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Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications., , , , , , , , , and 2 other author(s). KDD, page 5270-5281. ACM, (2023)IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research., , , , , and . KDD, page 4284-4295. ACM, (2023)Graph Neural Network Training and Data Tiering., , , , , and . KDD, page 3555-3565. ACM, (2022)PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction., , , , , , and . WWW, page 3784-3793. ACM, (2023)Split-merge: Using exponential neighborhood search for scheduling a batching machine., , , and . Comput. Oper. Res., (2015)An incomplete m-exchange algorithm for solving the large-scale multi-scenario knapsack problem., , , and . Comput. Oper. Res., 39 (9): 1988-2000 (2012)Finite-Time Control for Connected Vehicles Under Denial-of-Service Attacks: A Dynamic Event-Triggered Control Strategy., and . IEEE Access, (2022)Reliable Positioning Algorithm Using Two-Stage Adaptive Filtering in GPS-Denied Environments., , , and . J. Sensors, (2020)A Novel Nonlinear Algorithm for Non-Gaussian Noises and Measurement Information Loss in Underwater Navigation., , , , , and . IEEE Access, (2020)ColdGuess: A General and Effective Relational Graph Convolutional Network to Tackle Cold Start Cases., , , and . CoRR, (2022)