Results 11 to 20 of about 603,409 (311)
Correlation learning based multi-task model and its application
Shenzhen Daxue xuebao. Ligong ban, 2023 Multi-task learning is a means of learning by combining multiple tasks simultaneously to enhance the model representation and generalization ability. The correlation between tasks is the key factor for the construction of multi-task learning model.
XU Wei +3 more
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Prediction of drug–target interactions through multi-task learning
Scientific Reports, 2022 Identifying the binding between the target proteins and molecules is essential in drug discovery. The multi-task learning method has been introduced to facilitate knowledge sharing among tasks when the amount of information for each task is small ...
Chaeyoung Moon, Dongsup Kim
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Multi-Task Deep Learning Games: Investigating Nash Equilibria and Convergence Properties
Axioms, 2023 This paper conducts a rigorous game-theoretic analysis on multi-task deep learning, providing mathematical insights into the dynamics and interactions of tasks within these models.
Minhyeok Lee
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Learning to Branch for Multi-Task Learning
CoRR, 2020 Accepted at ICML ...
Pengsheng Guo +2 more
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Boosted multi-task learning [PDF]
Machine Learning, 2010 In this paper we propose a novel algorithm for multi-task learning with boosted decision trees. We learn several different learning tasks with a joint model, explicitly addressing their commonalities through shared parameters and their differences with task-specific ones. This enables implicit data sharing and regularization.
Olivier Chapelle +5 more
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FishNet: Fish visual recognition with one stage multi‐task learning
IET Image Processing, 2022 The use of computer vision for fish monitoring in aquaculture fisheries has gained importance. It is crucial to obtain the object box, instance mask and landmarks of the fish to determine their status.
Ziwen Chen +3 more
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Multi-Task Transformer with Adaptive Cross-Entropy Loss for Multi-Dialect Speech Recognition
Entropy, 2022 At present, most multi-dialect speech recognition models are based on a hard-parameter-sharing multi-task structure, which makes it difficult to reveal how one task contributes to others.
Zhengjia Dan +4 more
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JohnLaMaster/Impartial-Multi-Task-Learning: Initial Release
, 2022 PyTorch implementation of "Towards Impartial Multi-Task ...
John LaMaster
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Multi-Task Network Representation Learning
Frontiers in Neuroscience, 2020 Networks, such as social networks, biochemical networks, and protein-protein interaction networks are ubiquitous in the real world. Network representation learning aims to embed nodes in a network as low-dimensional, dense, real-valued vectors, and ...
Yu Xie +4 more
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Task-Aware Dynamic Model Optimization for Multi-Task Learning
IEEE Access, 2023 Multi-task learning (MTL) is a field in which a deep neural network simultaneously learns knowledge from multiple tasks. However, achieving resource-efficient MTL remains challenging due to entangled network parameters across tasks and varying task ...
Sujin Choi, Hyundong Jin, Eunwoo Kim
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