Abstract: Embodiments of the present disclosure provide method, system and computer program product for privacy preserving smart metering. According to one embodiment of the present disclosure, a plurality of customer-encrypted meter readings are received, each of the plurality of customer-encrypted meter readings being encrypted by a customer using a customer key, then a summation of customer keys is obtained, next the plurality of customer-encrypted meter readings are summed, and the summation of the plurality of customer-encrypted meter readings is decrypted based on the obtained summation of customer keys.

Abstract: Techniques for neural network training are provided. One computer-implemented method comprises: obtaining, by an electronic device operatively coupled to a processing unit, based on a similarity between two images, a first image and a second image. The computer-implemented method also comprises training, by the electronic device, a neural network based on the first image and the second image such that a distance between a first vector and a second vector generated respectively from the first image and the second image in the trained neural network is associated with the similarity.

Abstract: Techniques for model based data processing are proposed. In one example, a computer-implemented method is as follows. A first model is determined from a first category of data processing models and a second model is determined from a second category of data processing models. The second category can be different from the first category in some instances. Performance of a first combined model of the first and second models can be compared with performance of the first model. A target model for processing data can be selected from the first combined model and the first model based on the comparing.

Abstract: Method, computer program products, system are provided for job role identification. The computer implemented method comprises that receiving product purchase data of a plurality of organizations which comprise buyer information and product information and generating based on the buyer information and the product information, a plurality of buyer clusters. Further, at least one job role for at least one generated buyer cluster is determined.

Abstract: Techniques are provided for providing a local computation service on client device authorized by a remote service provider while keeping local data private from the remote service provider. In one example, a computer-implemented method comprises transmitting, by a device operatively coupled to a processor, a homomorphic encryption public key and homomorphically encrypted input data to a service provider. The computer-implemented method also comprises receiving, by the device from the service provider, a homomorphically encrypted signature generated based on the homomorphic encryption public key, the homomorphically encrypted input data, and a homomorphic encryption equivalent defined function.

Abstract: Techniques are provided for providing a local computation service on client device authorized by a remote service provider while keeping local data private from the remote service provider. In one example, a computer-implemented method comprises transmitting, by a device operatively coupled to a processor, a homomorphic encryption public key and homomorphically encrypted input data to a service provider. The computer-implemented method also comprises receiving, by the device from the service provider, a homomorphically encrypted signature generated based on the homomorphic encryption public key, the homomorphically encrypted input data, and a homomorphic encryption equivalent defined function.

Abstract: Techniques for neural network training are provided. One computer-implemented method comprises: obtaining, by an electronic device operatively coupled to a processing unit, based on a similarity between two images, a first image and a second image. The computer-implemented method also comprises training, by the electronic device, a neural network based on the first image and the second image such that a distance between a first vector and a second vector generated respectively from the first image and the second image in the trained neural network is associated with the similarity.

Abstract: Techniques for model based data processing are proposed. In one example, a computer-implemented method is as follows. A first model is determined from a first category of data processing models and a second model is determined from a second category of data processing models. The second category can be different from the first category in some instances. Performance of a first combined model of the first and second models can be compared with performance of the first model. A target model for processing data can be selected from the first combined model and the first model based on the comparing.

Abstract: Embodiments of the present disclosure provide method, system and computer program product for privacy preserving smart metering. According to one embodiment of the present disclosure, a plurality of customer-encrypted meter readings are received, each of the plurality of customer-encrypted meter readings being encrypted by a customer using a customer key, then a summation of customer keys is obtained, next the plurality of customer-encrypted meter readings are summed, and the summation of the plurality of customer-encrypted meter readings is decrypted based on the obtained summation of customer keys.

Abstract: A system and method for speech recognition includes determining active Gaussians related to a first feature stream and a second feature stream by labeling at least one of the first and second streams, and determining active Gaussians co-occurring in the first stream and the second stream based upon joint probability. A number of Gaussians computed is reduced based upon Gaussians already computed for the first stream and a number of Gaussians co-occurring in the second stream. Speech is decoded based on the Gaussians computed for the first and second streams.

Abstract: A method for speech recognition includes determining active Gaussians related to a first feature stream and a second feature stream by labeling at least one of the first and second streams, and determining active Gaussians co-occurring in the first stream and the second stream based upon joint probability. A number of Gaussians computed is reduced based upon Gaussians already computed for the first stream and a number of Gaussians co-occurring in the second stream. Speech is decoded based on the Gaussians computed for the first and second streams.

Abstract: A system and method for speech recognition includes determining active Gaussians related to a first feature stream and a second feature stream by labeling at least one of the first and second streams, and determining active Gaussians co-occurring in the first stream and the second stream based upon joint probability. A number of Gaussians computed is reduced based upon Gaussians already computed for the first stream and a number of Gaussians co-occurring in the second stream. Speech is decoded based on the Gaussians computed for the first and second streams.

Abstract: The invention provides a method and apparatus for automatically generating a summary or key phrase for a song. The song, or a portion thereof, is digitized and converted into a sequence of feature vectors, such mel-frequency cepstral coefficients (MFCCs). The feature vectors are then processed in order decipher the song's structure. Those sections that correspond to different structural elements are then marked with corresponding labels. Once the song is labeled, various heuristics are applied to select a key phrase corresponding to the song's summary. For example, the system may identify the label that appears most frequently within the song, and then select the longest duration of that label as the summary.