Patents by Inventor Max Chickering

Max Chickering has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11023677
    Abstract: 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.
    Type: Grant
    Filed: July 13, 2016
    Date of Patent: June 1, 2021
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Patrice Y. Simard, David Max Chickering, David G. Grangier, Aparna Lakshmiratan, Saleema A. Amershi
  • Patent number: 9779081
    Abstract: 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.
    Type: Grant
    Filed: April 21, 2016
    Date of Patent: October 3, 2017
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Patrice Y. Simard, David Max Chickering, David G. Grangier, Denis X. Charles, Leon Bottou, Carlos Garcia Jurado Suarez
  • Patent number: 9582490
    Abstract: 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.
    Type: Grant
    Filed: November 8, 2013
    Date of Patent: February 28, 2017
    Assignee: Microsoft Technolog Licensing, LLC
    Inventors: Patrice Y. Simard, David Max Chickering, Aparna Lakshmiratan, Denis X. Charles, Leon Bottou
  • Patent number: 9569541
    Abstract: Systems, methods, and computer storage media having computer-executable instructions embodied thereon that facilitate evaluation of digital content preferences are provided. A user is presented with items of digital content and permitted to manipulate the arrangement of the digital content items in the context of a layout area. Based on the user's manipulation of the digital content items, a user preference regarding an arrangement of digital content, such as a location preference, a position preference, and/or a usage preference, is identified. In embodiments, such a user preference can be utilized to later display digital content to a user in accordance therewith.
    Type: Grant
    Filed: December 31, 2009
    Date of Patent: February 14, 2017
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Reid Andersen, David Max Chickering, Ewa Dominowska, Matt Jacobsen, Anton Mityagin
  • Patent number: 9489373
    Abstract: 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.
    Type: Grant
    Filed: November 8, 2013
    Date of Patent: November 8, 2016
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Patrice Y. Simard, David Max Chickering, David G. Grangier, Denis X. Charles, Leon Bottou, Saleema A. Amershi, Aparna Lakshmiratan, Carlos Garcia Jurado Suarez
  • Patent number: 9430460
    Abstract: 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.
    Type: Grant
    Filed: November 8, 2013
    Date of Patent: August 30, 2016
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Patrice Y. Simard, David Max Chickering, David G. Grangier, Aparna Lakshmiratan, Saleema A. Amershi
  • Patent number: 9355088
    Abstract: 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.
    Type: Grant
    Filed: November 8, 2013
    Date of Patent: May 31, 2016
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Patrice Y. Simard, David Max Chickering, David G. Grangier, Denis X. Charles, Leon Bottou, Carlos Garcia Jurado Suarez
  • Patent number: 9104960
    Abstract: Methods, systems, and computer-storage media having computer-usable instructions embodied thereon for calculating event probabilities are provided. The event may be a click probability. Event probabilities are calculated using a system optimized for runtime model accuracy with an operable learning algorithm. Bin counting techniques are used to calculate event probabilities based on a count of event occurrences and non-event occurrences. Linear parameters, such and counts of clicks and non-clicks, may also be used in the system to allow for runtime adjustments.
    Type: Grant
    Filed: June 20, 2011
    Date of Patent: August 11, 2015
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Leon Bottou, Kumar Chellapilla, Patrice Y. Simard, David Max Chickering
  • Patent number: 8862468
    Abstract: A system and method of refining context-free grammars (CFGs). The method includes deriving back-off grammar (BOG) rules from an initially developed CFG and utilizing the initial CFG and the derived BOG rules to recognize user utterances. Based on a response of the initial CFG and the derived BOG rules to the user utterances, at least a portion of the derived BOG rules are utilized to modify the initial CFG and thereby produce a refined CFG. The above method can carried out iterativey, with each new iteration utilizing a refined CFG from preceding iterations.
    Type: Grant
    Filed: December 22, 2011
    Date of Patent: October 14, 2014
    Assignee: Microsoft Corporation
    Inventors: Timothy Paek, Max Chickering, Eric Badger
  • Patent number: 8589233
    Abstract: For a multi-party online advertising exchange including advertising and publishing entities and one or more third party participants, the disclosed systems and methods enable third party participation in arbitrage opportunities in online advertising transactions. A plurality of underlying transaction details are abstracted and provided to the third party participants without loss of generalization and while preserving relationships in the transaction data, to enable a third party share risk in advertising transactions. Various system refinements are provided and disclosed according to a host of optional embodiments.
