债务人
发表于 2025-3-21 17:45:26
书目名称Machine Learning and Knowledge Discovery in Databases: Research Track影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0620550<br><br> <br><br>书目名称Machine Learning and Knowledge Discovery in Databases: Research Track影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0620550<br><br> <br><br>书目名称Machine Learning and Knowledge Discovery in Databases: Research Track网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0620550<br><br> <br><br>书目名称Machine Learning and Knowledge Discovery in Databases: Research Track网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0620550<br><br> <br><br>书目名称Machine Learning and Knowledge Discovery in Databases: Research Track被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0620550<br><br> <br><br>书目名称Machine Learning and Knowledge Discovery in Databases: Research Track被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0620550<br><br> <br><br>书目名称Machine Learning and Knowledge Discovery in Databases: Research Track年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0620550<br><br> <br><br>书目名称Machine Learning and Knowledge Discovery in Databases: Research Track年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0620550<br><br> <br><br>书目名称Machine Learning and Knowledge Discovery in Databases: Research Track读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0620550<br><br> <br><br>书目名称Machine Learning and Knowledge Discovery in Databases: Research Track读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0620550<br><br> <br><br>
Venules
发表于 2025-3-21 22:03:13
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野蛮
发表于 2025-3-22 01:57:52
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看法等
发表于 2025-3-22 07:15:38
Machine Learning and Knowledge Discovery in Databases: Research Track978-3-031-43415-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
MAZE
发表于 2025-3-22 11:16:45
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faculty
发表于 2025-3-22 15:42:09
Scoring Rule Nets: Beyond Mean Target Prediction in Multivariate Regressioncorrelation. We then show in a variety of experiments on both synthetic and real data, that Conditional CRPS often outperforms MLE, and produces results comparable to state-of-the-art non-parametric models, such as Distributional Random Forest (DRF).
鞠躬
发表于 2025-3-22 19:50:01
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ironic
发表于 2025-3-22 22:43:57
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起波澜
发表于 2025-3-23 03:28:15
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好忠告人
发表于 2025-3-23 06:36:57
Rényi Divergence Deep Mutual Learningll reach nearby local optima but continue searching within a bounded scope, which may help mitigate overfitting. Finally, our extensive empirical results demonstrate the advantage of combining DML and the Rényi divergence, leading to further improvement in model generalization.