi-Task Reinforcement Learning in Humans [PDF]
Nature Human Behaviour, 2019 ABSTRACT The ability to transfer knowledge across tasks and generalize to novel ones is an important hallmark of human intelligence. Yet not much is known about human multi-task reinforcement learning. We study participants’ behavior in a novel two-step decision making task with multiple features and changing reward functions.
Momchil S. Tomov +2 more
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An efficient deep multi‐task learning structure for covid‐19 disease
IET Image Processing, 2023 COVID‐19 has had a profound global impact, necessitating the development of infection detection systems based on machine learning. This paper presents a Multi‐task architecture that addresses the classification and segmentation tasks for COVID‐19 ...
Shirin Kordnoori +3 more
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CoRR, 2019 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver ...
Xi Lin 0001 +4 more
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Understanding and Application of Multi-Task Learning in Medical Artificial Intelligence
대한영상의학회지, 2022 In the medical field, artificial intelligence has been used in various ways with many developments. However, most artificial intelligence technologies are developed so that one model can perform only one task, which is a limitation in designing the ...
Young Jae Kim, Kwang Gi Kim
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Multiple object tracking based on multi‐task learning with strip attention
IET Image Processing, 2021 Multiple object tracking (MOT) framework based on bifurcate strategy was usually challenged by data association of different model path, which work for object localisation and appearance embedding independently. By incorporating the re‐identification (re‐
Yaoye Song +5 more
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Robust multi-task feature learning [PDF]
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, 2012 Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning algorithms have received increasing attention and they have been successfully applied to many applications involving high-dimensional data.
Pinghua Gong +2 more
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