Vertical Semi-Federated Learning for Efficient Online Advertising
Fuente:
arXiv
Guardado en:
| Autores principales: | Li, Wenjie, Xia, Shu-Tao, Fan, Jiangke, Zhang, Teng, Wang, Xingxing |
|---|---|
| Formato: | Preprint |
| Publicado: |
2022
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
EGA-V1: Unifying Online Advertising with End-to-End Learning
por: Qiu, Junyan, et al.
Publicado: (2025)
por: Qiu, Junyan, et al.
Publicado: (2025)
EGA-V2: An End-to-end Generative Framework for Industrial Advertising
por: Zheng, Zuowu, et al.
Publicado: (2025)
por: Zheng, Zuowu, et al.
Publicado: (2025)
Multi-task Offline Reinforcement Learning for Online Advertising in Recommender Systems
por: Liu, Langming, et al.
Publicado: (2025)
por: Liu, Langming, et al.
Publicado: (2025)
Unlearning for Federated Online Learning to Rank: A Reproducibility Study
por: Tao, Yiling, et al.
Publicado: (2025)
por: Tao, Yiling, et al.
Publicado: (2025)
Scaling Laws for Online Advertisement Retrieval
por: Wang, Yunli, et al.
Publicado: (2024)
por: Wang, Yunli, et al.
Publicado: (2024)
Posterior Probability Matters: Doubly-Adaptive Calibration for Neural Predictions in Online Advertising
por: Wei, Penghui, et al.
Publicado: (2022)
por: Wei, Penghui, et al.
Publicado: (2022)
Bidding-Aware Retrieval for Multi-Stage Consistency in Online Advertising
por: Liu, Bin, et al.
Publicado: (2025)
por: Liu, Bin, et al.
Publicado: (2025)
Generative Recommendation for Large-Scale Advertising
por: Xue, Ben, et al.
Publicado: (2026)
por: Xue, Ben, et al.
Publicado: (2026)
HoMer: Addressing Heterogeneities by Modeling Sequential and Set-wise Contexts for CTR Prediction
por: Chen, Shuwei, et al.
Publicado: (2025)
por: Chen, Shuwei, et al.
Publicado: (2025)
End-to-End Semantic ID Generation for Generative Advertisement Recommendation
por: Jiang, Jie, et al.
Publicado: (2026)
por: Jiang, Jie, et al.
Publicado: (2026)
Efficient and Robust Regularized Federated Recommendation
por: Liu, Langming, et al.
Publicado: (2024)
por: Liu, Langming, et al.
Publicado: (2024)
Predict Click-Through Rates with Deep Interest Network Model in E-commerce Advertising
por: Zhou, Chang, et al.
Publicado: (2024)
por: Zhou, Chang, et al.
Publicado: (2024)
Enhancing Taobao Display Advertising with Multimodal Representations: Challenges, Approaches and Insights
por: Sheng, Xiang-Rong, et al.
Publicado: (2024)
por: Sheng, Xiang-Rong, et al.
Publicado: (2024)
How to Forget Clients in Federated Online Learning to Rank?
por: Wang, Shuyi, et al.
Publicado: (2024)
por: Wang, Shuyi, et al.
Publicado: (2024)
Recommendation System in Advertising and Streaming Media: Unsupervised Data Enhancement Sequence Suggestions
por: Shih, Kowei, et al.
Publicado: (2025)
por: Shih, Kowei, et al.
Publicado: (2025)
Location Aware Embedding for Geotargeting in Sponsored Search Advertising
por: Gligorijevic, Jelena, et al.
Publicado: (2026)
por: Gligorijevic, Jelena, et al.
Publicado: (2026)
Lower-Left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation
por: Shi, Wentao, et al.
Publicado: (2024)
por: Shi, Wentao, et al.
Publicado: (2024)
NGA: Non-autoregressive Generative Auction with Global Externalities for Advertising Systems
por: Zheng, Zuowu, et al.
Publicado: (2025)
por: Zheng, Zuowu, et al.
Publicado: (2025)
A Knowledge Graph and Deep Learning-Based Semantic Recommendation Database System for Advertisement Retrieval and Personalization
por: Wang, Tangtang, et al.
Publicado: (2025)
por: Wang, Tangtang, et al.
Publicado: (2025)
BroadGen: A Framework for Generating Effective and Efficient Advertiser Broad Match Keyphrase Recommendations
por: Mishra, Ashirbad, et al.
Publicado: (2025)
por: Mishra, Ashirbad, et al.
Publicado: (2025)
Online Learning for Recommendations at Grubhub
por: Egg, Alex
Publicado: (2021)
por: Egg, Alex
Publicado: (2021)
A Systematic Survey on Federated Sequential Recommendation
por: Li, Yichen, et al.
