Abstract: Methods and systems disclosed herein collect user data in real-time and organize them (e.g., using collaborative filtering) into groups (e.g., clusters). The system then determines statistical distributions of observed real-time intents (e.g., based on actual selections made by users) for each group. The system then merges this distribution with existing model predictions (e.g., a model trained on historical training data) to balance between historical and dynamically updated information.

Abstract: Described are a method for the manufacture of a shoe sole, the sole manufactured by the method, and a shoe including the sole. The method includes loading a pre-manufactured article comprising thermoplastic polyurethane (TPU) material into a mold; loading pellets of an expanded thermoplastic polyurethane (eTPU) material into said mold; and connecting the pellets with each other and to the pre-manufactured TPU article by providing an interconnecting medium, wherein the material of the pre-manufactured TPU article either comprises an additive to increase the viscosity of the material of the pre-manufactured TPU article, or has been annealed.

Abstract: Described are methods for manufacturing a plastic component, in particular a cushioning element for sports apparel, a plastic component manufactured with such methods, for example a sole or a part of a sole for a shoe, and a shoe with such a sole. The method for the manufacture of a plastic component includes loading a mold with a first material includes particles of an expanded material and fusing the surfaces of the particles by supplying energy. The energy is supplied in the form of at least one electromagnetic field.

Abstract: Edit automation functionality generalizes edits performed by a user in a document, locates similar text, and recommends or applies transforms while staying within a current workflow. Source code edits such as refactoring are automated. The functionality uses or provides anchor target lists, temporal edit patterns, edit graphs, automatable edit sequence libraries, and other data structures and computational techniques for identifying locations appropriate for particular edits, for getting transforms, for selecting optimal transforms, for leveraging transforms in an editing session or later, and for displaying transform recommendations and results. The edit automation functionality enhances automation subtool generation, discoverability, and flexibility, for refactoring, snippet insertion, quick actions in an integrated development environment, and other automatable edit sequences.

Abstract: Edit automation functionality generalizes edits performed by a user in a document, locates similar text, and recommends or applies transforms while staying within a current workflow. Source code edits such as refactoring are automated. The functionality uses or provides anchor target lists, temporal edit patterns, edit graphs, automatable edit sequence libraries, and other data structures and computational techniques for identifying locations appropriate for particular edits, for getting transforms, for selecting optimal transforms, for leveraging transforms in an editing session or later, and for displaying transform recommendations and results. The edit automation functionality enhances automation subtool generation, discoverability, and flexibility, for refactoring, snippet insertion, quick actions in an integrated development environment, and other automatable edit sequences.

Abstract: Methods and systems are described for generating dynamic conversational responses using two-tier machine learning models. The dynamic conversational responses may be generated in real time and reflect the likely goals and/or intents of a user. The two-tier machine learning model may include a first tier that determines an intent cluster based on a feature input, and a second tier that determines a specific intent from the cluster.

Abstract: A method and an associated controller for safely operating a multi-axis kinematic system by using a safety function are disclosed. The method includes calculating compensation values at the run time of a controller of the multi-axis kinematic system, wherein the calculation is performed based on predefinable error values of respective axes, geometric parameters of the multi-axis kinematic system, and current axis values of the multi-axis kinematic system. The method further includes operating the safety function based on the calculated compensation values.

Abstract: A method of image compression includes receiving an image. Multiple quantized latent representations are generated to represent features of the image. Each of the quantized latent representations has a different resolution and is generated at staggered timings. Each of the later generated quantized latent representations is conditioned on each of the prior generated quantized latent representations. The multiple quantized latent representations are decoded to reconstruct the image.

Abstract: A method for setting up safe operation of a multi-axis kinematic system, a method for safely operating a multi-axis kinematic system, and to an input device for setting up safe operation of a multi-axis kinematic system and a corresponding computer program product. A method includes providing error values of respective axes and ascertaining a compensation value for at least one variable of the safety function on the basis of the error values, on the basis of geometric parameters of the multi-axis kinematic system and on the basis of axis values of the respective axes that are obtained from trajectories of the multi-axis kinematic system.

Abstract: Unidimensional embedding using multi-modal deep learning models. An autoencoder executing on a processor may receive transaction data for a plurality of transactions, the transaction data including a plurality of fields, the plurality of fields including a plurality of different data types. An embeddings layer of the autoencoder may generate an embedding vector for a first transaction, the embedding vector includes floating point values to represent the plurality of data types of the transaction data. One or more fully connected layers of the autoencoder may generate, based on the embedding vector, a plurality of statistical distributions for the first transaction, each statistical distribution includes a respective embedding vector. A sampling layer of the autoencoder may sample a first statistical distribution of the plurality of statistical distributions. A decoder of the autoencoder may decode the first statistical distribution to generate an output representing the first transaction.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a method may include receiving data representing a query into a collaborative dataset consolidation system, identifying datasets relevant to the query, generating one or more queries to access disparate data repositories, and retrieving data representing query results. In some cases, one or more queries are applied (e.g.

