Abstract: According to one embodiment, a method, computer system, and computer program product for object detection. The embodiment may include receiving an annotated image dataset comprising rectangles which surround objects to be detected and labels which specify a class to which an object belongs. The embodiment may include calculating areas of high and low probability of rectangle distribution for each class of objects within images of the dataset. The embodiment may include applying a correction factor to confidence values of object prediction results, obtained during validation of a trained object detection (OD) model, depending on a class label and a rectangle location of an object prediction result and calculating an accuracy of the trained OD model. The embodiment may include increasing the correction factor and re-calculating the accuracy of the trained OD model with every increase. The embodiment may include selecting an optimal correction factor which yields a highest accuracy.

Abstract: Embodiments relate to a system and method for managing energy consumption of one or more processor cores in a multicore processing device. The method includes establishing a temporal interval that includes a plurality of temporal periods and an interval energy target for one or more processor cores. The method also includes determining for each temporal period a period energy target for the processor cores and determining a processor core throttling state for the processor cores. The method further includes adjusting the respective period energy target and the respective processor core throttling state at the beginning of each successive temporal period. The method also includes converging, subject to the adjusting, as each respective temporal period of the plurality of temporal periods is concluded, a total period energy consumption of the processor cores with the interval energy target.

Abstract: A solution is proposed for controlling access to data that are broadcast over a telecommunication medium. A corresponding method comprises validating by a plurality of validator devices an access request that is submitted by an access device for accessing the data. The validator devices update a blockchain by adding a new block comprising an indication of the access request in response to a positive result of its validation. A provider system transmits cryptographic information for decrypting the data to the access device in response to the new block. A corresponding method for broadcasting data by a provider system and a corresponding method for accessing broadcast data by an access device are proposed. Corresponding computer programs and computer program products for performing the methods are also proposed. Moreover, corresponding structure, provider system and access device are proposed.

Abstract: Embodiments are disclosed for a method. The method includes receiving an annotation set for a machine learning model. The annotation set includes multiple data points relevant to a task for the machine learning model. The method also includes determining total weights corresponding to the data points. The total weights are determined based on multiple ordering constraints indicating multiple data classes and corresponding weights. The corresponding weights represent a relative priority of the data classes with respect to each other. The method further includes generating an ordered annotation set from the annotation set. The ordered annotation set includes the data points in a sequence based on the determined total weights.

Abstract: Embodiments of the present disclosure relate to a solution for translation verification and correction. According to the solution, a neural network is trained to determine an association degree among a group of words in a source or target language. The neural network can be used for translation verification and correction. According to the solution, a group of words in a source language and translations of the group of words in a target language are obtained. An association degree among the group of words and an association degree among the translations can be determined by using the trained neural network. Then, whether there is a wrong translation can be determined based on the association degrees. In some embodiments, corresponding methods, systems and computer program products are provided.

Abstract: A method, system and apparatus for protecting against out-of-bounds references, including storing an address of a buffer in a general register and storing bounds information (BI) for the buffer in a bounds information register, and when a content of the general register is used as an address in a load or store operation, using a content of the bounds information register to determine if the load or store is out of bounds.

Abstract: A method, computer program product, and computer system for translating, using a beam search, a source sentence in a source language into a target sentence in a target language by an iterative process.

Abstract: This disclosure provides a method, a computing system, and a computer program product for managing prefetching of pages in a database system. The method comprises obtaining shared information associated with page access, wherein the shared information associated with the page access includes information associated with the page access from a plurality of computing nodes. The method further comprises determining whether to prefetch a number of pages into a global buffer pool based at least on the shared information associated with the page access using a sequential prefetching method.

Abstract: Embodiments are provided for error mitigation in quantum programs. In some embodiments, a system can include a processor that executes computer-executable components stored in memory. The computer-executable components include a compilation component that causes encoding of one or more qubits according to a circular repetition code at a time after operations on the one or more qubits and before readout.

Abstract: A computer-implemented method, a computer system and a computer program product generate a contextual display for a mobile computing device. The method includes identifying a task for the mobile computing device, wherein the task comprises a set of applications on the mobile computing device. The method also includes obtaining application usage data for each application in the set of applications and determining an application context for the task based on the application usage data and the set of applications, wherein the application context includes usage requirements for each application. In addition, the method includes generating a tile view for each application in the set of applications, wherein each tile view is laid out based on the usage requirements. Lastly, the method includes displaying a task view on the mobile computing device, wherein the task view is generated by laying out the tile views based on the usage requirements.

