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Workshop: Federated Learning for User Privacy and Data Confidentiality

Lightning Talks Session 1

Zhaohui Yang · Angel Navia-Vázquez · KUN LI · Hajime Ono · Yang Liu · Yuejiao Sun · Shahab Asoodeh · Chihoon Hwang · Romuald Menuet


Abstract:
  1. Zhaohui Yang, Mingzhe Chen, Walid Saad, Choong Seon Hong, Mohammad Shikh-Bahaei, H. Vincent Poor and Shuguang Cui. Delay Minimization for Federated Learning Over Wireless Communication Networks
  2. Angel Navia Vázquez, Manuel-Alberto Vázquez-López and Jesús Cid-Sueiro. Double Confidential Federated Machine Learning Logistic Regression for Industrial Data Platforms
  3. Kun Li, Fanglan Zheng, Jiang Tian and Xiaojia Xiang. A Federated F-score Based Ensemble Model for Automatic Rule Extraction
  4. Hajime Ono and Tsubasa Takahashi. Locally Private Distributed Reinforcement Learning
  5. Yang Liu, Zhihao Yi and Tianjian Chen. Defending backdoor attacks in feature-partitioned collaborative learning
  6. Tianyi Chen, Xiao Jin, Yuejiao Sun and Wotao Yin. VAFL: a Method of Vertical Asynchronous Federated Learning
  7. Shahab Asoodeh and Flavio Calmon. Differentially Private Federated Learning: An Information-Theoretic Perspective
  8. Mathieu Andreux, Andre Manoel, Romuald Menuet, Charlie Saillard and Chloé Simpson. Federated Survival Analysis with Discrete-Time Cox Models
  9. Myungjae Shin, Chihoon Hwang, Joongheon Kim, Jihong Park, Mehdi Bennis and Seong-Lyun Kim. XOR Mixup: Privacy-Preserving Data Augmentation for One-Shot Federated Learning

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