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Real-Time Bidding by Reinforcement Learning in Display Advertising
The majority of online display ads are served through real-time bidding ...
01/10/2017 ∙ by Han Cai, et al. ∙
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Activation Maximization Generative Adversarial Nets
Class label information has been empirically proven to be very useful in...
03/06/2017 ∙ by Zhiming Zhou, et al. ∙
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A Graph Traversal Based Approach to Answer Non-Aggregation Questions Over DBpedia
We present a question answering system over DBpedia, filling the gap bet...
10/16/2015 ∙ by Chenhao Zhu, et al. ∙
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Bidding Machine: Learning to Bid for Directly Optimizing Profits in Display Advertising
Real-time bidding (RTB) based display advertising has become one of the ...
03/01/2018 ∙ by Kan Ren, et al. ∙
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Learning Multi-touch Conversion Attribution with Dual-attention Mechanisms for Online Advertising
In online advertising, the Internet users may be exposed to a sequence o...
08/11/2018 ∙ by Kan Ren, et al. ∙
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Deep Recurrent Survival Analysis
Survival analysis is a hotspot in statistical research for modeling time...
09/07/2018 ∙ by Kan Ren, et al. ∙
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Guiding the One-to-one Mapping in CycleGAN via Optimal Transport
CycleGAN is capable of learning a one-to-one mapping between two data di...
11/15/2018 ∙ by Guansong Lu, et al. ∙
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Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction
User response prediction, which models the user preference w.r.t. the pr...
05/02/2019 ∙ by Kan Ren, et al. ∙
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Deep Landscape Forecasting for Real-time Bidding Advertising
The emergence of real-time auction in online advertising has drawn huge ...
05/07/2019 ∙ by Kan Ren, et al. ∙
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Sequential Recommendation with Dual Side Neighbor-based Collaborative Relation Modeling
Sequential recommendation task aims to predict user preference over item...
11/10/2019 ∙ by Jiarui Qin, et al. ∙
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