A multitask co-training framework for improving speech translation by leveraging speech recognition and machine translation tasks
Y Zhou, Y Yuan, X Shi - Neural Computing and Applications, 2024 - Springer
End-to-end speech translation (ST) has attracted substantial attention due to its less error
accumulation and lower latency. Based on triplet ST data⟨ speech-transcription …
accumulation and lower latency. Based on triplet ST data⟨ speech-transcription …
IMPRL-Net: interpretable multi-view proximity representation learning network
Due to the heterogeneity gap in multi-view data, researchers have been attempting to apply
these data to learn a co-latent representation to bridge this gap. However, multi-view …
these data to learn a co-latent representation to bridge this gap. However, multi-view …
Target Identification via Multi-View Multi-Task Joint Sparse Representation
J Chen, Z Zhang, X Wen - Applied Sciences, 2022 - mdpi.com
Recently, the monitoring efficiency and accuracy of visible and infrared video have been
relatively low. In this paper, we propose an automatic target identification method using …
relatively low. In this paper, we propose an automatic target identification method using …
Novel multi-view Takagi–Sugeno–Kang fuzzy system for epilepsy EEG detection
Y Li, P Qian, S Wang, S Wang - Journal of Ambient Intelligence and …, 2023 - Springer
Most intelligent algorithms used for recognizing epilepsy electroencephalogram (EEG) have
two major deficiencies. The one is the lack of interpretability and the other is unsatisfactory …
two major deficiencies. The one is the lack of interpretability and the other is unsatisfactory …
基于多视图矩阵补全的蛋白受体功能预测
黄玮翔， 丁季， 刘夏栩， 殷勤， 兰闯闯… - 南京大学学报(自然科学 …, 2024 - jns.nju.edu.cn
摘要蛋白受体是细胞信号转导的重要组成部分, 也是人类最重要的药物靶点, 其中G
蛋白偶联受体(G Protein Coupled Receptors, GPCRs) 占绝大部分, 目前市场上大约34 …
蛋白偶联受体(G Protein Coupled Receptors, GPCRs) 占绝大部分, 目前市场上大约34 …
Multiplicative Sparse Tensor Factorization for Multi-View Multi-Task Learning
Multi-View Multi-Task Learning (MVMTL) aims to make predictions on dual-heterogeneous
data. Such data contains features from multiple views, and multiple tasks in the data are …
data. Such data contains features from multiple views, and multiple tasks in the data are …
基于多视角学习的时序多模态情感分类研究.
陶全桧， 安俊秀， 戴宇睿， 陈宏松… - Application Research of …, 2023 - search.ebscohost.com
针对多模态融合效果不佳, 不能充分挖掘特定时间段, 多视角关键情感信息的问题,
提出了一种基于多视角的时序多模态情感分类模型, 用于提取特定时间段, 多视角下的关键情感 …
提出了一种基于多视角的时序多模态情感分类模型, 用于提取特定时间段, 多视角下的关键情感 …
Task-Oriented Multi-View Representation Learning
Multi-view representation learning aims to learn a high-quality unified representation for an
entity from its multiple observable views to facilitate the performance of downstream tasks. A …
entity from its multiple observable views to facilitate the performance of downstream tasks. A …
A graphical approach for multiclass classification and for correcting the labeling errors in mislabeled training data
E Merkurjev - Intelligent Data Analysis, 2021 - content.iospress.com
Multiclass data classification, where the goal is to segment data into classes, is an important
task in machine learning. However, the task is challenging due to reasons including the …
task in machine learning. However, the task is challenging due to reasons including the …