SYSTEMS AND METHODS FOR OPTIMAL BIDDING IN A BUSINESS TO BUSINESS ENVIRONMENT
The present invention relates to systems and methods for optimizing bidding in a business-to-business environment. Initially the observed outcomes for n deals are received, and the belief parameters for these n deals are calculated. The Bayes-greedy price is then calculated and presented to a buyer. The buyer's response is collected and an optimal variance parameter based on the buyer's response is generated. The belief parameters for these n+1 deals are also updated. This process may be repeated for additional deals.
1 . A method for reducing computations of non-normal data with a processor, comprising:
receiving, at a processor, features of n events;
receiving, at the processor, observed outcomes of the n events;
calculating, via the processor, a normal distribution of the observed outcomes based on the features; and
when a new event occurs:
calculating a posterior distribution representing regression coefficients of the observed outcomes with the new event, the posterior distribution being a non-normal distribution;
replacing, within memory associated with the processor, the posterior distribution with a normal approximated distribution of the posterior distribution;
calculating a projected outcome of the new event using the normal approximated distribution with the formula: p k−1 =p k −a k ∇ p k R(p k :x, β); and
outputting the projected outcome to a display.