Abstract: A method comprising using at least one hardware processor for: providing a set of development supervectors representing features of biometric samples of multiple subjects, the biometric samples being of at least a first and a second different biometric modalities; providing at least a first and a second enrollment supervectors representing features of at least a first and a second enrollment biometric samples of a target subject correspondingly, wherein the at least first and second enrollment samples are of the at least first and the second different biometric modalities correspondingly; providing at least a first and a second verification supervectors representing features of at least a first and a second verification biometric samples of the target subject correspondingly, wherein the at least first and second verification samples are of the at least first and second different biometric modalities correspondingly; concatenating the development supervectors to a set of development generic supervector, the a

Abstract: In one embodiment, a method selects a set of accounts related to a video using a first classifier that is trained to identify the set of accounts from a plurality of accounts and selects a token used to identify the video. A second classifier is trained to identify short messages that are related to the video using a first set of short messages from the accounts related to the video and the second set of short messages including the tokens. A third set of short messages is identified that is related to the video from a plurality of short messages. The method normalizes words in the set of short messages using a mixed model including a lexicon model and a translation model. Then, the method generates a set of ratings for the set of short messages and uses the set of ratings in a service for a video delivery service.

Abstract: A system is provided for control of an entertainment state system having segregated secure functions and public functions for use by one or more users of the system. First, a public interface portal receives instructions regarding operation of the entertainment state system from the one or more users. The interface portal includes a first interface, a processor, a graphical user interface (GUI) coupled to the processor, a control unit in operative communication with the processor and graphical user interface, and a second interface providing an application program interface (API). Secondly, a secure entity unit is provided, the secure entity unit including a receive interface, the receive interface adapted to receive a call from the application program interface (API) of the interface portal, a send interface, the send interface adapted to provide a response to the interface portal interface, a game engine, and a financial engine.

Abstract: Disclosed is a contactless powered and operated self-organizing sensing co-processor system for interacting with an object and one or more peripheral units. The system communicates with a communicating device over a communication network. It includes a hub for providing a modulated alternating electric field with variable frequency and releases routing instructions and further communicates data with the communicating device and one or more nanoCloud processors, wherein at least one of the one or more nanoCloud processors interact with the object and the hub.

Abstract: The present disclosure is directed to parallelization of artificial neural network processing by conditionally synchronizing, among multiple computer processors, either the input or output of individual operations, and by conditionally using either rows or columns of certain matrices used in the operations. The conditional processing may depend upon the relative sizes of the input and output of the specific operations to be performed. For example, if a current layer matrix of values is larger than a next layer matrix of values to be computed, then rows of a weight matrix may be used by the computer processors to compute the next layer matrix. If the current layer matrix is smaller than the next layer matrix, then columns of the weight matrix may be used by the computer processors to compute the next layer matrix.

Abstract: Artificial intelligence methods and systems for triggering the generation of narratives are disclosed. Specific embodiments relate to real-time evaluation and automated generation of narrative stories based on received data. For example, data can be tested against data representative of a plurality of story angles to determine whether a narrative story incorporating one or more such story angles is to be automatically generated.

Abstract: According to an embodiment, an automaton deforming device includes a transforming unit and a deforming unit. The transforming unit generates second values by transforming first values, which either represent weights assigned to transitions in a weighted finite state automaton or represent values that are transformed into weights assigned to transitions in a weighted finite state automaton, in such a way that number of elements of a set of the first values are reduced and an order of the first values is preserved. The deforming unit deforms a weighted finite state automaton in which weights according to the second values are assigned to transitions.

Abstract: In one embodiment, a computer-implemented method includes transforming a plurality of electronic health records into a plurality of temporal graphs indicating an order in which events observed in the plurality of electronic health records occur and learning a temporal pattern from the plurality of temporal graphs, wherein the temporal pattern indicates an order of events that is observed to occur repeatedly across the plurality of temporal graphs.

Abstract: A system for estimating data in large datasets for an equipment system is provided. The system includes a data estimation and forecasting (DEF) computing device. The DEF computing device arranges a dataset in a primary matrix and parses rows of the primary matrix and generates a sample matrix by selecting primary matrix rows having non-null values for each variable. The DEF computing device adds to the sample matrix rows that include non-null values for each variable except one. The DEF computing device generates normalized values for this augmented matrix, applies several techniques including probabilistic principal component analysis (PPCA) and Markov processes, and scales the augmented matrix to normalized values. The DEF computing device generates non-null values for the variable, scales the augmented matrix back to the sample matrix, and generates a forecast for the equipment system, directing a user to update logistics processes for the equipment system.

