Results 101 to 110 of about 3,537 (211)

Spatiotemporal Modeling of Surface Water–Groundwater Interactions via Multi-Task Transformer-Based Learning

Hydrology
A spatiotemporal, multi-task learning (MTL) model for simulating surface water–groundwater (SW-GW) dynamics is developed and applied to the Heihe River Basin, Northwest China.
Hao Jing, Yong Tian, Chunmiao Zheng
doaj   +1 more source

Multi-task Sparse Structure Learning With Gaussian Copula Models [PDF]

, 2017
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Multi-task learning (MTL) aims to improve generalization performance by learning multiple related tasks simultaneously.
Arindam, Fernando J.; Banerjee, Goncalves, Andre R.; Von Zuben   +3 more
core  

MTTLA‐DLW: Multi‐task TCN‐Bi‐LSTM transfer learning approach with dynamic loss weights based on feature correlations of the training samples for short‐term wind power prediction

Wind Energy
Wind power prediction for newly built wind farms is usually faced with the problem of no sufficient historical data. To efficiently extract the useful features from related wind farms, a novel transfer learning method based on temporal convolutional ...
Jifeng Song, Xiaosheng Peng, Jiajiong Song, Zimin Yang, Bo Wang, Jianfeng Che   +5 more
doaj   +1 more source

Enhancing Propaganda Detection in Arabic News Context Through Multi-Task Learning

Applied Sciences
Social media has become a platform for the rapid spread of persuasion techniques that can negatively affect individuals and society. Propaganda detection, a crucial task in natural language processing, aims to identify manipulative content in texts ...
Lubna Al-Henaki, Hend Al-Khalifa, Abdulmalik Al-Salman   +2 more
doaj   +1 more source

MTL-KD: Multi-Task Learning Via Knowledge Distillation for Generalizable Neural Vehicle Routing Solver

CoRR
Accepted at NeurIPS ...
Yuepeng Zheng, Fu Luo, Zhenkun Wang 0001, Yaoxin Wu, Yu Zhou 0027   +4 more
openaire   +2 more sources

Multi-Task Learning for Sequential Data

, 2008
The problem of multi-task learning (MTL) is considered for sequential data, such as that typically modeled via a hidden Markov model (HMM). A given task is composed of a set of sequential data, for which an HMM is to be learned, and MTL is employed to ...
Ya Xue, Shihao Ji, Lawrence Carin
core  

OR-MTL: A Robust Ordinal Regression Multi-Task Learning Framework for Partial Discharge Diagnosis in Gas-Insulated Switchgear

This paper proposes a novel Ordinal Regression Multi-Task Learning (OR-MTL) framework to address challenges in multi-task diagnosis of PD in Gas-Insulated Switchgear (GIS).
Jifu Li, Jianyan Tian, Gang Li
core   +1 more source

Multi-Task Learning with Convolutional Neural Networks

The CNN have achieved excellent performance in basic computer vision issues, such as, recognition and detection. However, the CNN is still an immature method, especially on multi-output classification.
Xia, Y
core   +1 more source

Molecular property prediction in the ultra‐low data regime

Communications Chemistry
Data scarcity remains a major obstacle to effective machine learning in molecular property prediction and design, affecting diverse domains such as pharmaceuticals, solvents, polymers, and energy carriers.
Basem A. Eraqi, Dmitrii Khizbullin, Shashank S. Nagaraja, S. Mani Sarathy   +3 more
doaj   +1 more source

The Potential of Multi-Task Learning in CFDST Design: Load-Bearing Capacity Design with Three MTL Models

Materials
Concrete-filled double steel tubes (CFDSTs) are a load-bearing structure of composite materials. By combining concrete and steel pipes in a nested structure, the performance of the column will be greatly improved. The performance of CFDSTs is closely related to their design.
Zhenyu Wang, Jian Zhou, Kang Peng
openaire   +2 more sources