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Telepath: Understanding Users from a Human Vision Perspective in Large-Scale Recommender Systems
This paper proposes Telepath, a vision-based bionic recommender system model, which understands users from such perspective.
LADDER: A Human-Level Bidding Agent for Large-Scale Real-Time Online Auctions
We present LADDER, the first deep reinforcement learning agent that can successfully learn control policies for large-scale real-world problems directly from raw inputs composed of high-level semantic information.
Optimizing Gross Merchandise Volume via DNN-MAB Dynamic Ranking Paradigm
With the transition from people's traditional `brick-and-mortar' shopping to online mobile shopping patterns in web 2. 0 $\mathit{era}$, the recommender system plays a critical role in E-Commerce and E-Retails.
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