Abstract: A bias compensation method, system, and computer program product include modifying a behavior of a first analytic engine service with a second analytic engine service, where the first service accepts user submitted data and communicates an assessment of the data in a form of a label associated with the corresponding submitted data, where the second service accepts an input and communicates an assessment in a form of a label associated with the corresponding input, and where a behavior model of the first service and the second service includes a discrepancy between the output labels by each service with respect to true labels of data accepted, further including composing a new analytic engine service from the first service and the second service to optimize a service bias in terms of a test dataset based on the behavior model and the known true assessments.

Abstract: An AI model is trained by determining insights for a sequence of computations used in the AI model. The sequence is applied to encrypted data and label pair(s), wherein computational details of each of the computations are defined. Information may also be committed for selected ones of the sequence of computations into a distributed database. The committed information may include computational details used in processing performed for the selected computations, and the distributed database may have a property that the committed information for each selected computation is linked with a verifiable signature of integrity with a previously committed computation in the sequence. Indication is received from an end-user computer system of selected computation(s). Computational details of the indicated selected computation(s) are sent toward the end-user computer system for use by the end-user computer system for verifying the indicated selected computation(s).

Abstract: Embodiments include methods, systems, and computer program products for treating skin lesions. Aspects include receiving an indication that a patient is oriented. Aspects also include acquiring data concerning an area of the patient, the area including a skin lesion. Aspects also include analyzing the data to distinguish between an affected region and an unaffected region of the area of the patient. Aspects also include excising the affected area.

Abstract: A face clustering system for video face clustering in a video sequence, the system including an inherent supervision summarization device configured to collect group-level supervision and instance level supervision within a same chunklet based on a user input of face images for a person, a discriminative projection learning device configured to embed group constraints of the group-level supervision into a transformed space, and configured to generate an embedding space from the original image feature space, and a clustering device, in the embedding space, configured to execute pair-wise based clustering to cluster the video images into different clusters with the instance level supervision collected by the inherent supervision summarization device.

Abstract: An anonymized biometric representation of a target individual is used in a computer based security system. A detailed input biometric signal associated with a target individual is obtained. A weakened biometric representation of the detailed biometric signal is constructed such that the weakened biometric representation is designed to identify a plurality of individuals including the target individual. The target individual is enrolled in a data store associated with the computer based security system wherein the weakened biometric representation is included in a record for the target individual. In another aspect of the invention, a detailed input biometric signal from a screening candidate individual is obtained. The detailed biometric signal of the screening candidate is matched against the weakened biometric representation included in the record for the target individual.

Abstract: A face clustering system for video face clustering in a video sequence, the system including an inherent supervision summarization device configured to collect group-level supervision and instance level supervision within a same chunklet based on a user input of face images for a person, a discriminative projection learning device configured to embed group constraints of the group-level supervision into a transformed space, and configured to generate an embedding space from the original image feature space, and a clustering device, in the embedding space, configured to execute pair-wise based clustering to cluster the video images into different clusters with the instance level supervision collected by the inherent supervision summarization device.

Abstract: A computer system receives a set of data encrypted by a homomorphic encryption transformation. The computer system performs machine learning operations using the encrypted set of data. The machine learning operations build, using homomorphic operations, a trained model of the data having a mapping between the encrypted data and output of the trained model. The model is stored for use for performing inferencing of other encrypted data to determine a corresponding output of the trained model. The computer system may perform inferencing of the other encrypted data at least by accessing the stored trained model and predicting by using the trained model a label in an encrypted format that corresponds to the other encrypted data. The computer system may send the label toward the client for the client to decrypt the label.

Abstract: An example operation may include one or more of joining, by a host device, a blockchain managed by one or more devices on a decentralized network, the blockchain is configured to use one or more smart contracts that specify transactions among a plurality of end-users, creating on the blockchain the smart contract defining authentication parameters for an authentication of an end-user from the plurality of the end-users, executing the smart contract to perform the authentication of the end-user associated with a transaction based on the authentication parameters by generating an authentication challenge for the transaction, and recording an authentication log produced by the authentication challenge into a metadata of a transaction payload for analytics.

Abstract: A method of displaying information relating to an allergen present in a food substance together with a user profile, the method including capturing an image of a scene, segmenting the image to determining at least a segmentation of the food substance in the image, determining a classification of the food substance using the segmentation, determining a presence of the allergen in the food substance using the classification of the food substance and a database of allergens and food substances, determining a risk to a user using the user profile specifying a user sensitivity to the allergen, and displaying an output including a view of the user profile and the image, wherein the image is augmented to identify the presence of the allergen.

Abstract: An example operation may include one or more of obtaining a first biometric sample of a user from a user device. extracting, by an issuing node of a permissioned blockchain network, a biometric template from the first biometric sample, encrypting the biometric template, distributing an issuetoken proposal comprising the encrypted biometric template to the blockchain network, and generating and distributing a biometric token to the user device. In response to the user indicating to the user device to redeem the biometric token, the method includes one or more of presenting, by the user device, the biometric token to a verifying node of the blockchain network, validating, by the verifying node, the biometric token, receiving, by the verifying node, a second biometric sample from the user device, distributing a redeemtoken proposal to the blockchain network, committing a transaction corresponding to the biometric token, to the blockchain network, and invalidating the biometric token.

