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公开(公告)号：US10579623B2
公开(公告)日：2020-03-03
申请号：US15143138
申请日：2016-04-29
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Mehran Kafai , Hongwei Shang , Omar Aguilar Macedo
IPC: G06F16/2455 , G06N7/00
Abstract: Dynamically updating a ridge regression data model of a continuous stream of data is disclosed. New data chunks corresponding to a current data accumulation point are received and the data values in the new data chunks are transformed via standardization methods. A ridge estimator for the standardized data that includes data chunks received up to a penultimate data accumulation point to include the new data chunks is dynamically updated. The cumulative observations received up to the current data accumulation point are updated and stored. Predictions for the continuous data stream are generated based on the updated ridge estimator.
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公开(公告)号：US10216899B2
公开(公告)日：2019-02-26
申请号：US15298412
申请日：2016-10-20
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Mehran Kafai , Kari Lam
Abstract: In some examples, a method may include obtaining, from a DNA sequence, a DNA bin that includes a number of consecutive DNA elements equal to a bin length parameter and constructing sentences from the DNA bin to form a constructed sentence set that includes a number of sentences equal to a size parameter. Each sentence of the constructed sentence set may be constructed by partitioning the DNA bin into words, each word comprising a number of DNA elements equal to the size parameter. Each sentence of the constructed sentence set may include overlapping DNA elements with other sentences of the constructed sentence set and may start with a different DNA element of the DNA bin. The method may further include using the constructed sentence set to train a classifier and determining a DNA classification for an unclassified DNA subsequence through the classifier trained using the constructed sentence set.
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公开(公告)号：US20170364517A1
公开(公告)日：2017-12-21
申请号：US15185727
申请日：2016-06-17
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Mehran Kafai , Kave Eshghi
CPC classification number: G06F17/10 , H04L9/0866
Abstract: A system may include an access engine to access an input vector as well as a projection matrix. The projection matrix may include a number of rows equal to a number of hash values to generate from the input vector multiplied by the square root of an inverted sparsity parameter specifying a ratio of the hash universe size from which the hash values are generated to the number of hash values to generate. The projection matrix may include a number of columns equal to the dimensionality of the input vector. The system may also include a hash computation engine to determine a projection vector from the projection matrix and the input vector, split the projection vector into a number of sub-vectors equal to the number of hash values to generate, and generate a hash value from each of the sub-vectors.
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公开(公告)号：US20200167312A1
公开(公告)日：2020-05-28
申请号：US16073961
申请日：2015-12-11
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Mehran Kafai , Kave Eshghi , Omar Aguilar Macedo
IPC: G06F16/13
Abstract: An example method is provided in according with one implementation of the present disclosure. The method comprises generating, via a processor, a set of hashes for each of a plurality of objects. The method also comprises computing, via the processor, a high-dimensional sparse vector for each object, where the vector represents the set of hashes for each object. The method further comprises computing, via the processor, a combined high-dimensional sparse vector from the high-dimensional sparse vectors for all objects and computing a hash suppression threshold. The method also comprises determining, via the processor, a group of hashes to be suppressed by using the hash suppression threshold, and suppressing, via the processor, the group of selected hashes when performing an action.
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公开(公告)号：US20180285693A1
公开(公告)日：2018-10-04
申请号：US15768539
申请日：2015-10-16
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Mehran Kafai , Kyriaki Dimitriadou , April Slayden Mitchell
Abstract: Incremental update of a neighbor graph via an orthogonal transform based indexing is disclosed. One example is a system including a hash transform module to apply an orthogonal transform to a data object in a data stream, and to associate the data object with a collection of ordered hash positions. An indexing module retrieves an index of ordered key positions, where each key position is indicative of data objects in the data stream that have a hash position at the key position. A neighbor determination module determines a ranked collection of neighbors for the data object in a neighbor graph, where the ranking is based on the index. A graph update module incrementally updates the neighbor graph by including the data object as a neighbor for a selected sub-plurality of data objects in the ranked collection.
