How to Forget Clients in Federated Online Learning to Rank?
Fuente:
arXiv
Saved in:
| Main Authors: | Wang, Shuyi, Liu, Bing, Zuccon, Guido |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Unlearning for Federated Online Learning to Rank: A Reproducibility Study
by: Tao, Yiling, et al.
Published: (2025)
by: Tao, Yiling, et al.
Published: (2025)
Effective and secure federated online learning to rank
by: Wang, Shuyi
Published: (2024)
by: Wang, Shuyi
Published: (2024)
Can It Reach the Generator? Investigating the Survival of Prompt-Injection Attacks in Realistic RAG Settings
by: Yin, Yu, et al.
Published: (2026)
by: Yin, Yu, et al.
Published: (2026)
Poisoning Deep Learning Based Recommender Model in Federated Learning Scenarios
by: Rong, Dazhong, et al.
Published: (2022)
by: Rong, Dazhong, et al.
Published: (2022)
Multi-granular Adversarial Attacks against Black-box Neural Ranking Models
by: Liu, Yu-An, et al.
Published: (2024)
by: Liu, Yu-An, et al.
Published: (2024)
A Privacy Preserving System for Movie Recommendations Using Federated Learning
by: Neumann, David, et al.
Published: (2023)
by: Neumann, David, et al.
Published: (2023)
Differentially Private Graph Diffusion with Applications in Personalized PageRanks
by: Wei, Rongzhe, et al.
Published: (2024)
by: Wei, Rongzhe, et al.
Published: (2024)
Poisoning Federated Recommender Systems with Fake Users
by: Yin, Ming, et al.
Published: (2024)
by: Yin, Ming, et al.
Published: (2024)
Tackling Data Heterogeneity in Federated Time Series Forecasting
by: Yuan, Wei, et al.
Published: (2024)
by: Yuan, Wei, et al.
Published: (2024)
When the Server Steps In: Calibrated Updates for Fair Federated Learning
by: Yu, Tianrun, et al.
Published: (2026)
by: Yu, Tianrun, et al.
Published: (2026)
Few-shot Model Extraction Attacks against Sequential Recommender Systems
by: Zhang, Hui, et al.
Published: (2024)
by: Zhang, Hui, et al.
Published: (2024)
Practical Poisoning Attacks against Retrieval-Augmented Generation
by: Zhang, Baolei, et al.
Published: (2025)
by: Zhang, Baolei, et al.
Published: (2025)
Traceback of Poisoning Attacks to Retrieval-Augmented Generation
by: Zhang, Baolei, et al.
Published: (2025)
by: Zhang, Baolei, et al.
Published: (2025)
Benchmarking Poisoning Attacks against Retrieval-Augmented Generation
by: Zhang, Baolei, et al.
Published: (2025)
by: Zhang, Baolei, et al.
Published: (2025)
Who Taught the Lie? Responsibility Attribution for Poisoned Knowledge in Retrieval-Augmented Generation
by: Zhang, Baolei, et al.
Published: (2025)
by: Zhang, Baolei, et al.
Published: (2025)
Adversarial Attacks to Multi-Modal Models
by: Dou, Zhihao, et al.
Published: (2024)
by: Dou, Zhihao, et al.
Published: (2024)
HGAttack: Transferable Heterogeneous Graph Adversarial Attack
by: Zhao, He, et al.
Published: (2024)
by: Zhao, He, et al.
Published: (2024)
Secure Retrieval-Augmented Generation against Poisoning Attacks
by: Cheng, Zirui, et al.
Published: (2025)
by: Cheng, Zirui, et al.
Published: (2025)
Unveiling Vulnerabilities of Contrastive Recommender Systems to Poisoning Attacks
by: Wang, Zongwei, et al.
Published: (2023)
by: Wang, Zongwei, et al.
Published: (2023)
LazyDP: Co-Designing Algorithm-Software for Scalable Training of Differentially Private Recommendation Models
by: Lim, Juntaek, et al.
Published: (2024)
by: Lim, Juntaek, et al.
Published: (2024)
Manipulating Recommender Systems: A Survey of Poisoning Attacks and Countermeasures
by: Nguyen, Thanh Toan, et al.
Published: (2024)
by: Nguyen, Thanh Toan, et al.
Published: (2024)
Watermarking Recommender Systems
by: Zhang, Sixiao, et al.
Published: (2024)
by: Zhang, Sixiao, et al.
