Patent ID: 11935137
Assignee: BEIJING JIAOTONG UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 1:
2. The method according to claim 1, wherein the steps of entering the reward distribution phase when the global model converges, dynamically adjusting the weights of the three factors, by the task publisher, according to the objective function of the equity reward, with the goal that the actual reward of the participant is as close as possible to the expected reward, and obtaining and distributing, by the task publisher, the actual reward of the participant comprises:
aggregating, by the task publisher, the local model of each participant and determining, by the task publisher, whether the global model converges according to set decision conditions, if the global model does not converge, downloading, by each participant, a current global model and continuing the forgoing training process;
if it is determined that the global model converges, the reward distribution phase is entered, if the task publisher calculates a total value u2i=Σri2ir of the model evaluation and a total value u3i=Σru3i of the waiting-time allowance of the participant i, the evaluation results of the three factors of the data contribution, the model evaluation and the waiting-time allowance of the participant i are Ui=[u1i, u2i, u3i]T, let the weights of the three factors of the data contribution, the model evaluation and the waiting-time allowance be Γ=[γ1, γ2, γ3], the weights F are calculated by using a trust domain linear constraint minimized method according to an objective function of an equity reward distribution to obtain actual reward value Ai=Γ·Ui of the participant i, the actual reward value Ai is distributed to the participant i, and the objective function of the equity reward distribution is as follows:, min
     ⁢
     
      
       ∑
       
        i
        =
        1
       
       N
      
      
       
        V
        i
       
       ·
       
        (
        
         
          Γ
          ·
          
           U
           i
          
         
         -
         
          E
          i
         
        
        )
       
      
     
    
   
   
    
     (
     8
     )
    
   
  
 

wherein expectations of all participants are met.