    Type: Grant
    Filed: June 15, 2007
    Date of Patent: November 19, 2013
    Assignee: Microsoft Corporation
    Inventors: Gary W. Flake, Brett D. Brewer, Christopher A. Meek, David Max Chickering, Jody D. Biggs, Ewa Dominowska, Brian Burdick
  • Patent number: 8533049
    Abstract: For a multi-party advertising exchange, including publishing entities and advertising entities from disparate advertising networks, which facilitates transactions for publishing inventory, a value add broker is provided to aggregate information from third parties having valuable information for input to the exchange or to perform services that are valuable to transactions in the exchange. The valuable information or services further facilitate the transactions for the publishing inventory automatically generating a benefit for the third parties providing the valuable information or services commensurate with the value added to the transactions.
    Type: Grant
    Filed: June 13, 2007
    Date of Patent: September 10, 2013
    Assignee: Microsoft Corporation
    Inventors: Gary W. Flake, Brett D. Brewer, Christopher A. Meek, David Max Chickering, Jody D. Biggs, Ewa Dominowska, Brian Burdick
  • Publication number: 20120150772
    Abstract: A social newsfeed being delivered to a user is triaged. A personalized model is established which predicts the importance to the user of data elements within a current social newsfeed being delivered to the user. The personalized model is established based on implicit actions the user takes in response to receiving previous social newsfeeds. The personalized model is then used to triage the data elements within the current social newsfeed.
    Type: Application
    Filed: December 10, 2010
    Publication date: June 14, 2012
    Applicant: MICROSOFT CORPORATION
    Inventors: Tim Paek, Scott Joseph Counts, Michael Gamon, Aaron Hoff, Max Chickering
  • Publication number: 20120095752
    Abstract: A system and method of refining context-free grammars (CFGs). The method includes deriving back-off grammar (BOG) rules from an initially developed CFG and utilizing the initial CFG and the derived BOG rules to recognize user utterances. Based on a response of the initial CFG and the derived BOG rules to the user utterances, at least a portion of the derived BOG rules are utilized to modify the initial CFG and thereby produce a refined CFG. The above method can carried out iterativey, with each new iteration utilizing a refined CFG from preceding iterations.
    Type: Application
    Filed: December 22, 2011
    Publication date: April 19, 2012
    Applicant: Microsoft Corporation
    Inventors: Timothy Paek, Max Chickering, Eric Badger
  • Patent number: 8155990
    Abstract: Computer-readable media for determining whether to accept a candidate order from a content provider, or advertiser, to display a particular number of advertisements within a specified time segment are provided. Initially, the content provider may include placement criteria that, among other things, identify a leaf node at which impressions of the advertisement are expected to be rendered. Generally, the leaf node refers to a location within a topic graph that describes inventory that is permissible to allocate to satisfy the candidate order. To perform the determination, the inventory of impressions available for accommodating the candidate order and a log of booked orders scheduled to be placed within the time segment are identified. Linear programs are then utilized to determine whether the estimated inventory that satisfies the placement criteria is available by predictively placing the booked orders at the estimated inventory. If estimated inventory remains available, the candidate order is accepted.
    Type: Grant
    Filed: January 26, 2009
    Date of Patent: April 10, 2012
    Assignee: Microsoft Corporation
    Inventors: David Max Chickering, Manan Sanghi, Ashis Roy, Robert Paul Gorman, Izzet Can Envarli
  • Patent number: 8108205
    Abstract: A system and method of refining context-free grammars (CFGs). The method includes deriving back-off grammar (BOG) rules from an initially developed CFG and utilizing the initial CFG and the derived BOG rules to recognize user utterances. Based on a response of the initial CFG and the derived BOG rules to the user utterances, at least a portion of the derived BOG rules are utilized to modify the initial CFG and thereby produce a refined CFG. The above method can carried out iterativey, with each new iteration utilizing a refined CFG from preceding iterations.
