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Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework

Research article (Proceedings of the ACM Web Conference 2022, 2022) · cited 27× · AI/ML
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Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework

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Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework. Retrieved May 24, 2026, from https://4ort.xyz/entity/alleviating-cold-start-problem-in-ctr-prediction-with-a-variational-embedding-learning-framework
MLA “Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/alleviating-cold-start-problem-in-ctr-prediction-with-a-variational-embedding-learning-framework.
BibTeX @misc{4ortxyz_alleviating-cold-start-problem-in-ctr-prediction-with-a-variational-embedding-learning-framework_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework}}, year = {2026}, url = {https://4ort.xyz/entity/alleviating-cold-start-problem-in-ctr-prediction-with-a-variational-embedding-learning-framework}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework — https://4ort.xyz/entity/alleviating-cold-start-problem-in-ctr-prediction-with-a-variational-embedding-learning-framework (retrieved 2026-05-24)

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