Abstract: Embodiments include methods, systems, and computer program products for detection and remediation of anxiety. Aspects include receiving an anxiety indicator. Aspects also include analyzing the anxiety indicator to determine whether an anxiety level exceeds an anxiety threshold. Aspects also include, based upon a determination that the anxiety level exceeds the anxiety threshold, selecting a first sound. Aspects also include outputting the first sound. Aspects also include receiving an anxiety feedback. Aspects also include determining, based upon the anxiety feedback, whether the anxiety level is decreasing.

Abstract: Parallel linguistic corpora used to train cognitive translation systems are built from robot plans. A collection of robot plans in various languages is analyzed in candidate pairings to see if any two plans are directed to the same task. If so, verbal instructions in different languages from the two plans (such as plan names) are assumed to have the same meaning, and are stored in association as part of the bilingual corpus. If each plan has multiple steps, the corresponding steps from the two plans can also be stored in association as part of the corpus. Robot plans are modeled as finite state automata having a plurality of links representing sensory states and a plurality of nodes representing motor actions, and the determination of plan similarity is based on a comparison of the two FSAs.

Abstract: An example operation may include one or more of detecting a suspected biometric authentication incident, submitting a first blockchain transaction including a first report to a blockchain network, submitting a second blockchain transaction including a second report to the blockchain network, and taking an action, by one or more blockchain nodes, in response to determining one or more of the first and second reports are relevant to the one or more blockchain nodes. The first report includes public and private data corresponding to the suspected biometric authentication incident, and the second report includes one or more of a root cause and mitigation steps for the incident.

Abstract: Embodiments include method, systems and computer program products for safeguarding biometric data. Aspects include receiving a first biometric data unit and generating a template based upon the first biometric data unit. Aspects also include sending the template to a plurality of external template storage devices, each template storage device having a unique device identifier. Aspects also include generating a biometric query including a second biometric data unit. Aspects also include sending the biometric query to at least some of the plurality of external template storage devices. Aspects also include receiving a match score from at least one of the plurality of template storage devices external to the processor, wherein the match score reflects the degree of similarity between the first biometric data unit and the second biometric data unit.

Abstract: Techniques for leveraging the capabilities of wearable mobile technology to collect data and to provide real-time feedback to an orator about his/her performance and/or audience interaction are provided. In one aspect, a method for providing real-time feedback to a speaker making a presentation to an audience includes the steps of: collecting real-time data from the speaker during the presentation, wherein the data is collected via a mobile device worn by the speaker; analyzing the real-time data collected from the speaker to determine whether corrective action is needed to improve performance; and generating a real-time alert to the speaker suggesting the corrective action if the real-time data indicates that corrective action is needed to improve performance, otherwise continuing to collect data from the speaker in real-time. Real-time data may also be collected from members of the audience and/or from other speakers (if present) via wearable mobile devices.

Abstract: Embodiments include methods, systems, and computer program products for detection and remediation of anxiety. Aspects include receiving an anxiety indicator. Aspects also include analyzing the anxiety indicator to determine whether an anxiety level exceeds an anxiety threshold. Aspects also include, based upon a determination that the anxiety level exceeds the anxiety threshold, selecting a first sound. Aspects also include outputting the first sound. Aspects also include receiving an anxiety feedback. Aspects also include determining, based upon the anxiety feedback, whether the anxiety level is decreasing.

Abstract: A method establishes a session between a network service and a user device used by the user having a particular sociometric identity. One or more processors identify an interaction between a user and one or more provider entities. The processor(s) identify profiles for the one or more provider entities, where each profild of the one or more provider entities describes a type of service provided by a respective provider entity of the one or more provider entities, and compute a sociometric identity of the user based on the profiles of the one or more provider entities with which the user has had an interaction. One or more processors transmit the sociometric identity to a network service in order to establish a session between the network service and a user device used by the user having the sociometric identity.

Abstract: Mechanisms are provided for training a classifier to identify adversarial input data. A neural network processes original input data representing a plurality of non-adversarial original input data and mean output learning logic determines a mean response for each intermediate layer of the neural network based on results of processing the original input data. The neural network processes adversarial input data and layer-wise comparison logic compares, for each intermediate layer of the neural network, a response generated by the intermediate layer based on processing the adversarial input data, to the mean response associated with the intermediate layer, to thereby generate a distance metric for the intermediate layer. The layer-wise comparison logic generates a vector output based on the distance metrics that is used to train a classifier to identify adversarial input data based on responses generated by intermediate layers of the neural network.

Abstract: A neural network is configured to suppress an output of a mitigation node in a mitigation layer of the neural network. The neural network is pre-configured to recognize objects from inputs when operating using a processor and a memory. An actual input is sent to the neural network for object recognition, the actual input is an altered input. By suppressing the output of the mitigation node, the neural network is caused to avoid falsely recognizing an object from the actual input, where the altered input is configured to cause the neural network to falsely recognize the object from the actual input.

Abstract: A method of displaying information relating to an allergen present in a food substance together with a user profile, the method including capturing an image of a scene, segmenting the image to determining at least a segmentation of the food substance in the image, determining a classification of the food substance using the segmentation, determining a presence of the allergen in the food substance using the classification of the food substance and a database of allergens and food substances, determining a risk to a user using the user profile specifying a user sensitivity to the allergen, and displaying an output including a view of the user profile and the image, wherein the image is augmented to identify the presence of the allergen.