Microsoft Technology Licensing, LLC

David G Grangier

Patrice Y Simard

Saleema Amin Amershi

David Max Chickering

Denis X Charles

Carlos Garcia Jurado Suarez

Aparna Lakshmiratan

Leon Bottou

Steven Mark Drucker

David Maxwell Chickering

Bongshin Lee

Patrice Yvon Rene Simard

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.

Interactive feature selection for training a machine learning system and displaying discrepancies within the context of the document

Interactive concept editing in computer-human interactive learning

Methods, computer systems, computer-storage media, and graphical user interfaces are provided for visualizing a performance of a machine-learned model. An interactive graphical user interface includes an item representation display area that displays a plurality of item representations corresponding to a plurality of items processed by the machine-learned model. The plurality of item representations are arranged according to scores assigned to the plurality of items by the machine-learned model. Further, each of the plurality of item representations is visually configured to represent a label assigned to a corresponding item.

Interactive visualization of machine-learning performance

Feature completion in computer-human interactive learning

Interactive segment extraction in computer-human interactive learning

Active featuring in computer-human interactive learning

Growing community of inventors

Kirkland, WA, United States of America

David G Grangier