Abstract: Computer-aided methods for performing computations using adversarially-robust neural networks is disclosed that includes providing a uncoded neural network comprising a plurality of neurons and associated inputs for each of the plurality of neurons, each neuron configured to perform a calculation according to an activation function. The method further includes transforming, using the computing device, at least one uncoded neuron into a coded neuron by adding, using the computing device, an error correcting code as an additional input to the at least one uncoded neuron, the error correcting code comprising a redundant combination of the associated inputs off the uncoded neuron, and revising, using the computing device, the activation function of the at least one uncoded neuron to accommodate the error correcting code as the additional input.

Abstract: A method for calculating a given multivariate polynomial f(Xi) is provided. The multivariate polynomial f(Xi) is to be calculated for every Xi in a large dataset X=(X1, X2, . . . ; XK) in accordance with an S-resilient, A-secure, and T-private scheme where K is an integer enumerating the number of elements in the dataset X, S is the number of stragglers to be tolerated, A is the number of adversaries to be tolerated, and T is the number of colluding workers that to be tolerated. The method is implemented by a computer system that includes a master computing device and a plurality of worker computing devices. The working computing devices can include colluding workers, malicious computing devices, and straggler computing devices.

Abstract: A mutation profile can be determined for an individual's DNA sequence or sequence segment that provides information about the evolutionary history of the DNA. This mutation profile can then be used with a machine learning classifier trained on other people's mutation profiles to determine probabilities that the individual has certain phenotypes. An example is cancer, where the probabilities of different types of cancer can be provided in a disease risk propensity.