Cisco Technology, Inc.

Amobee, Inc.

Microsoft Technology Licensing, LLC

Sumit Rangwala

Debojyoti Dutta

Subrata Banerjee

Ali Dasdan

Raja Rao Tadimeti

Yuanbo Zhu

Jean-Philippe Vasseur

Eric Huang

Joel Daniel Young

Santanu Kolay

Gilman Tolle

Xu Miao

David J Stein

Philip Buonadonna

Da Teng

Songxiang Gu

Chang-Ming Tsai

Shahriar Shariat

Lance M Wall

The disclosed embodiments provide a system for processing data. During operation, the system obtains a hierarchical representation containing a set of namespaces of a set of features shared by a set of statistical models. Next, the system uses the hierarchical representation to obtain, from one or more execution environments, a subset of the features for use in calculating the derived feature. The system then applies a formula from the hierarchical representation to the subset of the features to produce the derived feature. Finally, the system provides the derived feature for use by one or more of the statistical models.

Common feature protocol for collaborative machine learning

Methods and apparatus for identifying on-line users for advertisement or content targeting are disclosed. Historical user data is obtained in association with user identifiers, which have been unambiguously determined. The historical user data includes event data for one or more on-line user events that have occurred for each user identifier. The historical user data also specify fingerprint vectors of characteristic values that are each associated with specific ones of the user identifiers. A current one of the fingerprint vectors that is ambiguously associated with two or more user identifiers is received. A first user identifier is selected from the associated two or more user identifiers of the current fingerprint vector based on the event data of the historical user data. The selected first user identifier is provided to a server configured to provide advertisement or content based on user profile data that is obtainable for such selected first user identifier.

Methods and apparatus for identifying a cookie-less user

Methods and apparatus for finding detecting unique on-line users for advertisement or content targeting are disclosed. A bid request with initial fingerprint context data for a user and for content that is requested by such user is received at a bid management system, and the bid request is received with or without a user identifier. At the bid management system, an optimum bid for the bid request is determined based on the initial fingerprint context data for the user and the content. The optimum bid with a reference to an advertisement and a script for obtaining additional fingerprint context data from a device of the user is sent from the bid management system. The additional fingerprint context data is received and a unique user identifier is assigned in association with a combination of the initial and additional fingerprint context data.

Methods and apparatus for identifying unique users for on-line advertising

A method for summarizing capabilities in a hierarchically arranged data center includes receiving capabilities information, wherein the capabilities information is representative of capabilities of respective nodes at a first hierarchical level in the hierarchically arranged data center, clustering nodes based on groups of capabilities information, generating a histogram that represents individual node clusters, and sending the histogram to a next higher level in the hierarchically arranged data center. Relative rankings of capabilities may be used to order a sequence of clustering operations.

Data center capability summarization

In one embodiment, an aggregation device within a computer network domain receives one or more capability messages from one or more devices in the computer network domain. The aggregation device may then aggregate device capabilities from the capability messages, and provides the aggregated device capabilities to a management device located outside of the computer network domain.

Hierarchical schema to provide an aggregated view of device capabilities in a network

Growing community of inventors

Fremont, CA, United States of America

Sumit Rangwala