Published: (2024)
AgentPoison: Red-teaming LLM Agents via Poisoning Memory or Knowledge Bases
by: Chen, Zhaorun, et al.
Published: (2024)
by: Chen, Zhaorun, et al.
Published: (2024)
AI-Driven Guided Response for Security Operation Centers with Microsoft Copilot for Security
by: Freitas, Scott, et al.
Published: (2024)
by: Freitas, Scott, et al.
Published: (2024)
POST: Email Archival, Processing and Flagging Stack for Incident Responders
by: Fairbanks, Jeffrey
Published: (2024)
by: Fairbanks, Jeffrey
Published: (2024)
DM4Steal: Diffusion Model For Link Stealing Attack On Graph Neural Networks
by: Chen, Jinyin, et al.
Published: (2024)
by: Chen, Jinyin, et al.
Published: (2024)
Privacy-preserving recommender system using the data collaboration analysis for distributed datasets
by: Yanagi, Tomoya, et al.
Published: (2024)
by: Yanagi, Tomoya, et al.
Published: (2024)
Training Differentially Private Ad Prediction Models with Semi-Sensitive Features
by: Chua, Lynn, et al.
Published: (2024)
by: Chua, Lynn, et al.
Published: (2024)
Towards Differential Privacy in Sequential Recommendation: A Noisy Graph Neural Network Approach
by: Hu, Wentao, et al.
Published: (2023)
by: Hu, Wentao, et al.
Published: (2023)
Randomized algorithms for precise measurement of differentially-private, personalized recommendations
by: Laro, Allegra, et al.
Published: (2023)
by: Laro, Allegra, et al.
Published: (2023)
Auditing Privacy in Multi-Tenant RAG under Account Collusion
by: Burnat, Florian A. D.
Published: (2026)
by: Burnat, Florian A. D.
Published: (2026)
Safe machine learning model release from Trusted Research Environments: The SACRO-ML package
by: Smith, Jim, et al.
Published: (2022)
by: Smith, Jim, et al.
Published: (2022)
Preserving Privacy and Utility in LLM-Based Product Recommendations
by: Khezresmaeilzadeh, Tina, et al.
Published: (2025)
by: Khezresmaeilzadeh, Tina, et al.
Published: (2025)
Retrieval Pivot Attacks in Hybrid RAG: Measuring and Mitigating Amplified Leakage from Vector Seeds to Graph Expansion
by: Thornton, Scott
Published: (2026)
by: Thornton, Scott
Published: (2026)
Differentially Private Datastore Generation for Retrieval-Augmented Inference
by: Abouelenein, Abdelrahman, et al.
Published: (2026)
by: Abouelenein, Abdelrahman, et al.
Published: (2026)
RobustMask: Certified Robustness against Adversarial Neural Ranking Attack via Randomized Masking
by: Liu, Jiawei, et al.
Published: (2025)
by: Liu, Jiawei, et al.
Published: (2025)
BiRD: A Bidirectional Ranking Defense Mechanism for Retrieval Augmented Generation
by: Gao, Chengcai, et al.
Published: (2026)
by: Gao, Chengcai, et al.
Published: (2026)
FedGT: Identification of Malicious Clients in Federated Learning with Secure Aggregation
by: Xhemrishi, Marvin, et al.
Published: (2023)
by: Xhemrishi, Marvin, et al.
Published: (2023)
PhishLang: A Real-Time, Fully Client-Side Phishing Detection Framework Using MobileBERT
by: Roy, Sayak Saha, et al.
Published: (2024)
by: Roy, Sayak Saha, et al.
Published: (2024)
Adversarial Text Rewriting for Text-aware Recommender Systems
by: Oh, Sejoon, et al.
Published: (2024)
by: Oh, Sejoon, et al.
Published: (2024)
Similar Items
-
Unlearning for Federated Online Learning to Rank: A Reproducibility Study
by: Tao, Yiling, et al.
Published: (2025) -
Effective and secure federated online learning to rank
by: Wang, Shuyi
Published: (2024) -
Can It Reach the Generator? Investigating the Survival of Prompt-Injection Attacks in Realistic RAG Settings
by: Yin, Yu, et al.
Published: (2026) -
Poisoning Deep Learning Based Recommender Model in Federated Learning Scenarios
by: Rong, Dazhong, et al.
Published: (2022) -
Multi-granular Adversarial Attacks against Black-box Neural Ranking Models
by: Liu, Yu-An, et al.
Published: (2024)