Abstract: According to one embodiment, a learning apparatus includes processing circuitry. The processing circuitry generates a plurality of pieces of partial data from a mini-batch of learning data used for a plurality of learning processes for learning of a parameter of a neural network using an objective function, calculates a partial gradient that is a gradient related to the parameter of the objective function for each of the pieces of partial data, and updates the parameter based on an average value of the plurality of partial gradients corresponding to the pieces of partial data and a variance for the partial gradients.

Abstract: According to one embodiment, a trait prediction model generation apparatus generates a plurality of first trait prediction models for each of a plurality of populations, based on summary statistics and inter-polymorphism correlated information. The apparatus generates a second trait prediction model for a specific one of the populations based on regularized regression of the first trait prediction models of each of the populations using a plurality of data sets including single-nucleotide polymorphism data and a trait value.