Abstract: This document relates to training of machine learning models. One example method involves providing a machine learning model having a first classification layer, a second classification layer, and an encoder that feeds into the first classification layer and the second classification layer. The example method also involves obtaining first training examples having explicit labels and second training examples having inferred labels. The inferred labels are based at least on actions associated with the second training examples. The example method also involves training the machine learning model using the first training examples and the second training examples using a training objective that considers first training loss of the first classification layer for the explicit labels and second training loss of the second classification layer for the inferred labels. The method also involves outputting a trained machine learning model having the encoder and the first classification layer.

Abstract: A method for identifying from among network-connected devices a particular device likely associated with a theft of distributed content includes obtaining content, the content having been distributed from a particular one of the network-connected devices, identifying in the obtained content anti-collusion codes, and determining the particular one of the network-connected devices is likely associated with the theft of distributed content when an aggregated probability calculated using the identified anti-collusion codes is equal to or exceeds a predetermined threshold.

Abstract: A customized highlight sequence depicting multiple events, and based on a user's personal characteristics, interests, and/or preferences, is generated and presented. The events can be sporting events, entertainment events, and/or the like. For example, in the context of sporting events, a determination is made as to what types of sports, teams, leagues, players, plays, and/or the like are of interest to the user. In at least one embodiment, the amount of time available to the user can be obtained, so that the length of the highlight sequence can be tailored to the available time. A customized highlight sequence is then generated and presented, containing those specific portions of the sporting events that are likely to be of interest, arranged in a manner that is likely to be entertaining to the user and comports with the time restrictions.

Abstract: Systems and methods are provided for implementing a tool for evaluating an effect on an event, such as a medication or treatment, on a subject's condition, using a propensity model that identifies matched treatment and control cohorts within a base population of subjects. A propensity value threshold, which can be obtained based on user input, can be used to adjust the selection of subjects for treatment and control cohorts. The tool allows analyzing features of the subjects in the treatment and control groups, and further allows for evaluation and comparison of survival objectives of subjects in the treatment and control groups.

Abstract: A machine learning system builds and uses control policies for controlling robotic performance of a task. Such control policies may be trained using targeted updates. For example, two trials identified as similar may be compared and evaluated to determine which trial achieved a greater degree of task success; a control policy update may then be generated based on identified differences between the two trials.

Abstract: Systems and methods for discovering and annotating geo-fences from geo-referenced data are disclosed. The systems and methods input an area of interest containing a plurality of geo-referenced points having associated labels, and divides the area interest into cells. Each cell is assigned an initial label from among the plurality of labels and hierarchical clustering is used to find clusters of cells having a common label based on a maximization of an objective function for each cell with the objective function being dependent upon favoring spatially adjacent cells having a common label and limiting overgeneralization of the common label.

Abstract: A method of explaining a machine learning model, including: receiving a plurality of disease states for a patient over time from a database, wherein the disease states have a plurality of features; generating a plurality of locally faithful explanation models for the patient for each disease state based upon the machine learning model; calculating an explanation with respect to one feature of the plurality of features over time using the locally faithful explanation models; and calculating the importance of the one feature of the plurality of features over time based upon the plurality of locally faithful explanation models.

Abstract: Provided herein are biomarkers and methods for generating scores useful for assessing psoriatic arthritis (PsA) disease activity in subjects previously diagnosed with PsA. The invention also provides predictive model methods based on the biomarkers, as well as computer systems, software embodiments of the models for scoring and optionally classifying samples, and methods of recommending optimal therapeutic regimens.

Abstract: A method for identifying and ranking potentially privileged documents using a machine learning topic model may include receiving a set of documents. The method may also include, for each of two or more documents in the set of documents, extracting a set of spans from the document, generating, using a machine learning topic model, a set of topics and a subset of legal topics for the set of spans, generating a vector of probabilities for each span with a probability being assigned to each topic in the set of topics for the span, assigning a score to one or more spans in the set of spans by summing the probabilities in the vector that are assigned to a topic in the subset of legal topics, and assigning a score to the document. The method may further include ranking the two or more documents by their assigned scores.

