System and Method for Ensemble Expert Diversification via Bidding and Control Thereof

Machine readable and non-transitory medium having information recorded thereon for machine learning, wherein the information, once read by the machine, causes the machine to perform:

• receiving, from an expert during training, a bid for a training sample with an amount within a level of available bidding currency associated with the expert, wherein the training sample is used for training a model associated with the expert;
• determining whether the expert is among at least one winner selected based on bids from one or more experts;
• and
• sending the training sample to the expert if the expert is among the at least one winner, wherein the at least one winner is selected based on one or more criteria aiming at expert diversification.

A system for machine learning, comprising:

• a bidding winner selector configured for
• receiving, from an expert during training, a bid for a training sample with an amount within a level of available bidding currency associated with the expert, wherein the training sample is used for training a model associated with the expert, and
• determining whether the expert is among at least one winner selected based on bids from one or more experts;
• and
• a training data distribution unit configured for sending the training sample to the expert if the expert is among the at least one winner, wherein
• the at least one winner is selected based on one or more criteria aiming at expert diversification.