The ACM SIGKDD (International Conference on Data Mining and Knowledge Discovery, referred to as KDD) conference began in 1989. It is the oldest and largest international top academic conference in the field of data mining. The conference on concepts such as packages attracts a large number of research scholars and practitioners in the fields of data mining, machine learning, big data and artificial intelligence every year.
AMiner sorted out the conference papers included in KDD2023 through AI technology, and today I am sharing a paper on the theme of representation learning! (Due to space constraints, this article only shows some papers. Click to read the original text to go directly to the KDD summit page to view all papers)
1.DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection
Link: https://www.aminer.cn/pub/6492753bd68f896efa888f46/
2.GENERALIZED MATRIX LOCAL LOW RANK REPRESENTATION BY RANDOM PROJECTION AND SUBMATRIX PROPAGATION
Link: https://www.aminer.cn/pub/6433f6bc90e50fcafd6efdfd/
3.Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-source Knowledge Graphs
Link: https://www.aminer.cn/pub/647eaf51d68f896efad41d32/
4.Task Relation-aware Continual User Representation Learning
Link: https://www.aminer.cn/pub/647eaf35d68f896efad40763/
5.Dense Representation Learning and Retrieval for Tabular Data Prediction
Link: https://www.aminer.cn/pub/64af99fd3fda6d7f065a62e9/
6.Efficient and Effective Edge-wise Graph Representation Learning
Link: https://www.aminer.cn/pub/64af99fe3fda6d7f065a63b4/
7.CARL-G: Clustering-Accelerated Representation Learning on Graphs
Link: https://www.aminer.cn/pub/64af99fe3fda6d7f065a63ce/
8.LightPath: Lightweight and Scalable Path Representation Learning
Link: https://www.aminer.cn/pub/64af9a0b3fda6d7f065a70cd/
9.Urban Region Representation Learning with OpenStreetMap Building Footprints
Link: https://www.aminer.cn/pub/64af9a0b3fda6d7f065a70d1/
10.Representation Learning on Hyper-Relational and Numeric Knowledge Graphs with Transformers
Link: https://www.aminer.cn/pub/647572e0d68f896efa7b7983/
11.Expert Knowledge-Aware Image Difference Graph Representation Learning for Difference-Aware Medical Visual Question Answering
Link: https://www.aminer.cn/pub/64af9a023fda6d7f065a686d/
12.DyTed: Disentangled Representation Learning for Discrete-time Dynamic Graph
Link: https://www.aminer.cn/pub/64af9a093fda6d7f065a6eac/
13.Heterformer: Transformer-based Deep Node Representation Learning on Heterogeneous Text-Rich Networks
Link: https://www.aminer.cn/pub/64af9a093fda6d7f065a6eb0/
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KDD Conference: https://www.aminer.cn/conf/5ea1b22bedb6e7d53c00c41b/KDD2023