Abstract: Various techniques are disclosed for computerized tools to discover, form, and analyze dataset interrelations among a system of networked collaborative datasets including a repository configured to receive and store a dataset, and a dataset consolidation system configured to receive data to form a first input to initiate creation of a dataset based on a set of data, to activate a programmatic interface, to transform the set of data from a first format to an atomized format to form an atomized dataset, to monitor the creation of the dataset, to present data representing a status of a portion of the creation of the dataset, to calculate automatically dataset attributes of the linked dataset, to generate a plurality of sub-queries, and to retrieve data representing query results from the at least one of the different data repositories.

Abstract: Described are a method for the manufacture of a shoe sole, the sole manufactured by the method, and a shoe including the sole. The method includes loading a pre-manufactured article comprising thermoplastic polyurethane (TPU) material into a mold; loading pellets of an expanded thermoplastic polyurethane (eTPU) material into said mold; and connecting the pellets with each other and to the pre-manufactured TPU article by providing an interconnecting medium, wherein the material of the pre-manufactured TPU article either comprises an additive to increase the viscosity of the material of the pre-manufactured TPU article, or has been annealed.

Abstract: Methods and systems are described for generating dynamic interface options using machine learning models. The dynamic interface options may be generated in real time and reflect the likely goals and/or intents of a user. The machine learning model may provide these features by interpreting multi-modal feature inputs. For example, the machine learning model may include a first machine learning model, wherein the first machine learning model comprises a convolutional neural network, and a second machine learning model, wherein the second machine learning model performs a Weight of Evidence (WOE) analysis.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a method may include receiving a dataset having a data format into a dataset ingestion controller configured to form a collaborative dataset, interpreting data of the dataset against data classifications at an inference engine to derive at least an inferred attribute, associating the data with annotative data identifying the inferred attribute, and converting the dataset at a format converter to form an atomized dataset.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to provide an interface between repositories of disparate datasets and computing machine-based entities that seek access to the datasets, and, more specifically, to a computing and data storage platform that facilitates consolidation of one or more datasets, whereby a collaborative data layer and associated logic facilitate, for example, efficient access to, and implementation of, collaborative datasets. In some examples, a system may include data ingestion controller configured to format datasets to form a first and a second atomized dataset, the second atomized dataset including the first atomized dataset and one or more other atomized datasets. The system may include a dataset query engine configured to identify a portion of a dataset relevant to a query, and to retrieve query results from at least one of different data repositories.

Abstract: Various techniques are described for platform management of integrated access of public and privately-accessible datasets utilizing federated query generation and query schema rewriting optimization, including receiving at a dataset access platform a query formatted according to a first data schema, generating a copy of the query, saving the query and the copy to a datastore, parsing the copy of the query in the first schema using an inference engine, determining whether the query comprises data associated with an access control condition associated with accessing the dataset, the access control condition being configured to indicate whether the query is permitted to access the dataset, and rewriting, using a proxy server, the copy of the query in a second schema, and optimizing the rewriting by identifying a database engine to execute the query and including other data converted into another triple associated with an attribute of the query.

Abstract: Methods and systems are described herein for dynamically selecting alternative content based on real-time events during device sessions using a cross-channel, time-bound deep reinforcement machine learning. The use of this architecture allows for alternative content to be selected in a time-bound and continuous manner that provides predictions in a dynamic environment (e.g., an environment in which user data is continuously changing and new events are continuously occurring) and with an increased success rate (e.g., new data and events are factored into each prediction). For example, in the system each round of predictions considers both input features, which can change by a user's actions, state of a user interface, and/or previous responses and states.

Abstract: The present invention relates to methods of selecting a subject with cancer for treatment, screening a test molecule for use as a cancer therapeutic, and treating a subject with cancer, as well as compositions for treating cancer.

Abstract: Various techniques are described for platform management of integrated access of public and privately-accessible datasets utilizing federated query generation and query schema rewriting optimization, including receiving at a dataset access platform a query formatted according to a first data schema, generating a copy of the query, saving the query and the copy to a datastore, parsing the copy of the query in the first schema using an inference engine, determining whether the query comprises data associated with an access control condition associated with accessing the dataset, the access control condition being configured to indicate whether the query is permitted to access the dataset, and rewriting, using a proxy server, the copy of the query in a second schema by converting the copy of the query into a triple associated with the query and another triple associated with the access control condition.