Kan Ren

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Shanghai Jiao Tong University ∙ Microsoft

Infrared target tracking based on proximal robust principal component analysis method

Infrared target tracking plays an important role in both civil and milit...
10/11/2020 ∙ by Chao Ma, et al. ∙ 0 ∙ share

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Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning

Interactive recommender system (IRS) has drawn huge attention because of...
06/18/2020 ∙ by Sijin Zhou, et al. ∙ 0 ∙ share

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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. ∙ 0 ∙ share

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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. ∙ 0 ∙ share

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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. ∙ 0 ∙ share

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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. ∙ 0 ∙ share

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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. ∙ 0 ∙ share

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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. ∙ 0 ∙ share

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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. ∙ 0 ∙ share

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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. ∙ 0 ∙ share

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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. ∙ 0 ∙ share

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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. ∙ 0 ∙ share

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Kan Ren

Featured Co-authors

Jun Wang

Weinan Zhang

Yong Yu

Ya Zhang

Chao Ma

Kun Gai

Jian Xu

Qian Chen

Ruiming Tang

Xiuqiang He

Lei Zheng

Infrared target tracking based on proximal robust principal component analysis method

Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning

Sequential Recommendation with Dual Side Neighbor-based Collaborative Relation Modeling

Deep Landscape Forecasting for Real-time Bidding Advertising

Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction

Guiding the One-to-one Mapping in CycleGAN via Optimal Transport

Deep Recurrent Survival Analysis

Learning Multi-touch Conversion Attribution with Dual-attention Mechanisms for Online Advertising

Bidding Machine: Learning to Bid for Directly Optimizing Profits in Display Advertising

Activation Maximization Generative Adversarial Nets

Real-Time Bidding by Reinforcement Learning in Display Advertising

A Graph Traversal Based Approach to Answer Non-Aggregation Questions Over DBpedia