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Patent Agency Ranking
16.发明申请公开(公告)号：US20170344589A1
公开(公告)日：2017-11-30
申请号：US15166026
申请日：2016-05-26
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Mehran Kafai , Kave Eshghi
IPC: G06F17/30
CPC classification number: G06F16/2237 , G06F16/2264
Abstract: A system may include an access engine and a projection engine. The access engine may access a feature vector with an initial dimensionality that represents a data object of a physical system. The projection engine may generate an extended vector with an extended dimensionality from the feature vector. The projection engine may also apply an orthogonal transformation to the extended vector to obtain an intermediate vector with the extended dimensionality, as well as compute the inner products of the intermediate vector and sparse binary vectors of a sparse binary vector set. In doing so, the projection engine may obtain a randomly projected vector with an output dimensionality that is greater than the extended dimensionality of the intermediate vector. Then, the projection engine may output the randomly projected vector as an output vector that is a random projection of the feature vector with the output dimensionality.
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公开(公告)号：US20170208127A1
公开(公告)日：2017-07-20
申请号：US15324052
申请日：2014-07-25
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Mehran Kafai , Wen Yao , April Slayden Mitchell
IPC: H04L29/08
Abstract: Low-level nodes (LLNs) that are communicatively connected to one another each have sensing capability and processing capability. High-level nodes (HLNs) that are communicatively connected to one another and to the LLNs each have processing capability more powerful than the processing capability of each LLN. The LLNs and the HLNs perform processing based on sensing events captured by the LLNs. The processing is performed by the LLNs and the HLNs to minimize data communication among the LLNs and the HLNs, and to provide for software-defined sensing.
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公开(公告)号：US20170161337A1
公开(公告)日：2017-06-08
申请号：US15325493
申请日：2014-08-18
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor： Wen Yao , Mehran Kafai , April Slayden Mitchell
IPC: G06F17/30
CPC classification number: G06F16/2465 , G06F16/24578 , G06F16/2474 , G06F16/248 , G06F16/26
Abstract: Interactive sequential pattern mining is disclosed. One example is a system including a sequence miner, and an interaction processor. A sequence database is received, the sequence database including a plurality of input sequences, where each sequence of the plurality of input sequences is an ordered list of events, and each event in the list of events includes at least one item. The sequence miner mines the sequence database for a plurality of candidate sequence patterns, the mining based on an interaction with a user. The interaction processor processes the interaction with the user, the interaction based on domain relevance of the plurality of candidate sequence patterns to the user.
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公开(公告)号：US11361195B2
公开(公告)日：2022-06-14
申请号：US15768539
申请日：2015-10-16
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Mehran Kafai , Kyriaki Dimitriadou , April Slayden Mitchell
IPC: G06F16/00 , G06K9/62 , G06F16/901 , G06F16/903 , G06F17/10 , G06F16/28 , G06F17/14
Abstract: Incremental update of a neighbor graph via an orthogonal transform based indexing is disclosed. One example is a system including a hash transform module to apply an orthogonal transform to a data object in a data stream, and to associate the data object with a collection of ordered hash positions. An indexing module retrieves an index of ordered key positions, where each key position is indicative of data objects in the data stream that have a hash position at the key position. A neighbor determination module determines a ranked collection of neighbors for the data object in a neighbor graph, where the ranking is based on the index. A graph update module incrementally updates the neighbor graph by including the data object as a neighbor for a selected sub-plurality of data objects in the ranked collection.
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公开(公告)号：US11169964B2
公开(公告)日：2021-11-09
申请号：US16073961
申请日：2015-12-11
Applicant: Hewlett Packard Enterprise Development LP
Inventor： Mehran Kafai , Kave Eshghi , Omar Aguilar Macedo
Abstract: An example method is provided in according with one implementation of the present disclosure. The method comprises generating, via a processor, a set of hashes for each of a plurality of objects. The method also comprises computing, via the processor, a high-dimensional sparse vector for each object, where the vector represents the set of hashes for each object. The method further comprises computing, via the processor, a combined high-dimensional sparse vector from the high-dimensional sparse vectors for all objects and computing a hash suppression threshold. The method also comprises determining, via the processor, a group of hashes to be suppressed by using the hash suppression threshold, and suppressing, via the processor, the group of selected hashes when performing an action.
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