Abstract: Computer-implemented systems and methods are provided for constructing a numerical model to generate a probability that a patient diagnosed with multiple myeloma will die within a predetermined period of time. Reference data for a plurality of patients diagnosed with multiple myeloma is received. First variables selected from the reference data are deemed predictive of mortality for a first predetermined period of time, and second variables selected from the reference data are deemed predictive of mortality for a second predetermined period of time. A first computer model comprising a combination of variables of the first selected variables and first weighting factors is generated. A second computer model comprising a combination of variables of the second selected variables and second weighting factors is generated. The first computer model and the second computer model are trained using the reference data to determine numerical values for the respective first and second weighting factors.

Abstract: Systems and methods disclosed herein provide for a case-based reasoning using universal ontologies. Embodiments of the systems and methods provide for comparing current and past cases based on the universal ontologies and sorting the past cases based on the comparison, wherein the universal ontology integrates authority information associated with the current and past cases.

Abstract: A method for displaying points of interest on a digital map on a display, each point of interest being assigned at least one category and the space in front of the display being segmented into spatial regions where each spatial region is assigned a category. The method includes detecting the position of a hand of a user or part of the hand of the user by sensors, more particularly by cameras, identifying the spatial region in which the position of the hand or the part of the hand lies, identifying the category assigned to the identified spatial region, and displaying or highlighting the points of interest that have been assigned to the identified category.

Abstract: Methods, devices and system for determining fasting glucose level information and post-prandial glucose level information for diagnosing pre-diabetic and diabetic conditions based on monitored glucose measurements are provided.

Abstract: A medical system comprises processing circuitry configured to: receive a first trained model, wherein the trained model has been trained using a first data set acquired in a first cohort; receive a second data set acquired in a second cohort; input data included in the second data set and data representative of the first trained model into a second trained model; and receive from the second trained model an affinity-relating value which represents an affinity between the data included in the second data set and the first trained model.

Abstract: Aspects of the present disclosure enable humanly-specified relationships to contribute to a mapping that enables compression of the output structure of a machine-learned model. An exponential model such as a maximum entropy model can leverage a machine-learned embedding and the mapping to produce a classification output. In such fashion, the feature discovery capabilities of machine-learned models (e.g., deep networks) can be synergistically combined with relationships developed based on human understanding of the structural nature of the problem to be solved, thereby enabling compression of model output structures without significant loss of accuracy. These compressed models provide improved applicability to “on device” or other resource-constrained scenarios.

Abstract: In some embodiments, a method receives a connection to a data source. The method analyzes metadata of the data source to determine a first type of metadata for a first type of database access and a second type of metadata for a second type of database access. The first type of metadata and the second type of metadata are combined into a data structure. Then, the method stores the data structure where the data structure is used to analyze a query to determine which of the first type of database access and the second type of database access to use for the query.

Abstract: A physical environment is equipped with a plurality of sensors (e.g., motion sensors). As individuals perform various activities within the physical environment, sensor readings are received from one or more of the sensors. Based on the sensor readings, activities being performed by the individuals are recognized and the sensor data is labeled based on the recognized activities. Future activity occurrences are predicted based on the labeled sensor data. Activity prompts may be generated and/or facility automation may be performed for one or more future activity occurrences.

Abstract: A fault finding support system is a fault finding support system for instructing a maintenance worker of an appropriate examination location and examination contents using fault knowledge data in which a causal relationship of fault of a target machine is described, the system including: an examination procedure creation unit that creates an examination procedure with respect to the examination location and the examination contents of the target machine using the fault knowledge data, an examination result storage unit that stores an examination history of performing examination using the examination procedure created by the examination procedure creation unit, an update target extraction unit that recommends an update location of the fault knowledge data using the examination history stored in the examination result storage unit, and a user interface that provides a function of displaying a location extracted by the update target extraction unit and updating the fault knowledge data.

