咨询与建议

限定检索结果

文献类型

  • 554 篇 期刊文献
  • 494 篇 会议
  • 1 册 图书

馆藏范围

  • 1,049 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 732 篇 工学
    • 584 篇 计算机科学与技术...
    • 486 篇 软件工程
    • 165 篇 信息与通信工程
    • 104 篇 控制科学与工程
    • 78 篇 生物工程
    • 55 篇 生物医学工程(可授...
    • 50 篇 机械工程
    • 47 篇 电气工程
    • 47 篇 电子科学与技术(可...
    • 39 篇 化学工程与技术
    • 33 篇 光学工程
    • 23 篇 仪器科学与技术
    • 22 篇 航空宇航科学与技...
    • 18 篇 交通运输工程
    • 15 篇 土木工程
    • 14 篇 动力工程及工程热...
    • 14 篇 网络空间安全
  • 379 篇 理学
    • 261 篇 数学
    • 89 篇 生物学
    • 60 篇 统计学(可授理学、...
    • 47 篇 物理学
    • 39 篇 化学
    • 30 篇 系统科学
  • 251 篇 管理学
    • 134 篇 管理科学与工程(可...
    • 120 篇 图书情报与档案管...
    • 36 篇 工商管理
  • 40 篇 医学
    • 32 篇 临床医学
    • 24 篇 基础医学(可授医学...
    • 19 篇 药学(可授医学、理...
  • 15 篇 法学
    • 13 篇 社会学
  • 12 篇 农学
  • 5 篇 经济学
  • 5 篇 教育学
  • 3 篇 文学
  • 3 篇 艺术学
  • 2 篇 军事学
  • 1 篇 哲学

主题

  • 52 篇 computer science
  • 44 篇 educational inst...
  • 44 篇 laboratories
  • 43 篇 knowledge engine...
  • 41 篇 educational tech...
  • 26 篇 data mining
  • 24 篇 computer science...
  • 22 篇 semantics
  • 17 篇 feature extracti...
  • 15 篇 reinforcement le...
  • 15 篇 contrastive lear...
  • 14 篇 image segmentati...
  • 13 篇 deep learning
  • 13 篇 artificial intel...
  • 12 篇 ontologies
  • 11 篇 topology
  • 10 篇 recommender syst...
  • 10 篇 authentication
  • 10 篇 training
  • 9 篇 genetic algorith...

机构

  • 438 篇 college of compu...
  • 287 篇 key laboratory o...
  • 84 篇 key laboratory o...
  • 43 篇 key laboratory o...
  • 36 篇 key laboratory o...
  • 35 篇 college of softw...
  • 33 篇 school of artifi...
  • 31 篇 college of compu...
  • 29 篇 key laboratory o...
  • 24 篇 jilin university...
  • 20 篇 jilin university...
  • 19 篇 jilin university...
  • 19 篇 key laboratory o...
  • 19 篇 key laboratory o...
  • 18 篇 school of comput...
  • 16 篇 college of compu...
  • 15 篇 key laboratory o...
  • 15 篇 school of cyber ...
  • 15 篇 the college of c...
  • 14 篇 key laboratory o...

作者

  • 39 篇 yang bo
  • 36 篇 sun geng
  • 31 篇 li ximing
  • 27 篇 ouyang jihong
  • 26 篇 liu dayou
  • 25 篇 dantong ouyang
  • 24 篇 niyato dusit
  • 23 篇 bo yang
  • 22 篇 ouyang dantong
  • 22 篇 yanheng liu
  • 22 篇 li jiahui
  • 21 篇 chen haipeng
  • 21 篇 huang lan
  • 21 篇 liu yanheng
  • 20 篇 li xiongfei
  • 19 篇 guan renchu
  • 19 篇 liu da-you
  • 19 篇 da-you liu
  • 18 篇 dayou liu
  • 17 篇 chang yi