Abstract: Implement one or both of processing of computer queries using machine learning models and/or generation of machine learning models in a computer system. A computer processor generates a plurality of stored machine learning models. A computer processor extracts a plurality of updated parameters sets from the plurality of stored machine learning models. A computer processor creates a new machine learning model based on the respective distribution of each parameter included in the plurality of updated parameters sets. A computer processor processes at least one new query using the new machine learning model.

Abstract: Techniques facilitating hardware-based memory-error mitigation for heap-objects. In one example, a system can comprise a process that executes computer executable components stored in a non-transitory computer readable medium. The computer executable components comprise: an entry component; and a re-purpose component. The entry component can allocate an entry in a table to store bounds-information when an object is allocated in memory. The re-purpose component can re-purpose unused bits of an object address to store an index to the table entry.

Abstract: An approach is provided for training classifiers used in machine learning. A corpus of training data is received. One or more clusters of the training data is generated according to features of the training data. The one or more clusters are refined using user-specified rules. One or more classifiers are trained for use in machine learning based upon the refined one or more clusters.

Abstract: In an approach for compressing a neural network, a processor receives a neural network, wherein the neural network has been trained on a set of training data. A processor receives a compression ratio. A processor compresses the neural network based on the compression ratio using an optimization model to solve for sparse weights. A processor re-trains the compressed neural network with the sparse weights. A processor outputs the re-trained neural network.

Abstract: Various embodiments are provided for intelligent application of operational rules to operational data in a computing environment by a processor. One or more operational rules may be extracted and formalized from a knowledge graph, a domain knowledge, or a combination thereof describing one or more operational policies and conditions. The one or more operational rules may be applied to operational data to identify and filter non-compliant operational data.

Abstract: Disclosed are a computer-implemented method, a system and a computer program product for feature processing. In the computer-implemented method for feature processing, two input features selected from multiple features of each sample in a sample set are projected to one resulting feature by one or more processing units based on a specified curve. The sample set is updated by replacing the two input features with the one resulting feature for each sample in the sample set by one or more processing units. The projecting and the updating for the sample set are repeated by one or more processing units until the number of features of each sample in the sample set reaches a predetermined criterion.

Abstract: A coordinator module for improving communications within a cloud computing system is disclosed. The coordinator module initiates transaction requests by generating a coordination context, where the coordination context includes a transaction context, a coordination type, and an initiator supplemental address. The coordinator module includes a supplemental address handler for creating the initiator supplemental address that unique identifies the coordinator module and the associated pod. The coordinator module receives transaction responses, where the transaction response includes a coordination context. The coordinator module includes a transaction context checker to verify that the transaction response was not received in error, by comparing the received transaction context with a saved transaction context. The coordinator module includes a registration bridge that identifies an alternate coordinator module and alternate pod to process the transaction response if the transaction contexts do not match.

Abstract: Aspects of the present disclosure relate to virtual reality (VR) based commerce experience enhancement. A set of user data associated with a user can be received. A session of a VR commerce environment can be initiated with the user. A set of products to include in the VR commerce environment can be selected based on the set of user data. A position and orientation of each of the products of the set of products within the VR commerce environment can be determined based on the set of user data. The set of products can be displayed within the VR commerce environment according to the determined position and orientation of each product of the set of products.

Abstract: A computer-implemented method according to one embodiment includes building a knowledge graph of resource vendors. The method further includes identifying resources that are in relatively short supply in a host system, and determining, using a matching algorithm, a first of the resource vendors in the knowledge graph from which to temporarily lease the identified resources to the host system. The first resource vendor includes the identified resources and satisfies policy prerequisites of the host system. A lease is caused to be issued, from the first resource vendor to the host system, for the identified resources. A computer program product according to another embodiment includes a computer readable storage medium having program instructions embodied therewith. The program instructions are readable and/or executable by a computer to cause the computer to perform the foregoing method.

Abstract: According to one embodiment, a method, computer system, and computer program product for wearable device activity analysis is provided. A computer receives a video of an activity. The computer identifies the activity based on analyzing the video. The computer identifies body movements from the video. The computer correlates the activity and the body movements to a wearable device. The computer identifies additional inputs for the activity and updates the wearable device based on the identified additional inputs.