Abstract: Systems and methods for reconstruction of missing data using iterated geometric harmonics are described herein. A method includes receiving a dataset having missing entries, initializing missing values in the dataset with random data, and then performing the following actions for multiple iterations. The iterated actions include selecting a column to be updated, removing the selected column from the dataset, converting the dataset into a Gram matrix using a kernel function, extracting rows from the Gram matrix for which the selected column does not contain temporary values to form a reduced Gram matrix, diagonalizing the reduced Gram matrix to find eigenvalues and eigenvectors, constructing geometric harmonics using the eigenvectors to fill in missing values in the dataset, and filling in missing values to improve the dataset and create a reconstructed dataset. The result is a reconstructed dataset. The method is particularly useful in reconstructing image and video files.

Abstract: Techniques are described for automatic suggestion for socially connected experts in electronic discussions. In one example, techniques include extracting topics from an electronic discussion, generating a list of experts in the topics, and editing the list according to social closeness to participants in the electronic discussion.

Abstract: Computer-implemented systems and methods are disclosed for automatically generating predictive models using data driven featurization. The systems and methods provide for obtaining data associated with a target event, annotating the data to identify a target event and establishing one or more limits on the data, censoring the data based on the annotations, determining features of the censored data, and analyzing the features to determine a predictive model. In some embodiments, the systems and methods further provide for converting the features into a binary representation and analyzing the binary representation to produce the predictive model.

Abstract: Embodiments of the present invention provide methods, computer program products, and systems for classification and identification of cancer genes while correcting for sample bias for tumor-derived genomic features as well as other biased features using machine learning techniques. Embodiments of the present invention can be used to receive a set of genes that include a first gene and a subset of synthetic genes that include similar features to the first gene and receive a set of gene labels associated with physiological characteristics. Embodiments of the present invention can estimate probabilities that genes in the set of genes are associated with gene labels in the set of gene labels using a machine learning classifier and estimate an effective probability range for the first gene and each gene label based, at least in part, on the first gene's estimated probabilities and the estimated probabilities of one or more of the synthetic genes.

Abstract: Some embodiments include a method of detecting memes, as “key terms,” in a chatter aggregation in a social networking system. The method can include aggregating user-generated content objects within the social networking system into the chatter aggregation according to a set of filters. A meme analysis engine can define a target group within the chatter aggregation to compare against a background group. The meme analysis engine can extract key terms from textual content of the target group. The meme analysis engine can determine a relevancy rank of a term in the key terms based on an accounting of the term in the textual content of the target group and a linguistic relevance score of the term according to a linguistic model.

Abstract: A method and system are provided for performing a legal document search. The method includes finding, by a processor, for each of a plurality of documents, a respective law clause related thereto, to obtain a plurality of related law clauses. The method further includes constructing, by the processor, a graph having nodes defined by the plurality of documents and the plurality of related law clauses and having edges defined by (1) relations between the plurality of documents and the plurality of related law clauses and (2) relations between the plurality of documents. The method further includes identifying, by the processor, from the plurality of documents, one or more candidate documents that are similar to an input query document by mining the graph using similarity criteria.

Abstract: The methods and systems described herein relate to conducting a controlled experiment using prediction of future user behavior. The method, executable on at least one server, comprises: collecting behavior data on two sets of users over a first period, wherein: the first set of users is exposed to a control; the second set of users is exposed to a treatment variant; and the behavior data relates to a performance parameter of the controlled experiment; based on a prediction model applied to the behavior data, calculating predicted values of the performance parameter for each user of the first set and the second set of users over a second period of time; and determining if a difference exists between the predicted values of the performance parameter for each user of the first set of users and the predicted values of the performance parameter for each user of the second set of users.

Abstract: A system and method for generating an advertisement effectiveness performance score of a multimedia content element displayed in a webpage are provided. The method includes determining an advertisement context of an advertisement; analyzing metadata associated with at least one prior advertisement to determine a prior advertisement success score; determining a multimedia context of the multimedia content element displayed in the webpage; matching the advertisement context to the multimedia context to determine a context matching score; and generating an advertisement effectiveness score at least based on the prior advertisement success score and the context matching score.

Abstract: A method and system analyze data in a database. The method and system include defining a plurality of set of rules, wherein each set of rules corresponds to a predictive model, storing the each set of rules corresponding to the predictive model in a library as a user-defined function, and calling the user-defined function via a standard sequel language.

Abstract: A method of quantizing a floating point machine learning network to obtain a fixed point machine learning network using a quantizer may include selecting at least one moment of an input distribution of the floating point machine learning network. The method may also include determining quantizer parameters for quantizing values of the floating point machine learning network based at least in part on the at least one selected moment of the input distribution of the floating point machine learning network to obtain corresponding values of the fixed point machine learning network.

Abstract: Described is a system for securely searching streaming data. The system executes a secure pattern matching protocol between a client and at least one of a server and a processing element. Using the processing element, an encryption of a character delay based on a pattern to be searched is received. Streaming data is received at the processing element. A secure search is performed blindly at the processing element to find a match for the pattern in the streaming data, the search being performed using the encryption of the character delay vector. Encrypted results from the secure search are sent back to the client.