中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共50条，第1-10条 帮助

限定条件    
已选(0)清除 条数/页：   排序方式：
Generalized Embedding Machines for Recommender Systems 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 3, 页码: 571-584
作者:  Enneng Yang;  Xin Xin;  Li Shen;  Yudong Luo;  Guibing Guo
Adobe PDF(1617Kb)  |  收藏  |  浏览/下载：27/10  |  提交时间：2024/05/23
Feature interactions, high-order interaction, factorization machine (FM), recommender system, graph neural network (GNN)  
An Empirical Study on Google Research Football Multi-agent Scenarios 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 3, 页码: 549-570
作者:  Yan Song;  He Jiang;  Zheng Tian;  Haifeng Zhang;  Yingping Zhang;  Jiangcheng Zhu;  Zonghong Dai;  Weinan Zhang;  Jun Wang
Adobe PDF(24588Kb)  |  收藏  |  浏览/下载：26/7  |  提交时间：2024/05/23
Multi-agent reinforcement learning (RL), distributed RL system, population-based training, reward shaping, game theory  
Ripple Knowledge Graph Convolutional Networks for Recommendation Systems 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 3, 页码: 481-494
作者:  Chen Li;  Yang Cao;  Ye Zhu;  Debo Cheng;  Chengyuan Li;  Yasuhiko Morimoto
Adobe PDF(3688Kb)  |  收藏  |  浏览/下载：22/11  |  提交时间：2024/05/23
Deep learning, recommendation systems, knowledge graph, graph convolutional networks (GCNs), graph neural networks (GNNs)  
Parsing Objects at a Finer Granularity: A Survey 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 3, 页码: 431-451
作者:  Yifan Zhao;  Jia Li;  Yonghong Tian
Adobe PDF(1743Kb)  |  收藏  |  浏览/下载：13/7  |  提交时间：2024/05/23
Finer granularity, visual parsing, part segmentation, fine-grained object recognition, part relationship  
Distributed Deep Reinforcement Learning: A Survey and a Multi-player Multi-agent Learning Toolbox 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 3, 页码: 411-430
作者:  Qiyue Yin;  Tongtong Yu;  Shengqi Shen;  Jun Yang;  Meijing Zhao;  Wancheng Ni;  Kaiqi Huang;  Bin Liang;  Liang Wang
Adobe PDF(2923Kb)  |  收藏  |  浏览/下载：21/9  |  提交时间：2024/05/23
Deep reinforcement learning, distributed machine learning, self-play, population-play, toolbox  
A Soft Sensor with Light and Efficient Multi-scale Feature Method for Multiple Sampling Rates in Industrial Processing 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 2, 页码: 400-410
作者:  Dezheng Wang;  Yinglong Wang;  Fan Yang;  Liyang Xu;  Yinong Zhang;  Yiran Chen;  Ning Liao
Adobe PDF(3208Kb)  |  收藏  |  浏览/下载：35/5  |  提交时间：2024/04/23
Multi-scale, feature extractor, deep neural network (DNN), multirate sampled industrial processes, prediction  
GraphFlow+: Exploiting Conversation Flow in Conversational Machine Comprehension with Graph Neural Networks 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 2, 页码: 272-282
作者:  Jing Hu;  Lingfei Wu;  Yu Chen;  Po Hu;  Mohammed J. Zaki
Adobe PDF(1612Kb)  |  收藏  |  浏览/下载：29/7  |  提交时间：2024/04/23
Conversational machine comprehension (MC), reading comprehension, question answering, graph neural networks (GNNs), natural language processing (NLP)  
Corporate Credit Ratings Based on Hierarchical Heterogeneous Graph Neural Networks 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 2, 页码: 257-271
作者:  Bo-Jing Feng;  Xi Cheng;  Hao-Nan Xu;  Wen-Fang Xue
Adobe PDF(2621Kb)  |  收藏  |  浏览/下载：43/10  |  提交时间：2024/04/23
Corporate credit rating, hierarchical relation, heterogeneous graph neural networks, adversarial learning  
A Comprehensive Overview of CFN From a Commonsense Perspective 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 2, 页码: 239-256
作者:  Ru Li;  Yunxiao Zhao;  Zhiqiang Wang;  Xuefeng Su;  Shaoru Guo;  Yong Guan;  Xiaoqi Han;  Hongyan Zhao
Adobe PDF(2392Kb)  |  收藏  |  浏览/下载：21/7  |  提交时间：2024/04/23
Chinese FrameNet (CFN), commonsense, scenario commonsense, frame, knowledge  
The Life Cycle of Knowledge in Big Language Models: A Survey 期刊论文
Machine Intelligence Research, 2024, 卷号: 21, 期号: 2, 页码: 217-238
作者:  Boxi Cao;  Hongyu Lin;  Xianpei Han;  Le Sun
Adobe PDF(1430Kb)  |  收藏  |  浏览/下载：29/4  |  提交时间：2024/04/23
Pre-trained language model, knowledge acquisition, knowledge representation, knowledge probing, knowledge editing, knowledge application