Search Results for author: Guorui Zhou

Found 15 papers, 8 papers with code

Real Negatives Matter: Continuous Training with Real Negatives for Delayed Feedback Modeling

1 code implementation29 Apr 2021 Siyu Gu, Xiang-Rong Sheng, Ying Fan, Guorui Zhou, Xiaoqiang Zhu

If conversion happens outside the waiting window, this sample will be duplicated and ingested into the training pipeline with a positive label.

CAN: Feature Co-Action for Click-Through Rate Prediction

no code implementations11 Nov 2020 Weijie Bian, Kailun Wu, Lejian Ren, Qi Pi, Yujing Zhang, Can Xiao, Xiang-Rong Sheng, Yong-Nan Zhu, Zhangming Chan, Na Mou, Xinchen Luo, Shiming Xiang, Guorui Zhou, Xiaoqiang Zhu, Hongbo Deng

For example, a simple attempt to learn the combination of feature A and feature B <A, B> as the explicit cartesian product representation of new features can outperform previous implicit feature interaction models including factorization machine (FM)-based models and their variations.

Click-Through Rate Prediction

DCAF: A Dynamic Computation Allocation Framework for Online Serving System

no code implementations17 Jun 2020 Biye Jiang, Pengye Zhang, Rihan Chen, Binding Dai, Xinchen Luo, Yin Yang, Guan Wang, Guorui Zhou, Xiaoqiang Zhu, Kun Gai

These stages usually allocate resource manually with specific computing power budgets, which requires the serving configuration to adapt accordingly.

Recommendation Systems

A Deep Recurrent Survival Model for Unbiased Ranking

1 code implementation30 Apr 2020 Jiarui Jin, Yuchen Fang, Wei-Nan Zhang, Kan Ren, Guorui Zhou, Jian Xu, Yong Yu, Jun Wang, Xiaoqiang Zhu, Kun Gai

Position bias is a critical problem in information retrieval when dealing with implicit yet biased user feedback data.

Information Retrieval Survival Analysis

Res-embedding for Deep Learning Based Click-Through Rate Prediction Modeling

no code implementations25 Jun 2019 Guorui Zhou, Kailun Wu, Weijie Bian, Zhao Yang, Xiaoqiang Zhu, Kun Gai

In this paper, we model user behavior using an interest delay model, study carefully the embedding mechanism, and obtain two important results: (i) We theoretically prove that small aggregation radius of embedding vectors of items which belongs to a same user interest domain will result in good generalization performance of deep CTR model.

Click-Through Rate Prediction

Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction

2 code implementations22 May 2019 Qi Pi, Weijie Bian, Guorui Zhou, Xiaoqiang Zhu, Kun Gai

To our knowledge, this is one of the first industrial solutions that are capable of handling long sequential user behavior data with length scaling up to thousands.

Click-Through Rate Prediction Recommendation Systems

Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction

1 code implementation2 May 2019 Kan Ren, Jiarui Qin, Yuchen Fang, Wei-Nan Zhang, Lei Zheng, Weijie Bian, Guorui Zhou, Jian Xu, Yong Yu, Xiaoqiang Zhu, Kun Gai

In order to tackle these challenges, in this paper, we propose a Hierarchical Periodic Memory Network for lifelong sequential modeling with personalized memorization of sequential patterns for each user.

Deep Interest Evolution Network for Click-Through Rate Prediction

13 code implementations11 Sep 2018 Guorui Zhou, Na Mou, Ying Fan, Qi Pi, Weijie Bian, Chang Zhou, Xiaoqiang Zhu, Kun Gai

Easy-to-use, Modular and Extendible package of deep-learning based CTR models. DeepFM, DeepInterestNetwork(DIN), DeepInterestEvolutionNetwork(DIEN), DeepCrossNetwork(DCN), AttentionalFactorizationMachine(AFM), Neural Factorization Machine(NFM), AutoInt

Click-Through Rate Prediction

Rocket Launching: A Universal and Efficient Framework for Training Well-performing Light Net

2 code implementations14 Aug 2017 Guorui Zhou, Ying Fan, Runpeng Cui, Weijie Bian, Xiaoqiang Zhu, Kun Gai

Models applied on real time response task, like click-through rate (CTR) prediction model, require high accuracy and rigorous response time.

Click-Through Rate Prediction

Deep Interest Network for Click-Through Rate Prediction

16 code implementations21 Jun 2017 Guorui Zhou, Chengru Song, Xiaoqiang Zhu, Ying Fan, Han Zhu, Xiao Ma, Yanghui Yan, Junqi Jin, Han Li, Kun Gai

In this way, user features are compressed into a fixed-length representation vector, in regardless of what candidate ads are.

Click-Through Rate Prediction

Hierarchical Latent Semantic Mapping for Automated Topic Generation

no code implementations11 Nov 2015 Guorui Zhou, Guang Chen

Inspired by these algorithms, in this paper, we propose a novel method named Hierarchical Latent Semantic Mapping (HLSM), which automatically generates topics from corpus.

Community Detection

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