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随笔分类 -  Robust Learning

摘要:目录概符号说明AirGNN代码 Liu X., Ding J., Jin W., Xu H., Ma Y., Liu Z. and Tang J. Graph neural networks with adaptive residual. NIPS, 2021. 概 基于 UGNN 框架的一个更加鲁 阅读全文
posted @ 2023-10-31 19:38 馒头and花卷 阅读(37) 评论(1) 推荐(0) 编辑
摘要:Wang L. and Joachims T. Uncertainty quantification for fairness in two-stage recommender systems. In International World Wide Web Conference (WWW), 20 阅读全文
posted @ 2023-03-29 15:32 馒头and花卷 阅读(61) 评论(0) 推荐(0) 编辑
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(71) 评论(0) 推荐(0) 编辑
摘要:Ren Y., Tang H. and Zhu S. Unbiased learning to rank with biased continuous feedback. In International Conference on Information and Knowledge Managem 阅读全文
posted @ 2022-10-25 21:20 馒头and花卷 阅读(165) 评论(0) 推荐(0) 编辑
摘要:Liu S., Ying R., Dong H., Lin L., Chen J., Wu D. How powerful is implicit denoising in graph neural networks? arXiv preprint arXiv: 2209.14514, 2022. 阅读全文
posted @ 2022-10-19 16:38 馒头and花卷 阅读(89) 评论(0) 推荐(0) 编辑
摘要:Zhu M., Wang X., Shi C., Ji H. and Cui P. Interpreting and unifying graph neural networks with an optimization framework. In International World Wide 阅读全文
posted @ 2022-10-18 10:38 馒头and花卷 阅读(68) 评论(0) 推荐(0) 编辑
摘要:Zhao L. and Akoglu L. Connecting graph convolution and graph pca. 2022. 概 从 graph-regularized PCA 角度提出一种 GCN 的 message passing layer. 符号说明 ˜A 阅读全文
posted @ 2022-10-17 18:22 馒头and花卷 阅读(36) 评论(0) 推荐(0) 编辑
摘要:Liu X., Jin W., Ma Y., Li Y., Li Y., Liu H., Wang Y., Yan M. and Tang J. Elastic graph neural networks. In International Conference on Machine Learnin 阅读全文
posted @ 2022-10-17 16:05 馒头and花卷 阅读(64) 评论(0) 推荐(0) 编辑
摘要:Tan J., Geng S., Fu Z., Ge Y., Xu S., Li Y. and Zhang Y. Learning and evaluating graph neural network explanations based on counterfactual and factual 阅读全文
posted @ 2022-10-14 22:25 馒头and花卷 阅读(113) 评论(0) 推荐(0) 编辑
摘要:Ying R., Bourgeois D., You J., Zitnik M. and Leskovec J. GNNExplainer: generating explanations for graph neural networks. In Advances in Neural Inform 阅读全文
posted @ 2022-10-11 17:06 馒头and花卷 阅读(210) 评论(0) 推荐(0) 编辑
摘要:Dong Y., Liu N., Jalaian B. and Li J. EDITS: modeling and mitigating data bias for graph neural networks. In International World Wide Web Conference ( 阅读全文
posted @ 2022-10-09 16:07 馒头and花卷 阅读(82) 评论(0) 推荐(0) 编辑
摘要:Lahoti P., Beutel A., Chen J., Lee K., Prost F., Thain N., Wang X. and CHi E. H. Fairness without demographics through adversarially reweighted learni 阅读全文
posted @ 2022-10-08 12:45 馒头and花卷 阅读(78) 评论(0) 推荐(0) 编辑
摘要:Dai E. and Wang S. Towards self-explainable graph neural network. In International Conference on Information and Knowledge Management (CIKM), 2021. 概 阅读全文
posted @ 2022-10-07 15:49 馒头and花卷 阅读(168) 评论(0) 推荐(0) 编辑
摘要:Zhu D., Zhang Z., Cui P. and Zhu W. Robust graph convolutional networks against adversarial attacks. In ACM International Conference on Knowledge Disc 阅读全文
posted @ 2022-10-07 11:07 馒头and花卷 阅读(114) 评论(0) 推荐(0) 编辑
摘要:Xu K., Chen H., Liu S., Chen P., Weng T., Hong M. and Lin X. Topology attack and defense for graph neural networks: an optimization perspective. In In 阅读全文
posted @ 2022-10-06 14:37 馒头and花卷 阅读(194) 评论(0) 推荐(0) 编辑
摘要:Olatunji I. E., Funke T. and Khosla M. Releasing graph neural networks with differential privacy guarantees. In ACM Symposium on Neural Gaze Detection 阅读全文
posted @ 2022-10-05 14:02 馒头and花卷 阅读(52) 评论(0) 推荐(0) 编辑
摘要:Papernot N., Abadi M., Erlingsson U., Goodfellow I. and Talwar K. Semi-supervised knowledge transfer for deep learning from private training data. In 阅读全文
posted @ 2022-10-05 13:31 馒头and花卷 阅读(117) 评论(0) 推荐(0) 编辑
摘要:目录概符号说明MetricsSampled-based ranking例子Sampled metrics Krichene W. and Rendle S. On sampled metrics for item recommendation. KDD, 2020. 概 作者对推荐系统中 sampl 阅读全文
posted @ 2022-09-11 16:18 馒头and花卷 阅读(50) 评论(0) 推荐(0) 编辑
摘要:Ding S., Wu P., Feng F., Wang Y., He X., Liao Y. and Zhang Y. Addressing unmeasured confounder for recommendation with sensitivity analysis. In ACM SI 阅读全文
posted @ 2022-08-19 21:24 馒头and花卷 阅读(112) 评论(0) 推荐(0) 编辑
摘要:Chen J., Dong H., Qiu Y., He X., Xin X., Chen L., Lin G. and Yang K. AutoDebias: learning to debias for recommendation. In International ACM SIGIR Con 阅读全文
posted @ 2022-08-19 18:07 馒头and花卷 阅读(245) 评论(0) 推荐(1) 编辑

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