Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings

25 April 2019

Papers citing "Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings"

20 / 20 papers shown

Title
Exploiting Epistemic Uncertainty in Cold-Start Recommendation Systems Yang Xiang Li Fan Chenke Yin Menglin Kong Chengtao Ji OffRL 42 0 0 22 Feb 2025
AdaF^2M^2: Comprehensive Learning and Responsive Leveraging Features in Recommendation System Yongchun Zhu Jingwu Chen Ling Chen Y. Li Feng Zhang Xiao Yang Zuotao Liu 44 0 0 28 Jan 2025
Prompt Tuning for Item Cold-start Recommendation Yuezihan Jiang Gaode Chen Wenhan Zhang J. Wang Yinjie Jiang Qi Zhang Jingjian Lin Peng Jiang Kaigui Bian VLM 42 0 0 24 Dec 2024
Sequential LLM Framework for Fashion Recommendation Han Liu Xianfeng Tang Tianlang Chen Jiapeng Liu Indu Indu ... Roberto Fernandez Galan Michael D Porter Dongmei Jia Ning Zhang Lian Xiong AI4TS 35 1 0 15 Oct 2024
Enhancing User Interest based on Stream Clustering and Memory Networks in Large-Scale Recommender Systems Peng Liu Nian Wang Cong Xu Min Zhao Bin Wang Yi Ren 123 0 0 21 May 2024
$AntM$^{2}$C: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction$ AntM $^{2}$ C: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction Zhaoxin Huan Ke Ding Ang Li Xiaolu Zhang Xu Min ... Linjian Mo Jinjie Gu Zhongyi Liu Wenliang Zhong Guannan Zhang 21 0 0 31 Aug 2023
BERT4CTR: An Efficient Framework to Combine Pre-trained Language Model with Non-textual Features for CTR Prediction Dong Wang Kave Salamatian Yunqing Xia Weiwei Deng Qi Zhang 21 12 0 17 Aug 2023
Is Meta-Learning the Right Approach for the Cold-Start Problem in Recommender Systems? Davide Buffelli Ashish Gupta Agnieszka Strzalka Vassilis Plachouras OffRL LRM 26 1 0 16 Aug 2023
AutoAssign+: Automatic Shared Embedding Assignment in Streaming Recommendation Ziru Liu Kecheng Chen Fengyi Song Bo Chen Xiangyu Zhao Huifeng Guo Ruiming Tang 18 3 0 14 Aug 2023
ALT: An Automatic System for Long Tail Scenario Modeling Ya-Lin Zhang Jun Zhou Yankun Ren Yue Zhang Xinxing Yang Meng Li Qitao Shi Longfei Li 25 0 0 19 May 2023
Meta-Shop: Improving Item Advertisement For Small Businesses Yang Shi Guannan Liang Young-joo Chung 30 0 0 02 Dec 2022
Personalizing Intervened Network for Long-tailed Sequential User Behavior Modeling Zheqi Lv Feng Wang Shengyu Zhang Kun Kuang Hongxia Yang Fei Wu 29 8 0 19 Aug 2022
Multi-view Multi-behavior Contrastive Learning in Recommendation Yiqing Wu Ruobing Xie Yongchun Zhu Xiang Ao Xin Chen Xu-Yao Zhang Fuzhen Zhuang Leyu Lin Qing He 10 78 0 20 Mar 2022
Alleviating Cold-start Problem in CTR Prediction with A Variational Embedding Learning Framework Xiaoxiao Xu Chen Yang Qian Yu Zhiwei Fang Jiaxing Wang Chaosheng Fan Yang He Changping Peng Zhangang Lin Jingping Shao CML 20 27 0 17 Jan 2022
A Multi-Strategy based Pre-Training Method for Cold-Start Recommendation Bowen Hao Hongzhi Yin Jing Zhang Cuiping Li Hong Chen 27 22 0 04 Dec 2021
Learning to Learn a Cold-start Sequential Recommender Xiaowen Huang Jitao Sang Jian Yu Changsheng Xu DiffM CLL OffRL 19 22 0 18 Oct 2021
Learning with Multiclass AUC: Theory and Algorithms Zhiyong Yang Qianqian Xu Shilong Bao Xiaochun Cao Qingming Huang 36 67 0 28 Jul 2021
Learning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate Prediction W. Ouyang Xiuwu Zhang Shukui Ren Li Li Kun Zhang Jinmei Luo Zhaojie Liu Yanlong Du 25 45 0 19 May 2021
Personalized Adaptive Meta Learning for Cold-start User Preference Prediction Runsheng Yu Yu Gong Xu He Bo An Yu Zhu Qingwen Liu Wenwu Ou 9 57 0 22 Dec 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 329 11,684 0 09 Mar 2017