    Type: Grant
    Filed: December 1, 2006
    Date of Patent: January 31, 2012
    Assignee: Microsoft Corporation
    Inventors: Timothy Paek, Max Chickering, Eric Badger
  • Patent number: 8005770
    Abstract: A method for generating a Bayesian network in a parallel manner is based on an initial model having a plurality of nodes. Each node corresponds to a variable of a data set and has a local distribution associated therewith. The method includes assigning a plurality of subsets of the nodes to a respective plurality of constructors. The plurality of constructors is operated in a parallel manner to identify edges to add between nodes in the initial model. The identified edges are added to the initial model to generate the Bayesian network. The edges indicate dependency between nodes connected by the edges.
    Type: Grant
    Filed: June 9, 2008
    Date of Patent: August 23, 2011
    Assignee: Microsoft Corporation
    Inventors: Chi Cao Minh, Max Chickering, John Feo, Jaime Hwacinski, Anitha Panapakkam, Khaled Sedky
  • Patent number: 7777125
    Abstract: A “Music Mapper” automatically constructs a set coordinate vectors for use in inferring similarity between various pieces of music. In particular, given a music similarity graph expressed as links between various artists, albums, songs, etc., the Music Mapper applies a recursive embedding process to embed each of the graphs music entries into a multi-dimensional space. This recursive embedding process also embeds new music items added to the music similarity graph without reembedding existing entries so long a convergent embedding solution is achieved. Given this embedding, coordinate vectors are then computed for each of the embedded musical items. The similarity between any two musical items is then determined as either a function of the distance between the two corresponding vectors. In various embodiments, this similarity is then used in constructing music playlists given one or more random or user selected seed songs or in a statistical music clustering process.
    Type: Grant
    Filed: November 19, 2004
    Date of Patent: August 17, 2010
    Assignee: Microsoft Corporation
    Inventors: John Platt, Erin Renshaw, Max Chickering, Cormac Herley
  • Patent number: 7698166
    Abstract: For a multi-party advertising exchange including advertising and publishing entities, each participant specifies tax rate(s), such as import tax and export tax, that apply to at least one other entity in the exchange. Since tax rate(s) can be expressed in different transactional terms by different parties, each tax rate is reduced to a common tax rate expression within the exchange for comparison. Intelligent tax rate selection and support can be provided to dynamically set tax rates that achieve utilitarian goals for the individual participants taking into account the tax rates expressed by other participants and their respective advertising goals, and dynamically adjusting tax rates over time in response to condition changes. Various refinements are provided and disclosed according to a host of optional implementations.
    Type: Grant
    Filed: May 14, 2007
    Date of Patent: April 13, 2010
    Assignee: Microsoft Corporation
    Inventors: Gary W. Flake, Brett D. Brewer, Christopher A. Meek, David Max Chickering, Jody D. Biggs, Ewa Dominowska, Brian Burdick, Hrishikesh Bal
  • Publication number: 20090327083
    Abstract: A method and system for generating a price landscape for an advertiser for bids placed by the advertiser for advertisement space is provided. A price landscape system generates a price landscape based on information provided by an advertisement placement service that may include overall price estimation data and advertiser-specific performance data. The price landscape system generates price landscape data for an advertiser that combines the overall price estimation data and the advertiser-specific performance data to provide a more accurate assessment of the advertiser's expected performance than can be determined from the overall price estimation data or the advertiser-specific performance data alone.
    Type: Application
    Filed: June 27, 2008
    Publication date: December 31, 2009
    Applicant: Microsoft Corporation
    Inventors: Ashvin J. Mathew, Max Chickering, Jesper B. Lind, Vadims Cugunovs, Dipanjan Ghosh, Xiaoqiao Li, Nathan W. Brixius
  • Publication number: 20090307160
    Abstract: A method for generating a Bayesian network in a parallel manner is based on an initial model having a plurality of nodes. Each node corresponds to a variable of a data set and has a local distribution associated therewith. The method includes assigning a plurality of subsets of the nodes to a respective plurality of constructors. The plurality of constructors is operated in a parallel manner to identify edges to add between nodes in the initial model. The identified edges are added to the initial model to generate the Bayesian network. The edges indicate dependency between nodes connected by the edges.
    Type: Application
    Filed: June 9, 2008
    Publication date: December 10, 2009
    Applicant: MICROSOFT CORPORATION
    Inventors: Chi Cao Minh, Max Chickering, John Feo, Jaime Hwacinski, Anitha Panapakkam, Khaled Sedky