Publicado: (2025)
por: Li, Yichen, et al.
Publicado: (2025)
GORAG: Graph-based Online Retrieval Augmented Generation for Dynamic Few-shot Social Media Text Classification
por: Wang, Yubo, et al.
Publicado: (2025)
por: Wang, Yubo, et al.
Publicado: (2025)
Towards Scalable Semantic Representation for Recommendation
por: Zhang, Taolin, et al.
Publicado: (2024)
por: Zhang, Taolin, et al.
Publicado: (2024)
P4GCN: Vertical Federated Social Recommendation with Privacy-Preserving Two-Party Graph Convolution Network
por: Wang, Zheng, et al.
Publicado: (2024)
por: Wang, Zheng, et al.
Publicado: (2024)
A Survey of Controllable Learning: Methods and Applications in Information Retrieval
por: Shen, Chenglei, et al.
Publicado: (2024)
por: Shen, Chenglei, et al.
Publicado: (2024)
AD-Bench: A Real-World, Trajectory-Aware Advertising Analytics Benchmark for LLM Agents
por: Hu, Lingxiang, et al.
Publicado: (2026)
por: Hu, Lingxiang, et al.
Publicado: (2026)
Learning to Collaborate via Structures: Cluster-Guided Item Alignment for Federated Recommendation
por: Tu, Yuchun, et al.
Publicado: (2026)
por: Tu, Yuchun, et al.
Publicado: (2026)
Modeling the Heterogeneous Duration of User Interest in Time-Dependent Recommendation: A Hidden Semi-Markov Approach
por: Zhang, Haidong, et al.
Publicado: (2024)
por: Zhang, Haidong, et al.
Publicado: (2024)
Stalactite: Toolbox for Fast Prototyping of Vertical Federated Learning Systems
por: Zakharova, Anastasiia, et al.
Publicado: (2024)
por: Zakharova, Anastasiia, et al.
Publicado: (2024)
FedDCSR: Federated Cross-domain Sequential Recommendation via Disentangled Representation Learning
por: Zhang, Hongyu, et al.
Publicado: (2023)
por: Zhang, Hongyu, et al.
Publicado: (2023)
DisenSemi: Semi-supervised Graph Classification via Disentangled Representation Learning
por: Wang, Yifan, et al.
Publicado: (2024)
por: Wang, Yifan, et al.
Publicado: (2024)
RAT: Retrieval-Augmented Transformer for Click-Through Rate Prediction
por: Li, Yushen, et al.
Publicado: (2024)
por: Li, Yushen, et al.
Publicado: (2024)
FedUD: Exploiting Unaligned Data for Cross-Platform Federated Click-Through Rate Prediction
por: Ouyang, Wentao, et al.
Publicado: (2024)
por: Ouyang, Wentao, et al.
Publicado: (2024)
To Judge or not to Judge: Using LLM Judgements for Advertiser Keyphrase Relevance at eBay
por: Dey, Soumik, et al.
Publicado: (2025)
por: Dey, Soumik, et al.
Publicado: (2025)
LLM-PQA: LLM-enhanced Prediction Query Answering
por: Li, Ziyu, et al.
Publicado: (2024)
por: Li, Ziyu, et al.
Publicado: (2024)
Debiased Recommendation with Noisy Feedback
por: Li, Haoxuan, et al.
Publicado: (2024)
por: Li, Haoxuan, et al.
Publicado: (2024)
Variance Reduction in Ratio Metrics for Efficient Online Experiments
por: Baweja, Shubham, et al.
Publicado: (2024)
por: Baweja, Shubham, et al.
Publicado: (2024)
ADSNet: Cross-Domain LTV Prediction with an Adaptive Siamese Network in Advertising
por: Wang, Ruize, et al.
Publicado: (2024)
por: Wang, Ruize, et al.
Publicado: (2024)
Analyzing and Mitigating Repetitions in Trip Recommendation
por: Shu, Wenzheng, et al.
Publicado: (2025)
por: Shu, Wenzheng, et al.
Publicado: (2025)
Ejemplares similares
-
EGA-V1: Unifying Online Advertising with End-to-End Learning
por: Qiu, Junyan, et al.
Publicado: (2025) -
EGA-V2: An End-to-end Generative Framework for Industrial Advertising
por: Zheng, Zuowu, et al.
Publicado: (2025) -
Multi-task Offline Reinforcement Learning for Online Advertising in Recommender Systems
por: Liu, Langming, et al.
Publicado: (2025) -
Unlearning for Federated Online Learning to Rank: A Reproducibility Study
por: Tao, Yiling, et al.
Publicado: (2025) -
Scaling Laws for Online Advertisement Retrieval
por: Wang, Yunli, et al.
Publicado: (2024)