Huifeng Guo | DeepAI

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Featured Co-authors

Weinan Zhang
136 publications
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98 publications
Irwin King
95 publications
Zhenguo Li
93 publications
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92 publications
Qing Liu
59 publications
Wei Guo
56 publications
Xue Liu
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Ruiming Tang
53 publications

∙ 02/07/2023

Multi-Task Deep Recommender Systems: A Survey

Multi-task learning (MTL) aims at learning related tasks in a unified mo...

0 Yuhao Wang, et al. ∙

∙ 10/26/2022

Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks

Sequential recommendation (SR) plays an important role in personalized r...

0 Hengyu Zhang, et al. ∙

∙ 10/18/2022

IntTower: the Next Generation of Two-Tower Model for Pre-Ranking System

Scoring a large number of candidates precisely in several milliseconds i...

0 Xiangyang Li, et al. ∙

∙ 08/09/2022

OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction

Learning embedding table plays a fundamental role in Click-through rate(...

0 Fuyuan Lyu, et al. ∙

∙ 06/05/2022

Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation

Learning vectorized embeddings is at the core of various recommender sys...

0 Yankai Chen, et al. ∙

∙ 04/04/2022

Automated Machine Learning for Deep Recommender Systems: A Survey

Deep recommender systems (DRS) are critical for current commercial onlin...

0 Bo Chen, et al. ∙

∙ 12/03/2021

Towards Low-loss 1-bit Quantization of User-item Representations for Top-K Recommendation

Due to the promising advantages in space compression and inference accel...

0 Yankai Chen, et al. ∙

∙ 10/25/2021

Content Filtering Enriched GNN Framework for News Recommendation

Learning accurate users and news representations is critical for news re...

0 Yong Gao, et al. ∙

∙ 06/01/2021

Dual Graph enhanced Embedding Neural Network for CTR Prediction

CTR prediction, which aims to estimate the probability that a user will ...

0 Wei Guo, et al. ∙

∙ 04/17/2021

ScaleFreeCTR: MixCache-based Distributed Training System for CTR Models with Huge Embedding Table

Because of the superior feature representation ability of deep learning,...

0 Huifeng Guo, et al. ∙

∙ 12/16/2020

AutoDis: Automatic Discretization for Embedding Numerical Features in CTR Prediction

Learning sophisticated feature interactions is crucial for Click-Through...

0 Huifeng Guo, et al. ∙

∙ 09/04/2020

A Practical Incremental Method to Train Deep CTR Models

Deep learning models in recommender systems are usually trained in the b...

0 Yichao Wang, et al. ∙

∙ 08/25/2020

GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems

Given the convenience of collecting information through online services,...

39 Yishi Xu, et al. ∙

∙ 04/25/2020

Inter-sequence Enhanced Framework for Personalized Sequential Recommendation

Modeling the sequential correlation of users' historical interactions is...

0 Feng Liu, et al. ∙

∙ 01/01/2020

Multi-Graph Convolution Collaborative Filtering

Personalized recommendation is ubiquitous, playing an important role in ...

0 Jianing Sun, et al. ∙

∙ 04/09/2019

Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction

Click-Through Rate prediction is an important task in recommender system...

0 Bin Liu, et al. ∙

∙ 10/29/2018

Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling

Recommendation is crucial in both academia and industry, and various tec...

0 Feng Liu, et al. ∙

∙ 07/16/2018

An Adjustable Heat Conduction based KNN Approach for Session-based Recommendation

The KNN approach, which is widely used in recommender systems because of...

0 Huifeng Guo, et al. ∙

∙ 07/01/2018

Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data

User response prediction is a crucial component for personalized informa...

0 Yanru Qu, et al. ∙

∙ 04/12/2018

DeepFM: An End-to-End Wide & Deep Learning Framework for CTR Prediction

Learning sophisticated feature interactions behind user behaviors is cri...

0 Huifeng Guo, et al. ∙

∙ 02/23/2018

Novel Approaches to Accelerating the Convergence Rate of Markov Decision Process for Search Result Diversification

Recently, some studies have utilized the Markov Decision Process for div...

0 Feng Liu, et al. ∙

∙ 03/13/2017

DeepFM: A Factorization-Machine based Neural Network for CTR Prediction

Learning sophisticated feature interactions behind user behaviors is cri...

0 Huifeng Guo, et al. ∙