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公开(公告)号:US09977805B1
公开(公告)日:2018-05-22
申请号:US15838110
申请日:2017-12-11
Applicant: SAS Institute Inc.
Inventor: Brian Payton Bowman , Gordon Lyle Keener , Steven E. Krueger
CPC classification number: G06F17/30327 , G06F7/02 , G06F7/08 , G06F7/20 , G06F9/5027 , G06F9/5072 , G06F17/30289 , G06F17/30321 , G06F17/3033 , G06F17/30345 , G06F17/30371 , G06F17/30424 , G06F17/30575 , G06F17/30725 , G06F17/30949 , G06F17/30961
Abstract: An apparatus including a processor to index data records within a data cell, wherein for each data record, the processor retrieves data values from first and second data fields; determines whether the first and second data fields store unique data values; in response to the first data field storing a unique data value, adds an identifier of the data record to a first unique values index, in response to the second data field storing a unique data value, adds the identifier to a second unique values index, wherein identifiers of data records within the unique values indexes are ordered based on corresponding unique data values; and generates an indication of ranges of data values of the first and second data fields to enable a determination of whether a data value specified in search criteria is present within at least the data cell.
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公开(公告)号:US20180131516A1
公开(公告)日:2018-05-10
申请号:US15677683
申请日:2017-08-15
Applicant: SAS Institute Inc.
Inventor: GANG MENG
CPC classification number: H04L9/3073 , H04L9/3242 , H04L63/0428
Abstract: A node in a distributed computing environment can generate key-value pairs. The node can categorize the key-value pairs into bins, with each key-value pair being categorized into a bin spanning a range of hashed keys that includes a hashed key of the key-value pair. The node can determine nodes in the distributed computing environment that are mapped to the bins. The node can distribute each key-value pair to a node corresponding to a bin into which the key-value pair was categorized. The node can then sort any of the key-value pairs maintained on the node by hashed key or key to generate sorted key-value pairs. The node can assign index values to the sorted key-value pairs. The indexed key-value pairs may be the same each time the above process is run, regardless of the underlying topology of the distributed computing environment. This can result in stable data-processing.
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公开(公告)号:US20180096078A1
公开(公告)日:2018-04-05
申请号:US15725026
申请日:2017-10-04
Applicant: SAS Institute Inc. , North Carolina State University
Inventor: Samuel Paul Leeman-Munk , Saratendu Sethi , Christopher Graham Healey , Shaoliang Nie , Kalpesh Padia , Ravinder Devarajan , David James Caira , Jordan Riley Benson , James Allen Cox , Lawrence E. Lewis , Mustafa Onur Kabul
CPC classification number: G06F17/30994 , G06F17/30572 , G06F17/30958 , G06N3/04 , G06N3/105
Abstract: Convolutional neural networks can be visualized. For example, a graphical user interface (GUI) can include a matrix of symbols indicating feature-map values that represent a likelihood of a particular feature being present or absent in an input to a convolutional neural network. The GUI can also include a node-link diagram representing a feed forward neural network that forms part of the convolutional neural network. The node-link diagram can include a first row of symbols representing an input layer to the feed forward neural network, a second row of symbols representing a hidden layer of the feed forward neural network, and a third row of symbols representing an output layer of the feed forward neural network. Lines between the rows of symbols can represent connections between nodes in the input layer, the hidden layer, and the output layer of the feed forward neural network.
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公开(公告)号:US20180095632A1
公开(公告)日:2018-04-05
申请号:US15724029
申请日:2017-10-03
Applicant: SAS Institute Inc. , North Carolina State University
Inventor: SAMUEL PAUL LEEMAN-MUNK , SARATENDU SETHI , CHRISTOPHER GRAHAM HEALEY , SHAOLIANG NIE , KALPESH PADIA , RAVINDER DEVARAJAN , DAVID JAMES CAIRA , JORDAN RILEY BENSON , JAMES ALLEN COX , LAWRENCE E. LEWIS , MUSTAFA ONUR KABUL
IPC: G06F3/0481 , G06N3/04 , G06T11/60 , G06F9/44
CPC classification number: G06F3/04812 , G06F8/34 , G06F9/451 , G06F2203/04803 , G06N3/04 , G06N3/105 , G06T11/60
Abstract: Interactive visualizations of a convolutional neural network are provided. For example, a graphical user interface (GUI) can include a matrix having symbols indicating feature-map values that represent likelihoods of particular features being present or absent at various locations in an input to a convolutional neural network. Each column in the matrix can have feature-map values generated by convolving the input to the convolutional neural network with a respective filter for identifying a particular feature in the input. The GUI can detect, via an input device, an interaction indicating that that the columns in the matrix are to be combined into a particular number of groups. Based on the interaction, the columns can be clustered into the particular number of groups using a clustering method. The matrix in the GUI can then be updated to visually represent each respective group of columns as a single column of symbols within the matrix.
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公开(公告)号:US09928320B2
公开(公告)日:2018-03-27
申请号:US15485577
申请日:2017-04-12
Applicant: SAS Institute Inc.
Inventor: Mahesh V. Joshi , Richard Potter , Jan Chvosta , Mark Roland Little
CPC classification number: G06F17/18 , G06F17/5009 , G06F2217/10 , G06Q40/08
Abstract: Techniques for estimated compound probability distribution are described herein. Embodiments may include receiving, at a master node of a distributed system, a compound model specification comprising frequency models, severity models, and one or more adjustment functions, wherein at least one model of the frequency models and the severity models depend on one or more regressor and distributing the compound model specification to worker nodes of the distributed system, each of the worker nodes to at least generate a portion of samples for use in predicting compound distribution model estimates. Embodiments may also include predicting the compound distribution model estimates based on the sample portions of aggregate values and adjusted aggregate values.
