Route-and-Aggregate Decentralized Federated Learning Under Communication Errors [0.03%]
存在通信误差的路由和聚合去中心化联邦学习
Weicai Li,Tiejun Lv,Wei Ni et al.
Weicai Li et al.
Decentralized federated learning (D-FL) allows clients to aggregate learning models locally, offering flexibility and scalability. Existing D-FL methods use gossip protocols, which are inefficient when not all nodes in the network are D-FL ...
Analysis and Design of a Distributed kWTA With Application in Sealed-Bid Auctions With Bidding Price Privacy Protection [0.03%]
基于密封价格隐私保护的招标拍卖的分布式kWTA分析与设计
John Sum,Chi-Sing Leung,Janet C C Chang
John Sum
This article presents a distributed k-winner-take-all (kWTA) with application in sealed-bid auctions with bidding price privacy protection. The proposed kWTA is in essence a distributed network of n agents which are arbitrarily connected. L...
An Interpretable Neural Control Network With Adaptable Online Learning for Sample Efficient Robot Locomotion Learning [0.03%]
一种可解释的神经控制网络具备在线学习能力 用于样本高效的机器人行走学习
Arthicha Srisuchinnawong,Poramate Manoonpong
Arthicha Srisuchinnawong
Robot locomotion learning using reinforcement learning suffers from training sample inefficiency and exhibits the non-interpretable/closed-box nature. Thus, this work presents a novel SME-Adaptable Gradient-weighting Online Learning (AGOL) ...
Grouped Vector Autoregression Reservoir Computing Based on Randomly Distributed Embedding for Multistep-Ahead Prediction [0.03%]
基于随机分布嵌入的分组向量自回归蓄水池计算在多步预测中的应用
Heshan Wang,Zhepeng Wang,Mingyuan Yu et al.
Heshan Wang et al.
As an efficient recurrent neural network (RNN), reservoir computing (RC) has achieved various applications in time-series forecasting. Nevertheless, a poorly explained phenomenon remains as to why the RC and deep RCs succeed in handling tim...
MI-MCF: A Mutual Information-Based Multilabel Causal Feature Selection [0.03%]
基于互信息的多标签因果特征选择（MI-MCF）
Lin Ma,Liang Hu,Yonghao Li et al.
Lin Ma et al.
Multilabel causal feature selection has attracted extensive attention in recent years. Current multilabel causal feature selection algorithms typically employ existing Markov Blanket (MB) search methods for the initial construction of the M...
Semantic Prompt Enhancement for Semi-Supervised Low-Light Salient Object Detection [0.03%]
基于语义提示增强的半监督低光照显著目标检测方法
Nana Yu,Jie Wang,Zihao Zhang et al.
Nana Yu et al.
Most existing salient object detection (SOD) models are designed based on data collected in well-lit scenes, which is entirely inadequate for low-light conditions. Although recent models are designed for low-light conditions, they still hav...
End-to-End Streaming Video Temporal Action Segmentation With Reinforcement Learning [0.03%]
基于强化学习的端到端流视频时序行为分割
Jin-Rong Zhang,Wu-Jun Wen,Sheng-Lan Liu et al.
Jin-Rong Zhang et al.
The streaming temporal action segmentation (STAS) task, a supplementary task of temporal action segmentation (TAS), has not received adequate attention in the field of video understanding. Existing TAS methods are constrained to offline sce...
Multilevel Contrastive Multiview Clustering With Dual Self-Supervised Learning [0.03%]
基于双重自监督的多视图多层次对比聚类方法
Jintang Bian,Yixiang Lin,Xiaohua Xie et al.
Jintang Bian et al.
Multiview clustering (MVC) aims to integrate multiple related but different views of data to achieve more accurate clustering performance. Contrastive learning has found many applications in MVC due to its successful performance in unsuperv...
EmT: A Novel Transformer for Generalized Cross-Subject EEG Emotion Recognition [0.03%]
基于Transformer的通用化跨受试脑电情绪识别方法
Yi Ding,Chengxuan Tong,Shuailei Zhang et al.
Yi Ding et al.
Integrating prior knowledge of neurophysiology into neural network architecture enhances the performance of emotion decoding. While numerous techniques emphasize learning spatial and short-term temporal patterns, there has been a limited em...
Yuebin Xu,C L Philip Chen,Mengqi Wu et al.
Yuebin Xu et al.
Due to the complexity and self-evolutionary property of graph data in reality, graph learning methods require both validity to represent unstructured data and scalability to adapt to evolving graphs. However, current works have representati...