语言

  • 913 篇 英文
  • 97 篇 其他
  • 39 篇 中文
检索条件"机构=Key Laboratory of Symbolic Computing and Knowledge Engineering of"
1049 条 记 录,以下是111-120 订阅
排序:
Stable Learning via Triplex Learning
IEEE Transactions on Artificial Intelligence
收藏 引用
IEEE Transactions on Artificial Intelligence 2024年 第10期5卷 5267-5276页
作者: Yang, Shuai Jiang, Tingting Dang, Qianlong Gu, Lichuan Wu, Xindong Anhui Agricultural University School of Information and Artificial Intelligence Hefei230036 China Anhui Provincial Engineering Research Center for Agricultural Information Perception and Intelligent Computing Hefei230036 China Northwest A & F University College of Science Yangling712100 China Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data The Ministry of Education of China Hefei230601 China Hefei University of Technology School of Computer Science and Information Engineering Hefei230601 China
Stable learning aims to learn a model that generalizes well to arbitrary unseen target domain by leveraging a single source domain. Recent advances in stable learning have focused on balancing the distribution of conf... 详细信息
来源: 评论
Medical Scene Graphs and Reasoning
Medical Scene Graphs and Reasoning
收藏 引用
2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021
作者: Cao, Chuxue He, Yiming Chen, Yuzhen Song, Chunli Ling, Hao Guan, Renchu Feng, Xiaoyue Jilin University The Key Laboratory for Symbolic Computation and Knowledge Engineering of the Ministry of Education College of Software Changchun China The Second Hospital of Jilin University Changchun China Jilin University The Key Laboratory for Symbolic Computation and Knowledge Engineering of the Ministry of Education College of Computer Science and Technology Changchun China
Medical scene graph contributes to cognitive tasks such as question answering. An automatic medical scene graph generator can annotate medical images with scene graphs conveniently. An end-to-end model is proposed, wh... 详细信息
来源: 评论
Improving Local Search for Pseudo Boolean Optimization by Fragile Scoring Function and Deep Optimization  29
Improving Local Search for Pseudo Boolean Optimization by Fr...
收藏 引用
29th International Conference on Principles and Practice of Constraint Programming, CP 2023
作者: Zhou, Wenbo Zhao, Yujiao Wang, Yiyuan Cai, Shaowei Wang, Shimao Wang, Xinyu Yin, Minghao School of Information Science and Technology Northeast Normal University Changchun China Key Laboratory of Applied Statistics of MOE Northeast Normal University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of MOE Jilin University Changchun China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China
Pseudo-Boolean optimization (PBO) is usually used to model combinatorial optimization problems, especially for some real-world applications. Despite its significant importance in both theory and applications, there ar... 详细信息
来源: 评论
Learning generalizable agents via saliency-guided features decorrelation  23
Learning generalizable agents via saliency-guided features d...
收藏 引用
Proceedings of the 37th International Conference on Neural Information Processing Systems
作者: Sili Huang Yanchao Sun Jifeng Hu Siyuan Guo Hechang Chen Yi Chang Lichao Sun Bo Yang Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education and School of Artificial Intelligence Jilin University China Department of Computer Science University of Maryland College Park School of Artificial Intelligence Jilin University China Lehigh University Bethlehem Pennsylvania Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education
In visual-based Reinforcement Learning (RL), agents often struggle to generalize well to environmental variations in the state space that were not observed during training. The variations can arise in both task-irrele...
来源: 评论
BA-LORA: BIAS-ALLEVIATING LOW-RANK ADAPTATION TO MITIGATE CATASTROPHIC INHERITANCE IN LARGE LANGUAGE MODELS
arXiv
收藏 引用
arXiv 2024年
作者: Chang, Yupeng Chang, Yi Wu, Yuan School of Artificial Intelligence Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University China International Center of Future Science Jilin University China
Large language models (LLMs) have demonstrated remarkable proficiency across various natural language processing (NLP) tasks. However, adapting LLMs to downstream applications requires computationally intensive and me... 详细信息
来源: 评论
ExplSched: Maximizing Deep Learning Cluster Efficiency for Exploratory Jobs
ExplSched: Maximizing Deep Learning Cluster Efficiency for E...
收藏 引用
IEEE International Conference on Cluster computing
作者: Hongliang Li Hairui Zhao Zhewen Xu Xiang Li Haixiao Xu College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education Changchun China High Performance Computing Center Jilin University China
Resource management for Deep Learning (DL) clusters is essential for system efficiency and model training quality. Existing schedulers provided by DL frameworks are mostly adaptations from traditional HPC clusters and...
来源: 评论
Enhancing Unsupervised Graph Few-shot Learning via Set Functions and Optimal Transport
arXiv
收藏 引用
arXiv 2025年
作者: Liu, Yonghao Giunchiglia, Fausto Li, Ximing Huang, Lan Feng, Xiaoyue Guan, Renchu College of Computer Science and Technology Jilin University Changchun China Department of Information Engineering and Computer Science University of Trento Trento Italy Key Laboratory of Symbolic Computation and Knowledge Engineering The Ministry of Education China
Graph few-shot learning has garnered significant attention for its ability to rapidly adapt to downstream tasks with limited labeled data, sparking considerable interest among researchers. Recent advancements in graph... 详细信息
来源: 评论
From Incomplete Coarse-Grained to Complete Fine-Grained: A Two-Stage Framework for Spatiotemporal Data Reconstruction
arXiv
收藏 引用
arXiv 2024年
作者: Sun, Ziyu Su, Haoyang Wang, En Yang, Funing Yang, Yongjian Liu, Wenbin The College of Computer Science and Technology Jilin University Changchun130012 China The Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China
With the rapid development of various sensing devices, spatiotemporal data is becoming increasingly important nowadays. However, due to sensing costs and privacy concerns, the collected data is often incomplete and co... 详细信息
来源: 评论
Reusable Generator Data-Free knowledge Distillation with Hard Loss Simulation for Image Classification
SSRN
收藏 引用
SSRN 2024年
作者: Sun, Yafeng Wang, Xingwang Huang, Junhong Chen, Shilin Hou, Minghui College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China
In many image classification scenarios where knowledge distillation (KD) is applied, multiple users need to train various student models that conform to the device's computational limitations at different times. H... 详细信息
来源: 评论
AWEQ: Post-Training Quantization with Activation-Weight Equalization for Large Language Models
arXiv
收藏 引用
arXiv 2023年
作者: Li, Baisong Wang, Xingwang Xu, Haixiao School of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University China
Large language models(LLMs) excellent performance across a variety of tasks, but they come with significant computational and storage costs. Quantizing these models is an effective way to alleviate this issue. However... 详细信息
来源: 评论