Grangier
David Grangier, Princeton, NJ US
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20100179933 | SUPERVISED SEMANTIC INDEXING AND ITS EXTENSIONS - A system and method for determining a similarity between a document and a query includes building a weight vector for each of a plurality of documents in a corpus of documents stored in memory and building a weight vector for a query input into a document retrieval system. A weight matrix is generated which distinguishes between relevant documents and lower ranked documents by comparing document/query tuples using a gradient step approach. A similarity score is determined between weight vectors of the query and documents in a corpus by determining a product of a document weight vector, a query weight vector and the weight matrix. | 07-15-2010 |
20100185659 | SUPERVISED SEMANTIC INDEXING AND ITS EXTENSIONS - A system and method for determining a similarity between a document and a query includes providing a frequently used dictionary and an infrequently used dictionary in storage memory. For each word or gram in the infrequently used dictionary, n words or grams are correlated from the frequently used dictionary based on a first score. Features for a vector of the infrequently used words or grams are replaced with features from a vector of the correlated words or grams from the frequently used dictionary when the features from a vector of the correlated words or grams meet a threshold value. A similarity score is determined between weight vectors of a query and one or more documents in a corpus by employing the features from the vector of the correlated words or grams that met the threshold value. | 07-22-2010 |
David Grangier, San Francisco, CA US
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20110302118 | FEATURE SET EMBEDDING FOR INCOMPLETE DATA - Methods and systems for classifying incomplete data are disclosed. In accordance with one method, pairs of features and values are generated based upon feature measurements on the incomplete data. In addition, a transformation function is applied on the pairs of features and values to generate a set of vectors by mapping each of the pairs to a corresponding vector in an embedding space. Further, a hardware processor applies a prediction function to the set of vectors to generate at least one confidence assessment for at least one class that indicates whether the incomplete data is of the at least one class. The method further includes outputting the at least one confidence assessment. | 12-08-2011 |
David G. Grangier, Kirkland, WA US
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20150019204 | FEATURE COMPLETION IN COMPUTER-HUMAN INTERACTIVE LEARNING - A collection of data that is extremely large can be difficult to search and/or analyze. Relevance may be dramatically improved by automatically classifying queries and web pages in useful categories, and using these classification scores as relevance features. A thorough approach may require building a large number of classifiers, corresponding to the various types of information, activities, and products. Creation of classifiers and schematizers is provided on large data sets. Exercising the classifiers and schematizers on hundreds of millions of items may expose value that is inherent to the data by adding usable meta-data. Some aspects include active labeling exploration, automatic regularization and cold start, scaling with the number of items and the number of classifiers, active featuring, and segmentation and schematization. | 01-15-2015 |
20150019211 | INTERACTIVE CONCEPT EDITING IN COMPUTER-HUMAN INTERACTIVE LEARNING - A collection of data that is extremely large can be difficult to search and/or analyze. Relevance may be dramatically improved by automatically classifying queries and web pages in useful categories, and using these classification scores as relevance features. A thorough approach may require building a large number of classifiers, corresponding to the various types of information, activities, and products. Creation of classifiers and schematizers is provided on large data sets. Exercising the classifiers and schematizers on hundreds of millions of items may expose value that is inherent to the data by adding usable meta-data. Some aspects include active labeling exploration, automatic regularization and cold start, scaling with the number of items and the number of classifiers, active featuring, and segmentation and schematization. | 01-15-2015 |
20150019461 | INTERACTIVE SEGMENT EXTRACTION IN COMPUTER-HUMAN INTERACTIVE LEARNING - A collection of data that is extremely large can be difficult to search and/or analyze. Relevance may be dramatically improved by automatically classifying queries and web pages in useful categories, and using these classification scores as relevance features. A thorough approach may require building a large number of classifiers, corresponding to the various types of information, activities, and products. Creation of classifiers and schematizers is provided on large data sets. Exercising the classifiers and schematizers on hundreds of millions of items may expose value that is inherent to the data by adding usable meta-data. Some aspects include active labeling exploration, automatic regularization and cold start, scaling with the number of items and the number of classifiers, active featuring, and segmentation and schematization. | 01-15-2015 |
20150019463 | ACTIVE FEATURING IN COMPUTER-HUMAN INTERACTIVE LEARNING - A collection of data that is extremely large can be difficult to search and/or analyze. Relevance may be dramatically improved by automatically classifying queries and web pages in useful categories, and using these classification scores as relevance features. A thorough approach may require building a large number of classifiers, corresponding to the various types of information, activities, and products. Creation of classifiers and schematizers is provided on large data sets. Exercising the classifiers and schematizers on hundreds of millions of items may expose value that is inherent to the data by adding usable meta-data. Some aspects include active labeling exploration, automatic regularization and cold start, scaling with the number of items and the number of classifiers, active featuring, and segmentation and schematization. | 01-15-2015 |
Julien Grangier, Rumilly FR
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20090214146 | SYSTEM FOR MEASURING DEFORMATIONS BY RESILIENT COMPRESSION OF A GAUGE - A system for measuring deformations of an area of a structural element, includes at least one gauge including a rigid substrate on the upper surface of which is arranged at least one pattern of a material capable of being deformed and delivering a signal representative of the deformations the substrate is arranged to transmit, to the pattern, the deformations of the area when the lower surface of the substrate is attached to the area. The system includes a deformable element and a device for compression of the element on the upper surface of the substrate so that the substrate can be moved by the deformations of the area. The system also includes an arrangement for attachment of the compression device on the structural element, in which the attachment arrangement is intended to ensure that the substrate is held on the area by the deformable element, which is compressed on the upper surface of the substrate. | 08-27-2009 |
Philippe Grangier, Saint Remy Les Chevreuse FR
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20090268901 | CONTINUOUS VARIABLE QUANTUM ENCRYPTION KEY DISTRIBUTION SYSTEM - A continuous variable quantum encryption key distribution system comprises a sender (Alice) able to randomly choose the phase and the amplitude of each coherent light pulse of a signal, to provide a coherent state defined by a first quadrature and a second quadrature that are random, and to transmit to a receiver (Bob) the signal pulses (S) and a local oscillator (LO), the receiver comprising a homodyne detector ( | 10-29-2009 |