作者: Jiancheng Du1;Yang Gao1; (1School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China)
出处: IEEE Transactions on Knowledge and Data Engineering 2024 Vol.36 No.3 P1044-1055
关键词: Adaptation models;Task analysis;Data models;Training;Benchmark testing;Predictive models;Question answering (information retrieval);Domain Adaptation;Teacher Model;Benchmark Datasets;Target Domain;Good Initialization;Video Summarization;Parallel Corpus;Large Volume Of Information;Training Set;Validation Set;Natural Language;Data Generation;Transfer Learning;Scarcity Of Data;Latent Space;Adaptive Model;Question Answering;Language Model;Confidence Threshold;Variational Autoencoder;Pre-trained Language Models;Self-supervised Learning;Student Model;General Summary;Soft Labels;Source Documents;Types Of Queries;Smooth Distribution;Masked Language Model
摘要: Text summarizing is the task of reducing a document\'s length while maintaining its essential information. In the age of information explosion, how to ...
作者: Jiayue Geng1;Chen Ling2;Jinyu Liu2;Kexin Qiao1;Xiangjian Yi1;Liehuang Zhu1; (1School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, China 2School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China)
出处: IEEE Internet of Things Journal 2024 P1
关键词: Ciphers;Security;Internet of Things;Logic gates;Software;Resistance;Matrices
摘要: The proliferation of the Internet of Things (IoT) has amplified the necessity for secure data transmission. Lightweight block ciphers are pivotal in f ...
作者: Changyong Yu1;Yuhai Zhao1;Chu Zhao1;Jianyu Jin1;Keming Mao1;Guoren Wang2; (1College of Computer Science and Engineering, Northeastern University, Shenyang, China 2School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China)
出处: IEEE/ACM Transactions on Computational Biology and Bioinformatics 2024 Vol.21 No.1 P129-142
关键词: Bioinformatics;Genomics;Indexing;Costs;Task analysis;Memory management;Data structures
摘要: The De Bruijn graph (DBG) has been widely used in the algorithms for indexing or organizing read and reference sequences in bioinformatics. However, a ...
作者: Hao Wang1;Bo Tang2;Chi Harold Liu1;Shangqin Mao2;Jiahong Zhou2;Zipeng Dai1;Yaqi Sun2;Qianlong Xie2;Xingxing Wang2;Dong Wang2; (1School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China 2Meituan, Beijing, China)
出处: IEEE Transactions on Computers 2024 Vol.73 No.3 P815-828
关键词: Advertising;Resource management;Real-time systems;Reinforcement learning;Deep learning;Costs;Training;Deep Reinforcement Learning;Budget Allocation;Hierarchical Reinforcement Learning;Large-scale Data;Data Augmentation;Data Logger;Financial Constraints;Response Strategies;Auxiliary Loss;Deep Reinforcement Learning Framework;Bidding Strategy;High-level Planner;Resource Constraints;Lagrange Multiplier;Solution Space;Online Advertising;Allocation Scheme;Reward Function;Specific Channel;Mean Absolute Percentage Error;Bid Price;Conditional Variational Autoencoder;Off-line Training;Click-through;User Feedback;State-action Pair;Historical Statistics;Policy Learning;Online Prediction;Advertising Effectiveness
摘要: Online display advertising platforms service numerous advertisers by providing real-time bidding (RTB) for the scale of billions of ad requests every ...
作者:
Mixue Xie1;Shuang Li1;
出处: International Journal of Computer Vision 2024 Vol.132 No.4 P1417-1441
关键词: Domain shift;Domain adaptation;Semantic augmentation;Prototype constraint
摘要: The demand for reducing label annotation cost and adapting to new data distributions gives rise to the emergence of domain adaptation (DA). DA aims to ...
作者: Dapeng Yan1;Gangyi Ding1;Kexiang Huang1;Chongzhi Bai1;Lian He1;Longfei Zhang1; (1Key Laboratory of Digital Performance and Simulation Technology, School of Computer Science, Beijing Institute of Technology, Beijing 100081, China)
出处: Electronics 2024 Vol.13 No.5 P934
关键词: crowd simulation;social force model;pedestrian simulation;physics-infused machine learning
摘要: The traditional social force model (SFM) in crowd simulation experiences difficulty coping with the complexity of the crowd, limited by singular physi ...
作者: Xiaochen Liu1;Fan Li1;Yetong Cao1;Yu Wang2; (1School of Computer Science, Beijing Institute of Technology, Beijing, China 2Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA)
出处: IEEE Transactions on Mobile Computing 2024 P1-15
关键词: Braille;Wrist;Character recognition;Sensors;Piezoelectric transducers;Motion detection;Mobile computing
摘要: With the ever-increasing demand for improving communication and independence for visually impaired people, automatic Braille recognition has gained in ...
作者: Jiang, Xiurong1; Hou, Yifan1; Tian, Hui1; Zhu, Lin2; (1State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China;2School of Computer Science, Beijing Institute of Technology, Beijing, China)
出处: IET Computer Vision 2024 Vol.18 No.1 P15-32
关键词: image segmentation;object detection
摘要: Conventional RGB-T salient object detection treats RGB and thermal modalities equally to locate the common salient regions. However, the authors obser ...
作者:
Heyan Huang1;
出处: Knowledge-Based Systems 2024 P111677
摘要: As of present, the progress of conversational AI research has been greatly propelled by large-scale pre-trained language models. In particular, task-o ...
作者: Hao Wang1;Chi Harold Liu1;Haoming Yang1;Guoren Wang1;Kin K. Leung2; (1School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China 2Electrical and Electronic Engineering (EEE) Department, and the Computing Department, Imperial College, London, U.K.)
出处: IEEE/ACM Transactions on Networking 2024 Vol.32 No.1 P566-581
关键词: Sensors;Optimization;Crowdsensing;Autonomous aerial vehicles;Data integrity;Trajectory;Trajectory planning;Deep Reinforcement Learning;Multi-agent Deep Reinforcement Learning;Mobile Crowdsensing;Unmanned Aerial Vehicles;Real-world Datasets;Specific Threshold;Cooperative Mechanism;Trajectory Planning;Intrinsic Rewards;Distributed Architecture;Optimization Problem;Deep Neural Network;Emergency Response;Time Data;Temporal Features;Lack Of Models;Path Planning;Path Loss;Penalty Function;Limited Capability;Policy Network;Deep Reinforcement Learning Method;Temporal Model;Proximal Policy Optimization;Division Of Work;Multiple Unmanned Aerial Vehicles;Reconfigurable Intelligent Surface;L2 Loss;Trajectory Design;Unmanned Aerial Vehicle Trajectory
摘要: Unmanned aerial vehicle (UAV) crowdsensing (UCS) is an emerging data collection paradigm to provide reliable and high quality urban sensing services, ...