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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
posted @ 2023-03-02 20:17 馒头and花卷 阅读(289) 评论(0) 推荐(0)
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
posted @ 2023-02-27 15:37 馒头and花卷 阅读(252) 评论(0) 推荐(0)
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
posted @ 2023-02-26 19:49 馒头and花卷 阅读(295) 评论(0) 推荐(0)
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
posted @ 2023-02-26 15:10 馒头and花卷 阅读(93) 评论(0) 推荐(0)
摘要: Chen J., Lian D., Jin B., Zhang K. and Chen E. Learning recommenders for implicit feedback with importance resampling. In ACM Web Conference (WWW), 20 阅读全文
posted @ 2023-02-25 12:05 馒头and花卷 阅读(83) 评论(0) 推荐(0)
摘要: Kang W. and McAuley J. Self-attentive sequential recommendation. In IEEE International Conference on Data Mining (ICDM), 2018. 概 Transformer 最初用在序列推荐之 阅读全文
posted @ 2023-02-24 11:14 馒头and花卷 阅读(212) 评论(0) 推荐(0)
摘要: Lian D., Liu Q. and Chen E. Personalized ranking with importance sampling. In International World Wide Web Conference (WWW), 2020. 概 作者总结了 4 种基于 impor 阅读全文
posted @ 2023-02-19 18:25 馒头and花卷 阅读(120) 评论(1) 推荐(0)
摘要: Zhang W., Chen T., Wang J. and Yu Y. Optimizing top-n collaborative filtering via dynamic negative item sampling. In International ACM SIGIR Conferenc 阅读全文
posted @ 2023-02-19 14:18 馒头and花卷 阅读(169) 评论(0) 推荐(0)
摘要: Sun F., Liu J., Wu J., Pei C., Lin X., Ou W. and Jiang P. BERT4Rec: Sequential recommendation with bidirectional encoder representations from transfor 阅读全文
posted @ 2023-02-11 15:36 馒头and花卷 阅读(260) 评论(0) 推荐(0)
摘要: Wu S., Tang Y., Zhu Y., Wang L., Xie X. and Tan T. Session-based recommendation with graph neural networks. In AAAI Conference on Advancement of Artif 阅读全文
posted @ 2023-02-10 20:42 馒头and花卷 阅读(101) 评论(0) 推荐(0)
摘要: Hidasi B., Karatzoglou A., Baltrunas L. and Tikk D. Session-based recommendations with recurrent neural networks. In International Conference on Learn 阅读全文
posted @ 2023-02-10 14:39 馒头and花卷 阅读(487) 评论(0) 推荐(0)
摘要: Yu F., Liu Q., Wu S., Wang L. and Tan T. A dynamic recurrent model for next basket recommendation. International ACM SIGIR Conference on Research and 阅读全文
posted @ 2023-02-08 16:48 馒头and花卷 阅读(70) 评论(0) 推荐(0)
摘要: Zhang J., Chow C. and Li Y. In ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATITAL), 2014. 概 结合 social 阅读全文
posted @ 2023-01-10 13:56 馒头and花卷 阅读(45) 评论(0) 推荐(0)
摘要: 修饰 表品质 褒义 | Word | 含义 | 例句 | 近义词 | | : : | : : | : : | : : | | superior | adj. 上级的;优秀的,出众的;高傲的; | In this aspect, content filtering is superior. | sur 阅读全文
posted @ 2022-12-15 14:26 馒头and花卷 阅读(152) 评论(0) 推荐(0)
摘要: Austin J., Johnson D. D., Ho J., Tarlow D. and van den Berg R. Structured denoising diffusion models in discrete state-spaces. In Advances in Neural I 阅读全文
posted @ 2022-12-14 19:54 馒头and花卷 阅读(1981) 评论(0) 推荐(3)
摘要: Choi J., Hong S., Park N. and Cho S. GREAD: graph neural reaction-diffusion equations. arXiv preprint arXiv: arXiv:2211.14208 概 作者提出了一种基于 reaction-dif 阅读全文
posted @ 2022-12-01 16:53 馒头and花卷 阅读(372) 评论(0) 推荐(0)
摘要: Chen R. T. Q., Rubanova Y., Bettencourt J. and Duvenaud D. Neural ordinary differential equations. In Advances in Neural Information Processing System 阅读全文
posted @ 2022-11-30 20:26 馒头and花卷 阅读(325) 评论(0) 推荐(0)
摘要: 本文梳理一下 VAE -> Flow -> Diffusion 的过程 [9]. 需要声明的是, 个人是没有进行过这方面的实践的, 相关的理论只是也比较匮乏, 这里只是一个对这些从事贝叶斯网络研究满怀敬意的人的纸上谈兵了. 扩散模型没有被时间洪流所掩埋, 真是让人感动的事情. 符号说明 $\bm{x 阅读全文
posted @ 2022-11-27 18:54 馒头and花卷 阅读(615) 评论(0) 推荐(0)
摘要: Choi J., Hong S., Park N. and Cho S. Perturbation-recovery method for recommendation. arXiv preprint arXiv:2211.09324, 2022. 概 本文将最近很火的 diffusion mode 阅读全文
posted @ 2022-11-23 19:40 馒头and花卷 阅读(152) 评论(0) 推荐(0)
摘要: Choi J., Jeon J. and Park N. LT-OCF: Learnable-time ode-based collaborative filtering. In International Conference on Information and Knowledge Manage 阅读全文
posted @ 2022-11-23 17:41 馒头and花卷 阅读(99) 评论(0) 推荐(0)
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