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Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction., , , , , and . WWW, page 1119-1129. ACM, (2019)DeepFM: An End-to-End Wide & Deep Learning Framework for CTR Prediction., , , , , and . CoRR, (2018)Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data., , , , , , , and . CoRR, (2018)Memorize, Factorize, or be Naive: Learning Optimal Feature Interaction Methods for CTR Prediction., , , , , , and . ICDE, page 1450-1462. IEEE, (2022)MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction., , , , , , , , and . ICDE, page 727-740. IEEE, (2022)Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction., , , , , , , and . CoRR, (2022)Compressed Interaction Graph based Framework for Multi-behavior Recommendation., , , , , , , , , and 1 other author(s). WWW, page 960-970. ACM, (2023)Field-aware probabilistic embedding neural network for CTR prediction., , , , , , and . RecSys, page 412-416. ACM, (2018)Multi-Behavior Sequential Transformer Recommender., , , , , and . SIGIR, page 1642-1652. ACM, (2022)Unsupervised Learning Style Classification for Learning Path Generation in Online Education Platforms., , , , , , and . KDD, page 2997-3006. ACM, (2022)