变化无常 发表于 2025-3-28 16:42:47
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http://reply.papertrans.cn/63/6205/620490/620490_42.pngApraxia 发表于 2025-3-29 00:51:51
Smoothing Categorical Dataperiments we show that our approach preserves the large scale structure of a dataset well. That is, the smoothed dataset is simpler while the original and smoothed datasets share the same large scale structure.Left-Atrium 发表于 2025-3-29 05:04:21
http://reply.papertrans.cn/63/6205/620490/620490_44.pngimplore 发表于 2025-3-29 07:52:56
Combining Subjective Probabilities and Data in Training Markov Logic Networkssly used Gaussian priors over weights. We show how one can learn weights in an MLN by combining subjective probabilities and training data, without requiring that the domain expert provides consistent knowledge. Additionally, we also provide a formalism for capturing conditional subjective probabiliWITH 发表于 2025-3-29 14:39:47
Score-Based Bayesian Skill Learningns demonstrate that the new score-based models (a) provide more accurate win/loss probability estimates than TrueSkill when training data is limited, (b) provide competitive and often better win/loss classification performance than TrueSkill, and (c) provide reasonable score outcome predictions withdebris 发表于 2025-3-29 18:46:48
Hypergraph Spectra for Semi-supervised Feature Selectionestablish a novel hypergraph framework which is used for characterizing the multiple relationships within a set of samples. Thus, the structural information latent in the data can be more effectively modeled. Secondly, we derive a hypergraph subspace learning view of feature selection which castingHEED 发表于 2025-3-29 22:50:36
http://reply.papertrans.cn/63/6205/620490/620490_48.png欺骗手段 发表于 2025-3-30 01:58:53
Machine Learning and Knowledge Discovery in DatabasesEuropean Conference,CURT 发表于 2025-3-30 06:46:30
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