Abstract: Methods, systems, apparatus, and computer programs are disclosed for software-accelerated genomic data read mapping. In one aspect, the methods can include actions of obtaining a k-mer seed from a genomic data read, generating a genomic signature based on the obtained k-mer seed, determining a reference sequence location that match at least a portion of the k-mer seed using a hash data structure, wherein the hash data structure comprises N data cells comprising a first portion storing a predetermined genomic signature and a second portion storing a value that corresponds to a first occurrence of a reference sequence location that match at least a portion of the k-mer seed from which the predetermined genomic signature was derived, and selecting the determined reference sequence location as an actual alignment for the obtained k-mer seed based on one or more alignment scores.

Abstract: A method for communicating information relating to test results of a user includes obtaining test results of a user. An assertion is derived from the test results of the user. The test results are input to a pre-provisioned first algorithm. The assertion is encapsulated in a first data object by a PGE that controls an environment in which the first algorithm is executed. A first proof is generated which is configured to be usable to verify that the first algorithm used the test results to produce the assertion when provided to a PVE along with the first data object. The test results itself are excluded from the first proof and the first data object such that privacy of the test results is maintained. The first proof and the first data object are communicated to a receiving communication device from an enterprise communication device associated with the user and an enterprise.

Abstract: A method for determining a state of mind of a user may include receiving one or more strings of characters composed by the user, and determining, by a processing device, the state of mind of the user by processing the one or more strings of characters. The processing of the one or more strings of characters may include identifying similarities of the one or more strings of characters with other strings of characters indicative of the state of mind. The method may also include determining, based on the one or more strings of characters, a severity of the state of mind of the user.

Abstract: A method and system is provided for assisting a user to assign a label to words or spans of text in a transcript of a conversation between a patient and a medical professional and form groupings of such labelled words or spans of text in the transcript. The transcript is displayed on an interface of a workstation. A tool is provided for highlighting spans of text in the transcript consisting of one or more words. Another tool is provided for assigning a label to the highlighted spans of text. This tool includes a feature enabling searching through a set of predefined labels available for assignment to the highlighted span of text. The predefined labels encode medical entities and attributes of the medical entities. The interface further includes a tool for creating groupings of related highlighted spans of texts. The tools can consist of mouse action or key strokes or a combination thereof.

Abstract: A method, system and computer-usable medium for detecting headers in various documents, such as PDF and HTML files. The files are converted to a two dimensional array or table, having orthogonal rows and columns. Either rows or columns are determined to include headers. For determining if rows include headers. For each row in the array or table, pair wise comparison is performed for each cell of each column that is orthogonal to that row. The pair wise comparison scores or values are summed up for each orthogonal column to that row and the sum across for all the orthogonal columns to row provide a score or value for that row. Row scores are evaluated relative to one another to determine likelihood of headers in the row. For determining if columns have headers, similar calculation is performed between columns and their orthogonal rows.

Abstract: A computer-implemented method includes receiving genomic data associated with a plurality of genomes and identifying k-mer sets within the genomic data. The method includes constructing a k-mer subset tree according to the following process: performing iterative pairwise comparisons on the k-mer sets, wherein the iterative pairwise comparisons identify fragments with the most shared k-mers, merging the identified fragments into non-leaf nodes of the k-mer subset tree, and placing each remaining k-mer into a leaf node of the k-mer subset tree. The method includes storing the k-mer subset tree. A computer program product for data compression includes a computer readable storage medium having program instructions embodied therewith. The program instructions are executable by a computer to cause the compute to perform the foregoing method. A system includes a processor and logic. The logic is configured to perform the foregoing method.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting modified media are disclosed. In one aspect, a method includes the actions of receiving an item of media content. The actions further include providing the item as an input to a model that is configured to determine whether the item likely includes audio of a user's voice that was not spoken by the user or likely includes video of the user that depicts actions of the user that were not performed by the user. The actions further include receiving, from the model, data indicating whether the item likely includes audio of the user's voice that was not spoken by the user or includes video of the user that depicts actions of the user that were not performed by the user. The actions further include determining whether the item likely includes deepfake content.

