Results 121 to 130 of about 7,496 (160)

Signal-Guided Multitask Learning for Myocardial Infarction Classification Using Images of Electrocardiogram.

Cardiology
Park BE, Shon B, Cho J, Jung MS, Park JS, Kim MS, Lee E, Choi H, Park HK, Park YJ, Kim HN, Kim N, Bae MH, Lee JH, Yang DH, Park HS, Cho Y, Jeong S, Jang SY.   +18 more
europepmc   +1 more source

Balancing Between Privacy and Utility for Affect Recognition Using Multitask Learning in Differential Privacy-Added Federated Learning Settings: Quantitative Study.

JMIR Ment Health
Benouis M, Andre E, Can YS.
europepmc   +1 more source

Empowering Mental Health Monitoring Using a Macro-Micro Personalization Framework for Multimodal-Multitask Learning: Descriptive Study.

JMIR Ment Health
Song M, Yang Z, Triantafyllopoulos A, Zhang Z, Nan Z, Tang M, Takeuchi H, Nakamura T, Kishi A, Ishizawa T, Yoshiuchi K, Schuller B, Yamamoto Y.   +12 more
europepmc   +1 more source

Multitask model-free reinforcement learning

, 2014
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Semisupervised Multitask Learning

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009
Context plays an important role when performing classification, and in this paper we examine context from two perspectives. First, the classification of items within a single task is placed within the context of distinct concurrent or previous classification tasks (multiple distinct data collections).
Qiuhua, Liu, Xuejun, Liao, Hui Li, Carin, Jason R, Stack, Lawrence, Carin   +4 more
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Faceted Text Segmentation via Multitask Learning

IEEE Transactions on Neural Networks and Learning Systems, 2021
Text segmentation is a fundamental step in natural language processing (NLP) and information retrieval (IR) tasks. Most existing approaches do not explicitly take into account the facet information of documents for segmentation. Text segmentation and facet annotation are often addressed as separate problems, but they operate in a common input space ...
Bei Wu, Bifan Wei, Jun Liu, Kewei Wu, Meng Wang   +4 more
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Multitask Learning for Visual Question Answering

IEEE Transactions on Neural Networks and Learning Systems, 2023
Visual question answering (VQA) is a task that machines should provide an accurate natural language answer given an image and a question about the image. Many studies have found that the current VQA methods are heavily driven by the surface correlation or statistical bias in the training data, and lack sufficient image grounding. To address this issue,
Jie Ma, Jun Liu, Qika Lin, Bei Wu, Yaxian Wang, Yang You   +5 more
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Multitask Robot Learning Control

1992 American Control Conference, 1992
In this paper, we consider the problem of determining an optimal trajectory for the execution of class of robot tasks using a learning-adaptive robot control systems. A quadratic cost functional which involves the reference trajectory and the actual control efforts is optimized on-line while the robot is learning how to execute the tasks.
Roberto Horowitz, Perry Li
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Online Federated Multitask Learning

2019 IEEE International Conference on Big Data (Big Data), 2019
With the popular use of mobile devices, it becomes increasingly important to conduct analysis on distributed data collected from multiple devices. Federated learning is a distributed learning framework which takes advantage of the training data and computational ability of scattered mobile devices to learn prediction models, and multi-task learning ...
Rui Li, Fenglong Ma, Wenjun Jiang, Jing Gao   +3 more
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