公开(公告)号：US20180089301A1

公开(公告)日：2018-03-29

申请号：US15278253

申请日：2016-09-28

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Mehran Kafai ,  Manav Das

IPC: G06F17/30 ,  G06F11/14

CPC classification number: G06F16/285 ,  G06F21/602 ,  G06F21/78

Abstract: Storage allocation based on secure data comparisons is disclosed. One example is a system including a plurality of intermediaries, a data allocator and a plurality of storage containers. Each intermediary receives a request from the data allocator to identify a target storage container of the plurality of storage containers, for secure allocation of a data term. Each intermediary compares, for each storage container, the truncated data term with a collection of truncated candidate terms to select a representative term of the candidate terms, identifies the selected representative term to the storage container, receives a similarity profile from each storage container, where the similarity profile is representative of similarities between the truncated data term and terms in the storage container, and selects a candidate target storage container based on similarity profiles received from each storage container.

公开(公告)号：US20170316338A1

公开(公告)日：2017-11-02

申请号：US15142357

申请日：2016-04-29

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Kave Eshghi ,  Mehran Kafai ,  Omar Aguilar Macedo

IPC: G06N99/00 ,  G06F17/30

CPC classification number: G06N20/00 ,  G06F16/285

Abstract: In some examples, a method includes accessing input vectors in an input space, wherein the input vectors characterize elements of a physical system. The method may also include generating feature vectors from the input vectors, and the feature vectors are generated without any vector product operations between performed between any of the input vectors. An inner product of a pair of the feature vectors may correlate to an implicit kernel for the pair of feature vectors, and the implicit kernel may approximate a Gaussian kernel within a difference threshold. The method may further include providing the feature vectors to an application engine for use in analyzing the elements of the physical system, other elements in the physical system, or a combination of both.

公开(公告)号：US20170228810A1

公开(公告)日：2017-08-10

申请号：US15502523

申请日：2014-09-26

Applicant: Hewlett-Packard Enterprise Development LP

Inventor： Hongwei Shang ,  Yong Liu ,  Mehran Kafai ,  April Slayden Mitchell

IPC: G06Q30/06 ,  G06F7/02 ,  G06Q10/06

CPC classification number: G06Q30/0631 ,  G06F7/026 ,  G06F16/90 ,  G06Q10/067

Abstract: An example method is provided in according with one implementation of the present disclosure. The method includes extracting features related to a plurality of users and a plurality of items and computing a correction parameter score for each of a plurality of user-item pair combinations. The method further includes computing a user response value for a user-item pair combination by applying a generalized linear model to the features of the user-item pair combination and using the correction parameter score for the user-item pair combination in the generalized linear model.

公开(公告)号：US20170163424A1

公开(公告)日：2017-06-08

申请号：US15327015

申请日：2014-08-29

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Mehran Kafai ,  Hongwei Shang ,  Apri Slayden Mitchell

IPC: H04L9/32 ,  G06F17/30 ,  G06F21/62

CPC classification number: H04L9/3242 ,  G06F16/334 ,  G06F21/6245 ,  H04L9/3236 ,  H04L2209/42

Abstract: Secure information retrieval is disclosed. One example is a system including an information retriever comprising a collection of nodes that receive a hash count from a first dataset, the first dataset including a first data term, and provide the hash count to a second dataset, the second dataset including a plurality of second data terms. A hash transformer transforms the data terms based on the hash count. A modifier modifies, for a given node, the transformed data terms. An evaluator evaluates, for each node, a similarity value between the first data term and each given second data term based on shared data elements between the modified first data term and a given modified second data term associated with the given second data term. The information retriever provides to the first dataset, at least one term identifier associated with a second data term.