Ting Hu,Xiaotong Liu,Kai Ji et al.
Ting Hu et al.
In this article, we present a family of adaptive stochastic optimization methods, which are associated with mirror maps that are widely used to capture the geometry properties of optimization problems during iteration processes. The well-kn...
Model-Free and Pseudoinverse-Free Zhang Neurodynamics Scheme for Robotic Arms' Path Tracking Control [0.03%]
无需模型和伪逆的张神经动力学方案在机械臂轨迹跟踪控制中的应用
Jielong Chen,Yan Pan,Yunong Zhang
Jielong Chen
Path tracking control of robotic arms is regarded as a fundamental problem in the field of robotics. However, obtaining an accurate model of the robotic arm in practical engineering poses significant challenges. As a result, model-free sche...
Protein Language Pragmatic Analysis and Progressive Transfer Learning for Profiling Peptide-Protein Interactions [0.03%]
蛋白质语言的语用分析和渐进迁移学习在描绘肽-蛋白质相互作用中的应用
Shutao Chen,Ke Yan,Xuelong Li et al.
Shutao Chen et al.
Protein complex structural data are growing at an unprecedented pace, but its complexity and diversity pose significant challenges for protein function research. Although deep learning models have been widely used to capture the syntactic s...
A Novel Fusion and Feature Selection Framework for Multisource Time-Series Data Based on Information Entropy [0.03%]
一种基于信息熵的多源时间序列数据融合与特征选择新框架
Xiuwei Chen,Li Lai,Maokang Luo
Xiuwei Chen
Information technology growth brings vast time-series data. Despite richness, challenges like redundancy emphasize the need for time-series data fusion research. Rough set theory, a valuable tool for dealing with uncertainty, can identify f...
Mean-Square Synchronization of Additive Time-Varying Delayed Markovian Jumping Neural Networks Under Multiple Stochastic Sampling [0.03%]
多重随机采样下加性时变延迟Markov跳变神经网络的均方同步
Pratap Anbalagan,Zhiguang Feng,Tingwen Huang et al.
Pratap Anbalagan et al.
This study aims to solve the mean-square asymptotic synchronization problem of additive time-varying delayed Markovian jumping neural networks (ATVMJNNs) under the framework of multiple stochastic samplings and its direct application in sec...
Globality Meets Locality: An Anchor Graph Collaborative Learning Framework for Fast Multiview Subspace Clustering [0.03%]
全局性与局部性的结合：用于快速多视角子空间聚类的锚图协作学习框架
Jipeng Guo,Yanfeng Sun,Xin Ma et al.
Jipeng Guo et al.
Multiview subspace clustering (MSC) maximizes the utilization of complementary description information provided by multiview data and achieves impressive clustering performance. However, most of them are inefficient or even invalid among la...
Dual Consistency Constraint-Based Self-Supervised Representation Learning for Heterogeneous Graphs With Missing Attributes [0.03%]
基于双一致性约束的具有缺失属性异构图的自监督表示学习
Yajie Lei,Yujie Mo,Luping Ji et al.
Yajie Lei et al.
Missing attribute completion for unattributed nodes in heterogeneous graphs has received increasing attention, but previous works still suffer from the following issues: 1) they ignore the noise in the raw attributes, resulting in noise pro...
Yizhang Wang,Wei Pang,Di Wang et al.
Yizhang Wang et al.
Federated clustering (FC) performs well in independent and identically distributed (IID) scenarios, but it does not perform well in non-IID scenarios. In addition, existing methods lack proof of strict privacy protection. To address the abo...
INGC-GAN: An Implicit Neural-Guided Cycle Generative Approach for Perceptual-Friendly Underwater Image Enhancement [0.03%]
INGC-GAN：一种感知友好的水下图像增强隐式神经网络引导循环生成方法
Weiming Li,Xuelong Wu,Shuaishuai Fan et al.
Weiming Li et al.
The key requirement for underwater image enhancement (UIE) is to overcome the unpredictable color degradation caused by the underwater environment and light attenuation, while addressing issues, such as color distortion, reduced contrast, a...
Neuron Perception Inspired EEG Emotion Recognition With Parallel Contrastive Learning [0.03%]
受神经感知启发的平行对比学习EEG情感识别
Dongdong Li,Shengyao Huang,Li Xie et al.
Dongdong Li et al.
Considerable interindividual variability exists in electroencephalogram (EEG) signals, resulting in challenges for subject-independent emotion recognition tasks. Current research in cross-subject EEG emotion recognition has been insufficien...