Hewlett-packard Development Company, L.p.

Hewlett Packard Enterprise Development LP

Micro Focus Lcc

Krishnamurthy Viswanathan

Chetan Kumar Gupta

Choudur K Lakshminarayan

Erik Ordentlich

Vanish Talwar

Marcelo Weinberger

Jun Li

Mijung Kim

Chengwei Wang

Fei Chen

Umeshwar Dayal

Gadiel Seroussi

Manish Marwah

Tomas Sander

Jichuan Chang

Craig Peter Sayers

William G Horne

Ram Swaminathan

Kimberly Keeton

Anurag Singla

Martin B Scholz

Sergio Verdu

Itschak Weissman

Wade James Satterfield

Indrajit Roy

Haris Volos

Hernan Laffitte

Siva Raj Rajagopalan

Ron Bekkerman

Maria Teresa Gonzalez Diaz

Henggang Cui

Maria Gonzalez

Abdullah Al Mueen

Cheng Chang

Nandish Jayaram

A transformation on raw data is applied to produce transformed data, where the transformation includes at least one selected from among a summary of the raw data or a transform of the raw data between different domains. In response to a query to access data, the query is processed using the transformed data.

Processing a query using transformed raw data

Example implementations relate to updating an inference graph absent node locking. For example, a processor executing a first thread may receive a first task for updating a node of an inference graph stored by a storage device accessible to a second thread, the first task being assigned during a first iteration of a graph update loop. Absent locking the node from access by the second thread, the processor may generate a value for the node and update the node with the value. Based on detecting that each node of the inference graph has been updated, the processor may continue with a second iteration of the graph update loop.

Updating inference graph absent node locking

Providing a targeted security alert can include collecting participant data from a plurality of participants within a threat exchange community, calculating, using a threat exchange server, a threat relevancy score of a participant among the plurality of participants within the threat exchange community using the collected participant data, and providing, from the threat exchange server to the participant, the targeted security alert based on the calculated threat relevancy score via a communication link within the threat exchange community.

Targeted security alerts

Storing time series data for a search query includes identifying a time series whose representation is to be pre-computed based on available memory storage, pre-computing at least one representation of the identified time series, and storing the at least one representation in the memory storage.

Storing time series data for a search query

An example technique includes assigning partitions of a dataset of multidimensional points to a plurality of local memory nodes of a multicore machine and using the local memory nodes for a search query to determine similarity matches in the dataset for a given multidimensional point. The using includes parallel searching with the local memory nodes in the assigned partitions to identify candidate similarity matches to the given multidimensional point using indexes derived from the multidimensional points, the parallel searching for each node progressing through a sequence of search distances and providing an ongoing search result for each search distance from the given multidimensional point and regulating an extent of the parallel searching based on the ongoing search results.

Using local memory nodes of a multicore machine to process a search query

Examples herein involve graph processing using a shared memory. An example method includes distributing vertices of a graph to a plurality of graph partition processors of a system, the graph partition processors to process non-overlapping sets of vertices of the graph; storing a master copy of a vertex state of the graph in a shared memory of the system; instructing the graph partition processors to iteratively process respective vertices of the graph partitions based on local copies of the state of the graph stored in respective local memories of the graph partition processors; and updating the master copy of the state of the graph in the shared memory based on the iterative processing of the partitions of the vertices by the graph partition processors until convergence of the graph.

Graph processing using a shared memory

A method for event correlation includes capturing events and arranging the events sequentially in at least one dimension. An event correlator implemented by a computational device convolves a kernel density function with each of the events to produce a convolved function for each event. Co-occurrences between events are found by calculating overlap between convolved functions.

Event correlation

Probable anomalies associated with at least one data metric may be detected across a series of windows of time series data by comparison of data to a threshold. An estimated probability of anomalies for each of the windows of time series data may be determined based on the detected probable anomalies and the threshold. The windows of time series data may be ranked based on the estimated probabilities. Probable anomalies associated with highest ranked windows of time series data may be output to a user.

System and method for ranking anomalies

Event determination can include selecting a time lag, calculating a dependency value at the time lag between event pairs within a first textual stream and a second textual stream, and ordering the event pairs based on the dependency value.

Event determination

Methods and devices are provided for data compression. Data compression can include receiving a plurality of data chunks, sampling at least some of the plurality of data chunks extracting a common portion from a number of the plurality of data chunks based on the sampling, and storing a remainder of the plurality of data chunks in memory.

Hardware compression using common portions of data

A similarity search initialization system includes a leaf selector to select a leaf of a suffix tree generated from a target string representing a target sequence. The selected leaf is associated with a prefix in the suffix tree having a longest match to a suffix of a query string representing a query. The system further includes a distance module to determine a distance between the query and a subsequence of the target sequence represented by a candidate substring of the target string. The candidate substring includes the prefix associated with the selected leaf. The determined distance is to provide an initial upper bound in a similarity search of the target sequence using the query.

Similarity search initialization

A joint image compression system and method compress a target image and a reference image under a selected transform to produce a compressed difference image. The joint image compression system includes a computer readable media and a computer program stored on the computer readable media. The computer program includes instructions that implement selecting a transform from among a plurality of transforms that includes a subset determined projective (SDP) transform, where the selected transform minimizes a cumulative mapping error (CME) for corresponding feature points in each of a target image and a reference image. The instructions further implement applying the selected transform to one of the target image and the reference image; forming a difference image under the selected transform and compressing the difference image to produce a compressed difference image.

Joint image compression method and apparatus

Systems and methods of anomaly detection in data centers. An example method may include analyzing time series data for the data center by testing statistical hypotheses. The method may also include constructing upper and lower bounds based on the statistical hypotheses. The method may also include flagging anomalies in the time series data falling outside of the upper and lower bounds.

Anomaly detection in data centers

A method and apparatus are disclosed for identifying anomalies of a signal, by analyzing a signal using a frequency-based technique, analyzing results of the frequency-based analysis using a statistical analysis technique, determining one or more limits based on the statistical analysis, and comparing a frequency domain representation of the signal to the limits to identify anomalies of the signal.

Method and apparatus for identifying anomalies of a signal

Improving data clustering stability. A computer accesses a first plurality of cluster groups comprising data. The computer then applies a clustering method to the first plurality of cluster groups while adjusting said first plurality of cluster groups to be in higher agreement between themselves, thereby generating a second plurality of cluster groups that is in higher agreement between themselves than the first plurality of cluster groups. The second plurality of cluster groups corresponds to the first plurality of cluster groups.

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Mountain View, CA, United States of America

Krishnamurthy Viswanathan