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Simplify and Robustify Negative Sampling for Implicit Collaborative
  Filtering

Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering

7 September 2020
Jingtao Ding
Yuhan Quan
Quanming Yao
Yong Li
Depeng Jin
ArXivPDFHTML

Papers citing "Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering"

12 / 12 papers shown
Title
MixDec Sampling: A Soft Link-based Sampling Method of Graph Neural Network for Recommendation
MixDec Sampling: A Soft Link-based Sampling Method of Graph Neural Network for Recommendation
Xiangjin Xie
Yiran Chen
Ruipeng Wang
Kai Ouyang
Zihan Zhang
...
Buyue Qian
Hansen Zheng
Bo Hu
Chengxiang Zhuo
Zang Li
74
3
0
12 Feb 2025
AutoSAM: Towards Automatic Sampling of User Behaviors for Sequential Recommender Systems
Hao Zhang
Mingyue Cheng
Qi Liu
Ziqiang Liu
Junzhe Jiang
Enhong Chen
AI4TS
55
3
0
03 Jan 2025
End-to-end Training for Recommendation with Language-based User Profiles
End-to-end Training for Recommendation with Language-based User Profiles
Zhaolin Gao
Joyce Zhou
Yijia Dai
Thorsten Joachims
AI4Ed
59
2
0
24 Oct 2024
Large Language Model Enhanced Hard Sample Identification for Denoising
  Recommendation
Large Language Model Enhanced Hard Sample Identification for Denoising Recommendation
Tianrui Song
Wenshuo Chao
Hao Liu
32
3
0
16 Sep 2024
Exploiting Preferences in Loss Functions for Sequential Recommendation
  via Weak Transitivity
Exploiting Preferences in Loss Functions for Sequential Recommendation via Weak Transitivity
H. Chung
Jungtaek Kim
Hyungeun Jo
Hyungwon Choi
47
0
0
01 Aug 2024
Toward a Better Understanding of Loss Functions for Collaborative
  Filtering
Toward a Better Understanding of Loss Functions for Collaborative Filtering
Seongmin Park
Mincheol Yoon
Jae-woong Lee
Hogun Park
Jongwuk Lee
29
14
0
11 Aug 2023
Distillation from Heterogeneous Models for Top-K Recommendation
Distillation from Heterogeneous Models for Top-K Recommendation
SeongKu Kang
Wonbin Kweon
Dongha Lee
Jianxun Lian
Xing Xie
Hwanjo Yu
VLM
35
21
0
02 Mar 2023
Bayesian Negative Sampling for Recommendation
Bayesian Negative Sampling for Recommendation
B. Liu
Bang-wei Wang
BDL
25
9
0
02 Apr 2022
Consensus Learning from Heterogeneous Objectives for One-Class
  Collaborative Filtering
Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering
SeongKu Kang
Dongha Lee
Wonbin Kweon
Junyoung Hwang
Hwanjo Yu
17
12
0
26 Feb 2022
Learning Explicit User Interest Boundary for Recommendation
Learning Explicit User Interest Boundary for Recommendation
Jianhuan Zhuo
Qiannan Zhu
Yinliang Yue
Yuhong Zhao
11
17
0
22 Nov 2021
Unsupervised Path Representation Learning with Curriculum Negative
  Sampling
Unsupervised Path Representation Learning with Curriculum Negative Sampling
Sean Bin Yang
Chenjuan Guo
Jilin Hu
Jiangtao Tang
Bin Yang
SSL
18
47
0
17 Jun 2021
Scalable Personalised Item Ranking through Parametric Density Estimation
Scalable Personalised Item Ranking through Parametric Density Estimation
Riku Togashi
Masahiro Kato
Mayu Otani
T. Sakai
Shiníchi Satoh
38
0
0
11 May 2021
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