Abstract: The present invention relates to a method of identifying a subgroup of patients suffering from diffuse cutaneous systemic sclerosis (dcSSc) which subgroup of patients benefits from a treatment with at least one sGC stimulator and/or sGC activator in a higher degree than patients not belonging to this subgroup.

Abstract: Processor-implemented systems and methods are provided for generating clusters of technical documents. A method includes analyzing degrees of similarity among the technical documents using a hierarchical taxonomy code similarity model and a text clustering model. Clusters of the technical documents are generated based upon the analyzed degrees of similarity from the models.

Abstract: Video information defining video content may be accessed. Music information defining a music track providing an accompaniment for video content may be accessed. The music track may have pulses and one or more music events. Individual music events may correspond to different moments within the music track. One or more music events may be individually classified into one or more categories based on intensities of one or pulses occurring within the music event. One or more visual effects may be selected for different moments within the music track based on the categories of the music events. One or more visual effects may be applied to the video content. One or more visual effects may be applied to one or more moments within the video content aligned to one or more different moments within the music track.

Abstract: In a method for determining a dialog state, first dialog information is obtained. The first dialog information is dialog information inputted during a dialog process. Based on the first dialog information, target scenario information corresponding to the first dialog information is determined. The target scenario information is used to indicate a dialog scenario of the first dialog information. Based on the first dialog information and the target scenario information, a first dialog state corresponding to the first dialog information is obtained. The first dialog state is used to represent a response mode for responding to the first dialog information.

Abstract: The described technology relates to electronic continuous trading systems, and matching data records representing inventories with variant characteristics such as, variant length, variant data types, etc. Example implementations provide for generating instrument descriptors that include unitary-valued attributes and set-valued attributes, and the use of both types of attributes in trade decision making.

Abstract: A system and method for generating a database query from a natural language using a query engine selector module for identifying appropriate database query format, a query engine builder module to generate appropriate database query using an intermediate query language 2 (IQL2) as input, and a data retriever module for fetching data from single or multiple data sources.

Abstract: An information extraction unit 82 extracts a set including pieces of predetermined information from a past search history for each change of a configuration requirement. A learning unit 83 uses a collection of the sets as learning data to learn a calculation method for calculating a score indicating the degree of appropriateness of a concretizing rule included in the set including the pieces of predetermined information. A search unit 86 repeats extracting the set including the pieces of predetermined information for each pair including a concretizing rule applicable to a configuration requirement of interest and an application part of the concretizing rule in the configuration requirement of interest, calculating a score for the set, and newly selecting a configuration requirement as a configuration requirement of interest based on the score.

Abstract: The disclosed systems and methods provide a systematic approach to analyzing an individual's lifestyle factors (e.g., foods consumed by the individual) that contribute to the individual's current or potential for disease, and taking further action based on that analysis. One example embodiment is a machine learning system that includes a food composition layer, chemical compounds layer, and disease layer. The food composition layer provides representations of chemical compounds of foods consumed or to be consumed by the individual. The chemical compounds layer is coupled to the food composition layer by links and filters the representations of the chemical compounds based on genetic or metabolic information of the individual, resulting in representations of personalized filtered chemical compounds.

Abstract: Systems, methods, and other embodiments associated with a social media assessment tool. According to one embodiment, a social media assessment tool includes an identification logic that identifies interactivity criteria of a social media property. The interactivity criteria are associated with access to the social media property. The social media assessment tool also includes an assessment logic that determines that interactivity criteria satisfy a threshold value. In response to the social media property satisfying the threshold, the assessment logic calculates a score for at least one feature of the social media property.

Abstract: An electronic device is disclosed. The electronic device stores metadata associated with a content item, the metadata including first metadata from a first source and second metadata from a second source. Both the first and second metadata are associated with a particular attribute of the content item. Based on the first and second metadata, preferred metadata is generated for a particular attribute of the content item.