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公开(公告)号:US09928052B2
公开(公告)日:2018-03-27
申请号:US15341491
申请日:2016-11-02
Applicant: SAS Institute Inc.
Inventor: Mihai Ibanescu
CPC classification number: G06F8/63 , G06F8/61 , G06F9/4401 , G06F9/451 , G06F11/1446 , H04L67/10 , H04L67/34
Abstract: Various embodiments are generally directed to an apparatus, method and other techniques for receiving a request to generate a bootable image in a cloud-based computing environment, creating a block storage volume in the cloud-based computing environment in response to receiving the request, the block storage volume having one or more partitions. Further, an apparatus, method and so forth may include installing software comprising one or more files in a file system on the block storage volume in the cloud-based computing environment, creating a snapshot of the file system including the software in the cloud-based computing environment, and creating a bootable image from the snapshot of the file system in the cloud-based computing environment.
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公开(公告)号:US20180075051A1
公开(公告)日:2018-03-15
申请号:US15804570
申请日:2017-11-06
Applicant: SAS Institute Inc.
Inventor: BRIAN PAYTON BOWMAN , STEVEN E. KRUEGER , RICHARD TODD KNIGHT , CHIH-WEI HO
CPC classification number: G06F17/30097 , G06F3/0604 , G06F3/061 , G06F3/064 , G06F3/0643 , G06F3/0644 , G06F3/067 , G06F9/5072 , G06F9/5077 , G06F12/0292 , G06F17/302 , G06F17/30312 , G06F17/30584 , G06F2212/1016 , G06F2212/1056 , G06F2212/154 , G06F2212/262 , G06F2212/263
Abstract: An apparatus includes a processor component caused to: retrieve metadata of organization of data within a data set, and map data of organization of data blocks within a data file; receive indications of which node devices are available to perform a processing task with a data set portion; and in response to the data set including partitioned data, compare the quantities of available node devices and of the node devices last involved in storing the data set. In response to a match, for each map data map entry: retrieve a hashed identifier for a data sub-block, and a size for each of the data sub-blocks within the corresponding data block; divide the hashed identifier by the quantity of available node devices; compare the modulo value to a designation assigned to each of the available node devices; and provide a pointer to the available node device assigned the matching designation.
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118.
公开(公告)号:US20180039897A1
公开(公告)日:2018-02-08
申请号:US15788238
申请日:2017-10-19
Applicant: SAS Institute Inc.
Inventor: KALYAN JOSHI , NITZI ROEHL , YUNG-HSIN (ALEX) CHIEN
IPC: G06N5/04
CPC classification number: G06N5/04
Abstract: Data sets for a three-stage predictor can be automatically determined. For example, multiple time series can be filtered to identify a subset of time series that have time durations that exceed a preset time duration. Whether a time series of the subset of time series includes a time period with inactivity can be determined. Whether the time series exhibits a repetitive characteristic can be determined based on whether the time series has a pattern that repeats over a predetermined time period. Whether the time series includes a magnitude spike with a value above a preset magnitude can be determined. If the time series (i) lacks the time period with inactivity, (ii) exhibits the repetitive characteristic, and (iii) has the magnitude spike with the value above the preset magnitude threshold, the time series can be included in a data set for use with the three-stage predictor.
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公开(公告)号:US20180011865A1
公开(公告)日:2018-01-11
申请号:US15694217
申请日:2017-09-01
Applicant: SAS Institute Inc.
Inventor: Brian Payton Bowman , Mark Kuebler Gass, III
CPC classification number: G06F17/30097 , G06F3/0604 , G06F3/061 , G06F3/064 , G06F3/0643 , G06F3/0644 , G06F3/067 , G06F9/5072 , G06F9/5077 , G06F12/0292 , G06F17/302 , G06F17/30312 , G06F17/30584 , G06F21/602 , G06F2212/1016 , G06F2212/1056 , G06F2212/154 , G06F2212/262 , G06F2212/263
Abstract: An apparatus including a processor caused to: receive sizes and data block encryption data for multiple encrypted data blocks from multiple node devices, wherein data block encryption data is separately generated and used by each node device to encrypt a portion of a data set to generate one of the multiple encrypted data blocks; for each encrypted data block, generate a corresponding map entry within map data to include size and data block encryption data; and in response to receiving size and data block encryption data for all encrypted data blocks, encrypt a portion of the map data to generate an encrypted map base, wherein the portion of map data includes at least a subset of the multiple map entries, and transmit the encrypted map base to one or more storage devices to be stored within a data file along with the multiple encrypted data blocks.
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公开(公告)号:US09860229B2
公开(公告)日:2018-01-02
申请号:US15486480
申请日:2017-04-13
Applicant: SAS Institute Inc.
Inventor: Brian Oneal Miles , Keith Adams
CPC classification number: H04L63/08 , G06F17/30076 , G06F21/6209 , G06F21/6254 , H04L63/02
Abstract: A first computing device connected to an internal network de-anonymizes data. A record including a surrogate key is received from a second computing device connected to an external network to the internal network. Each identity data record includes a second surrogate key, an entity identifier field value, a record type field value, and a de-identified field value. The second surrogate key uniquely identifies the respective record. The surrogate key is compared to the second surrogate key to identify a matching record. The matching entity identifier field value is selected and compared to the entity identifier field value of the plurality of records to identify a master record for the surrogate key. The record type field value includes an indicator indicating whether the record is the master record. The de-identified field value included in the identified master record is selected. The received record is supplemented with the selected de-identified field value.
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