馒头and花卷

摘要： Wu H., Zhang Y., Ma C., Lyu F., Diaz F. and Liu X. A survey of diversification techniques in search and recommendation. arXiv preprint arXiv:2212.1446 阅读全文

摘要： Meymandpour R. and Davis J. G. Measuring the diversity of recommendations: a preference-aware approach for evaluating and adjusting diversity. Knowled 阅读全文

摘要： Clarke C. L. A., Kolla M., Cormack G. V., Vechtomova O., Ashkan A., B\ddot{u}ttcher S. and MacKinnon I. Novelty and diversity in information retrieval 阅读全文

摘要： Zhai C., Cohen W. W. and Lafferty J. Beyond independent relevance: methods and evaluation metrics for subtopic retrieval. In International ACM SIGIR C 阅读全文

摘要： Wilhelm M., Ramanathan A., Bonomo A., Jain S., Chi E. H. and Gillenwater J. Practical diversified recommendations on youtube with determinantal point 阅读全文

摘要： Carbonell J. and Goldstein. The use of MMR, diversity-based reranking for reordering documents and producing summaries. In International ACM SIGIR Con 阅读全文

摘要： Rombach R., Blattmann A., Lorenz D., Esser P. and Ommer B. High-resolution image synthesis with latent diffusion models. In IEEE Computer Vision and P 阅读全文

摘要： Zhang M. and Chen Y. Inductive matrix completion based on graph neural networks. In International Conference on Learning Representations (ICLR) 概 本文介绍 阅读全文

摘要： Zhang M., Cui Z., Jiang S. and Chen Y. Beyond link prediction: Predicting hyperlinks in adjacency space. In AAAI Conference on Advancement of Artifici 阅读全文

摘要： Zhang M. and Chen Y. Link prediction based on graph neural networks. In Advances in Neural Information Processing Systems (NIPS), 2018. 概 这篇工作 的延续的工作. 阅读全文

摘要： Zhang M. and Chen Y. Weisfeiler-Lehman neural machine for link prediction. In ACM International Conference on Knowledge Discovery and Data Mining (KDD 阅读全文

摘要： Pan L., Shi C., Dokmani{'c} I. Neural link prediction with walk pooling. In International Conference on Learning Representations (ICLR), 2022. 概 作者认为 阅读全文

摘要： Cai X., Huang C., Xia L. and Ren X. LightGCL: Simple yet effective graph contrastive learning for recommendation. In International Conference on Learn 阅读全文

摘要： Song J., Meng C. and Ermon S. Denoising diffusion implicit models. In International Conference on Learning Representations (ICLR), 2021. 概 DDIM 从另一种观点 阅读全文

摘要： Choi J., Lee J., Shin C., Kim S., Kim H. and Yoon S. Perception prioritized training of diffusion models. In IEEE Computer Vision and Pattern Recognit 阅读全文

摘要： Gong S., Li M., Feng J., Wu Z. and Kong L. DiffuSeq: Sequence to sequence text generation with diffusion models. In International Conference on Learni 阅读全文

摘要： Li X. L., Thickstun J., Gulrajani I., Liang P. and Hashimoto T. B. Diffusion-lm improves controllable text generation. arXiv preprint arXiv:2205.14217 阅读全文

摘要： [TOC] > [Shi W., Chen J., Feng F., Zhang J., Wu J., Gao C. and He X. On the theories behind hard negative sampling for recommendation. In Internationa 阅读全文

摘要： Zhu D., Li G., Wang B., Wu X. and Yang T. When AUC meets DRO: Optimizing partial auc for deep learning with non-convex convergence guarantee. In Inter 阅读全文

摘要： Duchi J. C. and Namkoong H. Learning models with uniform performance via distributionally robust optimization. The Annals of Statistics, 49(3), 1378-1 阅读全文