Abstract: An embodiment of a summarization application divides collected conversation data into media and text components. The application implements respective machine learning mechanisms to enhance modeling operations of the text and media components to identify key elements from the conversation. The application generates a headline banner from a group of key elements based on an analysis involving first predetermined criteria. The application also combines additional key elements to the group of key elements to form a second group of key elements. The application generates a summary from the second group of key elements based on a second analysis involving second predetermined criteria. The application presents, via a display, the headline banner according to a first output of the first key element analysis and the summary according to a second output of the second key element analysis.

Abstract: An information processing apparatus includes: a memory; and a processor coupled to the memory and configured to: perform control to store data on the memory; determine a correlation between a plurality of pieces of data, based on pieces of attribute information of the plurality of pieces of data, wherein dispose pieces of data having a high correlation among the plurality of pieces of data at neighboring locations on the memory.

Abstract: Each image of a plurality of user-defined collections of images has properties associated therewith. A seed image is defined as currently viewed or selected image and the properties associated with the seed image are retrieved. The seed image is used to identify seed collections as the collections of images which have the seed image as one of their images. A plurality of candidate images are identified from the seed collections. For each candidate image, a significance score is determined as a function of either the number of seed collections to which the candidate image belongs or the ratio of the number of seed collections to the set of all collections to which the candidate image belongs. Each candidate image is ranked based on the significance scores and the seed image properties. At least one candidate image is recommended to the user based on the ranking of the candidate images.

Abstract: Methods and apparatus to measure exposure to streaming media are disclosed. An example apparatus includes a processor, and memory including machine readable instructions that, when executed, cause the processor to: extract a series of tags associated with media playing on a presentation device, different ones of the tags in the series of the tags embedded in the media at different temporal positions within a duration of the media; identify a first tag from the series of tags to report to a central facility, the first tag identified based on a temporal proximity of the first tag to an event associated with the media playing on the presentation device; and transmit the identified first tag to the central facility, other tags in the series of tags not being transmitted to the central facility.

Abstract: A vehicle controller that controls a vehicle having a first driving mode in which the vehicle travels according to a first control signal based on manual driving or automated driving, and has a second driving mode in which the vehicle travels according to the second control signal based on remote driving is provided, the vehicle controller including a signal comparing unit that compares, to a first control signal, a second control signal acquired by a second control signal acquiring unit while a vehicle control unit is controlling the travelling of the vehicle according to the first control signal, and a mode control unit that causes the vehicle to exit the first driving mode and enter the second driving mode when a comparison result by a signal comparing unit satisfies a predetermined condition.

Abstract: An information processing apparatus includes a generation unit, an adding unit, and an association unit. The generation unit generates, in a case where additional processing needs to be performed on input information in a workflow, unique information for uniquely identifying the information. The adding unit adds the unique information generated by the generation unit to identification information for identifying the information to generate new identification information of the information. The association unit associates the new identification information generated by the adding unit with the information.

Abstract: A method may include obtaining multiple operations configured to be performed in a serial fashion to implement a function. In some embodiments, each operation may be performed with respect to a parameter and an input. The method may also include obtaining an indication of multiple resources configured to perform the operations and a duration for each of the multiple resources to perform each of the multiple operations individually. The method may also include modeling, as a binary optimization, a scheduling of the resources to perform the multiple operations that reduces a total duration to perform the multiple operations based on the duration for each of the multiple resources to perform each of the multiple operations individually. The method may further include solving the binary optimization to determine a schedule of the multiple resources and performing, by the multiple resources, the multiple operations according to the schedule to implement the function.

Abstract: Complex cloud-based system with many different entities, e.g., servers, clients, databases, firewalls, other machines, etc. often require on call engineers to be available to help with maintenance, emergencies, and other tasks. Sometimes ad hoc access is required when on call engineers are unable to resolve a particular issue. Organizations that manually manage access to on call and ad hoc engineer access, may do so relatively easily if they are a smaller organization. But, for larger or more complex environments, manual processes represent a significant burden. An alternative is automatically grant and revoke access. For example, if a vendor tracks your on call engineers, on call statuses may be identified to automatically grant access while on call. For ad hoc access, a requestor may request temporary access, and if valid, access may also be automatically granted for a desired time period. Automation frees valuable limited resources for other tasks.

