Symantec Corporation

Uber Technologies, Inc.

Jeremy Hermann

Eric Bothwell

Alexander Fontana

Michel Zoppas

Conal O'Raghallaigh

Nikunj Aggarwal

Eric Chen

Shahriar Shariat

Pusheng Zhang

Michael Del Balso

Brandon White

Shagandeep Kaur

Marcos M Campos

Machine-learned models are selectively distributed to a plurality of computer servers according to conditions associated with the computer servers. A server receives travel information from a travel coordination system. The travel information describes a plurality of conditions. The server identifies a hierarchy of one or more parent-child relationships based on the plurality of conditions. The server trains machine-learned models using the plurality of conditions described by the travel information. The server selects machine-learned models for the plurality of conditions responsive to the identified hierarchy. The server distributes machine-learned models to the plurality of computer servers responsive to the identified hierarchy.

Selective distribution of machine-learned models

A method and apparatus for scanning structured data from a data repository having an arbitrary data schema and for applying a policy to the data of the data repository are described. In one embodiment, the structured data is converted to unstructured text data to allow a schema-independent policy to be applied to the text data in order to detect a policy violation in the data repository regardless of the data schema used by the data repository.

Method and apparatus for detecting policy violations in a data repository having an arbitrary data schema

Growing community of inventors

San Francisco, CA, United States of America

Jeremy Hermann