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Titlebook: Machine Learning and Data Mining in Pattern Recognition; 13th International C Petra Perner Conference proceedings 2017 Springer Internation

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發(fā)表于 2025-3-30 09:44:49 | 只看該作者
Importance of Recommendation Policy Space in Addressing Click Sparsity in Personalized Advertisemenstic and stochastic policy spaces and conduct extensive experiments on public and proprietary datasets to illustrate the improvement in click-through-rate (CTR) obtained by using the ranker-based policy over classifier-based policy.
52#
發(fā)表于 2025-3-30 12:56:43 | 只看該作者
Global Flow and Temporal-Shape Descriptors for Human Action Recognition from 3D Reconstruction Datauding temporal information, is also proposed. The latter descriptor efficiently addresses the inherent problems of temporal alignment and compact representation, while also being robust in the presence of noise. Experimental results using public datasets demonstrate the efficiency of the proposed ap
53#
發(fā)表于 2025-3-30 18:47:35 | 只看該作者
,Towards an Efficient Method of Modeling “Next Best Action” for Digital Buyer’s Journey in B2B,ion using a novel ensemble method that aims to predict the best digital asset to target customers as a next action. The paper provides a unique approach to translate the propensity model at an email address level into a segment that can target a group of email addresses. In the first step, we identi
54#
發(fā)表于 2025-3-30 20:56:54 | 只看該作者
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發(fā)表于 2025-3-31 03:41:14 | 只看該作者
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發(fā)表于 2025-3-31 06:40:47 | 只看該作者
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發(fā)表于 2025-3-31 12:09:01 | 只看該作者
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發(fā)表于 2025-3-31 15:12:23 | 只看該作者
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發(fā)表于 2025-3-31 20:39:33 | 只看該作者
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發(fā)表于 2025-3-31 22:38:39 | 只看該作者
Julio Borges,Martin A. Neumann,Christian Bauer,Yong Ding,Till Riedel,Michael Beigl
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