Abstract: A receiving unit (310) receives a message transmitted from any one of the users that are talk targets. The interpreter (341) attempts to interpret, as an answer to a question, the message received by the receiving unit (310). A collector (342) collects, upon success of the attempt made by the interpreter (341), the interpreted answer as the answer from the user who sends the message. When a predetermined requirement is satisfied in a state where a yet-to-respond user whose answer is not yet collected by the collector (342) is present, an inquiry transmitter (321) transmits an inquiry about the question to at least the yet-to-respond user among the users. A result transmitter (322), after the answers are collected from all of the users, transmits to the users a message indicating a result obtained by tallying the answers.

Abstract: Embodiments for relationship graph expansion and extraction from a collection of unstructured text data by a processor. A query relating to one or more concepts may be received. The query may be expanded according to a logical reasoning operation and a domain ontology having a set of logical rules. A relationship graph between one or more concepts from a plurality of unstructured text data may be extracted based on an expanded query according to a domain ontology and the set of logical rules.

Abstract: In implementations of systems for suggesting content components, a computing device implements a design system to receive input data describing a feature of a content component to be included in a hypertext markup language (HTML) document. The design system represents that feature of the content component as a document object model (DOM) element and determines a hash value for the DOM element using locality-sensitive hashing. Manhattan distances are computed between the has value and has values described by a segment of content component data. The hash values were determined using the locality-sensitive hashing for DOM elements extracted from a corpus of HTML documents. The design system generates indications, for display in a user interface, of candidate content components for inclusion in the HTML document based on the Manhattan distances.

Abstract: A method, system and computer-usable medium for performing a security analysis operation within a security environment, comprising: monitoring electronically-observable user behavior about a particular entity; maintaining a state about the particular entity, the state representing a context of a particular event; converting the electronically-observable user behavior into electronic information representing the electronically-observable user behavior; generating a user behavior profile based upon the electronic information representing the electronically-observable user behavior; and, analyzing the event using the state of the entity and the user behavior profile.

Abstract: Technologies are provided for determining an individual's likelihood of relapsing into prior behavior subsequent to a treatment for a mental health or addiction disorder, and in some instances predicting a likelihood time frame for such a relapse. Target subjects having a risk of addiction relapse, non-adherence to a treatment program, or absconding, may be automatically identified based on a multiplicative-regression model for relative survival (MRS) that is developed for predicting risk or likelihood of relapse or non-adherence. Further, in some embodiments, a leading indicator of near-term future abnormalities may be provided thereby proactively notifying supervisory personnel responsible for the person and providing such personnel with timely notice to enable effective corrective, preventive, or trend-modifying maneuvers to be undertaken.

Abstract: Methods and systems are provided for creating a calendar event using context. A natural language expression including at least one of words, terms, and phrases of text may be received at a calendar event creation module from an application. The calendar event creation module may identify one or more slots in the text of the natural language expression related to the calendar event using a first grammar module and a second grammar module. The one or more slots identified by the first grammar module and the second grammar module that indicate a calendar event may be compared to determine whether there is a match between the one or more identified slots. If a match is found, at least one calendar event using the one or more slots identified by the first grammar module and the second grammar module may be created.

Abstract: A query-focused faceted structure generation method, system, and computer program product for generating a query-focused faceted structure from a taxonomy for searching a document corpus, including augmenting taxonomy types with new instances where the instances comprise entities within a proximity of existing instances of taxonomy types in a local embedding of entities parsed from the document corpus, ranking each instance in the augmented taxonomy with respect to its type as a function of both a distance from an instance to a query in a global embedding vector space of the entities trained from the document corpus and a distance of an instance to a type in the local embedding, and ranking the taxonomy types using expanded instances in the document corpus for each type.