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K-core decomposition on super large graphs with limited resources., , , , , , , and . SAC, page 413-422. ACM, (2022)Analyzing Online Transaction Networks with Network Motifs., , , , , , and . KDD, page 3098-3106. ACM, (2022)An Experimental Evaluation of Large Scale GBDT Systems., , , and . Proc. VLDB Endow., 12 (11): 1357-1370 (2019)DimBoost: Boosting Gradient Boosting Decision Tree to Higher Dimensions., , , and . SIGMOD Conference, page 1363-1376. ACM, (2018)Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning., , , , , , , and . CoRR, (2023)P2CG: a privacy preserving collaborative graph neural network training framework., , , , , , , , and . VLDB J., 32 (4): 717-736 (July 2023)Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent., , , , , , , and . Proc. VLDB Endow., 16 (12): 3781-3794 (2023)KVSAgg: Secure Aggregation of Distributed Key-Value Sets., , , , , , , , and . ICDE, page 1775-1789. IEEE, (2023)SketchML: Accelerating Distributed Machine Learning with Data Sketches., , , and . SIGMOD Conference, page 1269-1284. ACM, (2018)SKCompress: compressing sparse and nonuniform gradient in distributed machine learning., , , , and . VLDB J., 29 (5): 945-972 (2020)