2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
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MLSP-12: Federated Learning 1

Session Type: Poster
Time: Wednesday, 9 June, 13:00 - 13:45
Location: Gather.Town
Session Chair: Tao Zhang, Amazon
 
   MLSP-12.1: FEDERATED LEARNING FROM BIG DATA OVER NETWORKS
         Yasmin SarcheshmehPour; Aalto University
         Miika Leinonen; Aalto University
         Alexander Jung; Aalto University
 
   MLSP-12.2: EFFICIENT CLIENT CONTRIBUTION EVALUATION FOR HORIZONTAL FEDERATED LEARNING
         Jie Zhao; Hainan University
         Xinghua Zhu; Ping An Technology (Shenzhen) Co., Ltd.
         Jianzong Wang; Ping An Technology (Shenzhen) Co., Ltd.
         Jing Xiao; Ping An Technology (Shenzhen) Co., Ltd.
 
   MLSP-12.3: A QUANTITATIVE METRIC FOR PRIVACY LEAKAGE IN FEDERATED LEARNING
         Yong Liu; National University of Singapore
         Xinghua Zhu; Ping An Technology (Shenzhen) Co., Ltd.
         Jianzong Wang; Ping An Technology (Shenzhen) Co., Ltd.
         Jing Xiao; Ping An Technology (Shenzhen) Co., Ltd.
 
   MLSP-12.4: DP-SIGNSGD: WHEN EFFICIENCY MEETS PRIVACY AND ROBUSTNESS
         Lingjuan Lyu; Ant Group
 
   MLSP-12.5: FEDERATED ALGORITHM WITH BAYESIAN APPROACH: OMNI-FEDGE
         Sai Anuroop Kesanapalli; Indian Institute of Technology, Dharwad
         B. N. Bharath; Indian Institute of Technology, Dharwad
 
   MLSP-12.6: TRAINING SPEECH RECOGNITION MODELS WITH FEDERATED LEARNING: A QUALITY/COST FRAMEWORK
         Dhruv Guliani; Google Inc
         Francoise Beaufays; Google Inc
         Giovanni Motta; Google Inc