Leaving No One Behind: A Multi-Scenario Multi-Task Meta Learning Approach for Advertiser Modeling

18 January 2022

Papers citing "Leaving No One Behind: A Multi-Scenario Multi-Task Meta Learning Approach for Advertiser Modeling"

7 / 7 papers shown

Title
Scenario-Wise Rec: A Multi-Scenario Recommendation Benchmark Xiaopeng Li Jingtong Gao Pengyue Jia Xiangyu Zhao Yichao Wang ... Yansen Wang Yuhao Wang Xiangyu Zhao Huifeng Guo Ruiming Tang 65 1 0 17 Jan 2025
Retrievable Domain-Sensitive Feature Memory for Multi-Domain Recommendation Yuang Zhao Zhaocheng Du Qinglin Jia Linxuan Zhang Zhenhua Dong Ruiming Tang 38 2 0 21 May 2024
Deep Task-specific Bottom Representation Network for Multi-Task Recommendation Qi Liu Zhilong Zhou Gangwei Jiang T. Ge Defu Lian 26 12 0 11 Aug 2023
AdaptDHM: Adaptive Distribution Hierarchical Model for Multi-Domain CTR Prediction Jinyun Li Huiwen Zheng Yuan-Cheng Liu Minfang Lu Lixia Wu Haoyuan Hu 47 7 0 22 Nov 2022
BASM: A Bottom-up Adaptive Spatiotemporal Model for Online Food Ordering Service Boya Du Shaochuan Lin Jiong Gao Xiyu Ji Mengya Wang Taotao Zhou Hengxu He Jia Jia Ning Hu 28 6 0 22 Nov 2022
Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks Jindong Han Hao Liu Hengshu Zhu Hui Xiong Dejing Dou 80 75 0 30 Dec 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 419 11,715 0 09 Mar 2017