Microsoft Technology Licensing, LLC

Other

Intuit, Inc.

David Junzi Wu

J Andrew Goossen

John Raymond Justice

Habib Zargarpour

Kristin E Lauter

Michael Naehrig

Tony Feng

Marko Rukonic

Bonnie Berger Leighton

Hyunghoon Cho

Levon Budagyan

Andrew J Goossen

Computationally-efficient techniques facilitate secure crowdsourcing of genomic and phenotypic data, e.g., for large-scale association studies. In one embodiment, a method begins by receiving, via a secret sharing protocol, genomic and phenotypic data of individual study participants. Another data set, comprising results of pre-computation over random number data, e.g., mutually independent and uniformly-distributed random numbers and results of calculations over those random numbers, is also received via secret sharing. A secure computation then is executed against the secretly-shared genomic and phenotypic data, using the secretly-shared results of the pre-computation over random number data, to generate a set of genome-wide association study (GWAS) statistics. For increased computational efficiency, at least a part of the computation is executed over dimensionality-reduced genomic data. The resulting GWAS statistics are then used to identify genetic variants that are statistically-correlated with a phenotype of interest.

Secure secret-sharing-based crowdsourcing for large-scale association studies of genomic and phenotypic data

Embodiments of the present invention split game processing and rendering between a client and a game server. A rendered video game image is received from a game server and combined with a rendered image generated by the game client to form a single video game image that is presented to a user. Control input is received by a client device and then communicated to a game server, potentially with some preprocessing, and is also consumed locally on the client, at least in part. An embodiment of the present invention processes and renders some or all of a character's interactions with game objects on the client device associated with the character. A character is associated with a client device when control input associated with the character is received from a user of the client device.

Client side processing of character interactions in a remote gaming environment

A user device and one or more server computers securely evaluate a k-nearest neighbor model, with reasonable computation speed and bandwidth utilization, using a combination of techniques. The user device encrypts input vectors using a client's public key to keep client information private. The server computer homomorphically computes a distance between the encrypted input vector and vectors stored in the k-nearest neighbor model. The server computer then engages in a minimization process which results in the user device receiving classification vectors corresponding to the k-nearest neighbors.

Secure computer evaluation of k-nearest neighbor models

Decision trees can be securely evaluated with reasonable computation speed and bandwidth utilization. A user device encrypts input vectors using a client's public key in an additively homomorphic encryption system. A server computer effectively randomizes the decision tree for each use, such that a value indicative of a path resulting from applying an input vector to the decision tree is different each time the decision tree is used. The server computer homomorphically computes the evaluations of each decision node. The server computer provides the value indicative of the path through the decision tree as one part accessible by the client, and another part accessible by the server. The server computer uses the parts to look up a corresponding output value from a database of output values for each path. In this operation, only the output value corresponding to the combined parts can be retrieved, and only by the intended recipient.

Secure computer evaluation of decision trees

Embodiments of the present invention provide client-side scene movement using imagery generated by a game server. Embodiments of the present invention predictively render additional imagery surrounding the present field of view. The predictive scene imagery may be on all sides of the current field of view. Embodiments of the present invention determine the amount of predictive scene imagery generated according to a likelihood of use. In addition to client-adjusted rotation, embodiments of the present invention may predictively translate the field of view. Translation is moving the point of view forward, backward or side-to-side. Predictive translation imagery may be communicated to the game server for use in local translation functions.

Client side processing of player movement in a remote gaming environment

A method to optimize recategorization of financial transactions using collaborative filtering involves obtaining a set of financial transactions of a set of users with a merchant. The method also involves determining, using a processor, a first portion of the set of financial transactions assigned to each recategorization value of a set of recategorization values; determining, using the processor, a second portion of the set of financial transactions where the each recategorization value is different from an initial category; generating, using the processor, a recategorization index for each recategorization value using the first portion of each recategorization value and the second portion; and determining, using the processor, an alternative categorization candidate based on the recategorization index of the each recategorization value.

Growing community of inventors

Stanford, CA, United States of America

David Junzi Wu