Abstract: A method for analyzing time-series data is provided. The method includes: identifying, from within a first set of time-series data, data sequences that correspond to patterns, each data sequence being representative of a predetermined time interval; converting the data sequences into respective pattern images; receiving a second set of time-series data; converting the second set of time-series data into an additional image; comparing each of the pattern images with a portion of the additional image that corresponds to a most recent time interval; and determining whether the portion of the additional image that corresponds to the most recent time interval corresponds to any of the patterns based on a result of the comparison.

Abstract: A method for forecasting a change in a market is provided. The method includes: using historical market data to generate a plurality of first images that correspond to a predetermined time sequence; generating, based on the plurality of first images, second images that correspond to a future time point with respect to the predetermined time sequence; and determining a prediction of future market data based on the second images. The generation of the second images and the prediction of the future market data are implemented by applying a convolutional neural network (CNN) algorithm that implements a stochastic latent residual video prediction (SRVP) technique with respect to a group of financial assets.

Abstract: A method for creating a realistic agent-based simulation of an over-the-counter market and using data from the real market to calibrate the simulator is provided. The method includes: assigning, to each of a group of agents, a type value that relates to a state of the respective agent; receiving agent-specific data that relates to market-based observations, market-based actions, and market-based rewards; generating a market simulation based on the assigned type values and the received agent-specific data; and calibrating the market simulation based on actual market data.

Abstract: A method for detecting an anomaly in human behavior is provided. The method includes: receiving information that relates to a behavior of a person; determining at least one behavior trace based on the received information; classifying each behavior trace into a respective category from among a first category that corresponds to behaviors that indicate an intention to commit a crime, such as money laundering, and a second category that corresponds to behaviors that indicate standard non-criminal activity; and analyzing each behavior trace to determine a potential intended goal of the person. The behavior trace includes a sequence of behavioral states and actions performed by the person in response to each respective behavioral state.

Abstract: A method for heuristics-based link prediction in multiplex networks may include a link prediction computer program: receiving a model for a multiplex network; defining a property matrix that specifies feature for cross-layer correlation; constructing a cross-correlation matrix from the property matrix; applying a count and weight correlation heuristic to the cross-correlation matrix, wherein the count and weight correlation heuristic counts a number of layers that contain a link between two nodes, and weights that count according to cross-layer correlations; applying a correlation weighted heuristic to the cross-correlation matrix; applying a count correlation-weighted heuristic to the cross-correlation matrix that counts the number of layers that contain a link between two nodes and weights that count according to both cross-layer correlations and values resulting from evaluating a monoplex heuristic applied to each layer in the multiplex network, resulting in output values; and identifying a missing link ba

Abstract: Systems and methods for applying game theory for fraud detection. Rather than inspecting every transaction record, embodiments are directed to limiting incoming suspicious transaction records according to a schedule. The schedule may define time windows for various clients and transactions. These time windows may filter down the stream of incoming transaction records to a subset. As a result, fraud may be detected by strategically allocating resources in an optimal way rather than attempting to inspect each and every instance of transaction.

Abstract: Systems and methods for digital document generation using natural language interaction are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for digital document generation using natural language interaction may include: (1) receiving from an electronic device, a natural language command comprising an action to generate digital content, an object, and a data source for the digital content; (2) processing the natural language command to identify the action, the type of digital content, and the data source; (3) identifying a skill in a skill library that is mapped to the action and the object; (4) retrieving data from the data source for the skill; and (5) generating the digital content according to the skill using the data.

Abstract: Systems and methods for risk-sensitive reinforcement learning are disclosed. In one embodiment, a method for a method for training a risk-sensitive reinforcement learning policy may include: (1) receiving, from a data source, a plurality of sets of training data for a plurality of time steps; (2) receiving a training budget comprising a plurality of episodes, a risk aversion coefficient, and an end state; and (3) calculating a correction factor using the training data. The correction factor may minimize stochasticity based on a risk aversion coefficient.

Abstract: Systems and methods for privacy-preserving inventory matching are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for inventory matching may include: (1) receiving, from each of a plurality of clients, a masked submission comprising an identification of at least one security to buy or sell and a desired quantity to buy or sell; (2) aggregating the masked submissions resulting in a sum of the desired quantities to buy or sell; (3) matching at least two of the clients to conduct a transaction based on aggregation and their respective masked submissions; and (4) conducing the transaction between the matched clients.

Abstract: Systems and methods for privacy-preserving summarization of digital activity are disclosed. According to one embodiment in an information processing apparatus comprising at least one computer processor and at least one display, a privacy-preserving digital activity computer program performing the following: (1) capturing a blurred or pixelated screenshot of the at least one display; (2) identifying a plurality of computer application visible in the blurred or pixelated screenshot; (3) identifying a foreground or actively-used application out of the plurality computer applications in the blurred or pixelated screenshot; and (4) logging the visible computer applications and the foreground or actively-used application.

Abstract: A method for using images that represent time-series data to forecast future images depicting future values as pixelated information is provided. The method includes: receiving a first set of time-series data; converting the received first set of time-series data into a first image; and using the first image to forecast a future image depicting future values as pixelated information that corresponds to a future time interval Training sets of time-series data are used to generate historical data that provides input to a machine learning algorithm, which provides, as an output, a composite image that depicts the future values as pixelated information that reflects associated uncertainties in the value predictions.

Abstract: A method, comprising displaying an image to a first player, displaying a portion of the image to a second player wherein the portion of the image displayed to the second player is less than all of the image and wherein the portion of the image displayed to the second player is determined by an action of the first player, allowing the second player to submit a word, and determining whether the word submitted by the second player is related to the image. The present invention also includes apparatuses and systems.