Patents by Inventor Ralf Herbrich

Ralf Herbrich 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).

  • Publication number: 20140059163
    Abstract: Processing a request is disclosed. A request associated with a first identifier is received. A selected request handler is selected among a first plurality of request handlers to process the request. The selection of the selected request handler is based at least in part on the first identifier. The request is processed using a second identifier included in the request. Processing the request includes using a local version of a data associated with the second identifier and stored in a storage managed by the selected request handler. The local version of the data has been updated using a centralized version of the data. The centralized version of the data has been determined using processing performed by a second plurality of request handlers. The selected request handler is included in the second plurality of request handlers.
    Type: Application
    Filed: August 24, 2012
    Publication date: February 27, 2014
    Inventors: Ralf Herbrich, Iouri Y. Poutivski, Antoine Joseph Atallah
  • Publication number: 20140059162
    Abstract: Processing a prepared update is disclosed. A prepared update associated with a request that has been used by the sender to update a local version of a data associated with the sender is received from a sender. Based at least in part on an identifier included in the prepared update, a selected data handler is selected among a plurality of data handlers. The selected data handler is used to update a centralized version of the data at least in part by using the received prepared update. The centralized version of the data has been previously updated using a plurality of prepared updates received from a plurality of senders. The updated centralized version of the data is sent to update the local version of the data associated with the sender.
    Type: Application
    Filed: August 24, 2012
    Publication date: February 27, 2014
    Inventors: Ralf Herbrich, Iouri Y. Putivsky, Antoine Joseph Atallah
  • Patent number: 8645298
    Abstract: Machine learning techniques may be used to train computing devices to understand a variety of documents (e.g., text files, web pages, articles, spreadsheets, etc.). Machine learning techniques may be used to address the issue that computing devices may lack the human intellect used to understand such documents, such as their semantic meaning. Accordingly, a topic model may be trained by sequentially processing documents and/or their features (e.g., document author, geographical location of author, creation date, social network information of author, and/or document metadata). Additionally, as provided herein, the topic model may be used to predict probabilities that words, features, documents, and/or document corpora, for example, are indicative of particular topics.
    Type: Grant
    Filed: October 26, 2010
    Date of Patent: February 4, 2014
    Assignee: Microsoft Corporation
    Inventors: Philipp Hennig, David Stern, Thore Graepel, Ralf Herbrich
  • Patent number: 8589317
    Abstract: Many computing scenarios involve the classification of content items within one or more categories. The content item set may be too large for humans to classify, but an automated classifier (e.g., an artificial neural network) may not be able to classify all content items with acceptable accuracy. Instead, the automated classifier may calculate a classification confidence while classifying respective content items. Content items having a low classification confidence may be sent to a human classifier, and may be added, along with the categories identified by the human classifier, to a training set. The automated classifier may then be retrained using the training set, thereby incrementally improving the classification confidence of the automated classifier while conserving the involvement of human classifiers. Additionally, human classifiers may be rewarded for classifying the content items, and the costs of such rewards may be considered while selecting content items for the training set.
    Type: Grant
    Filed: December 16, 2010
    Date of Patent: November 19, 2013
    Assignee: Microsoft Corporation
    Inventors: Ulrich Paquet, David Stern, Jurgen Anne Francois Marie Van Gael, Ralf Herbrich
  • Patent number: 8583266
    Abstract: Skill scores represent a ranking or other indication of the skill of the player based on the outcome of the game in a gaming environment. Skills scores can be used in matching compatible players on the same team and matching opposing players or teams to obtain an evenly-matched competition. An initial skill score of a player in a new gaming environment may be based in whole or in part on the skill score of that player in another game environment. The influence that the skill scores for these other game environments may have in the skill score seeding for the new game environment may be weighted based on a defined compatibility factor with the new game environment. The compatibility factor can be determined based on a game-to-game basis, compatible categories or features, game developer defined parameters, or any combination of considerations.
    Type: Grant
    Filed: March 5, 2012
    Date of Patent: November 12, 2013
    Assignee: Microsoft Corporation
    Inventors: Ralf Herbrich, Thore K. H. Graepel
  • Publication number: 20130282631
    Abstract: One or more techniques and/or systems are disclosed for predicting propagation of a message on a social network. A predictive model is trained to determine a probability of propagation of information on the social network using both positive and negative information propagation feedback, which may be collected while monitoring the social network over a desired period of time for information propagation. A particular message can be input to the predictive model, which can determine a probability of propagation of the message on the social network, such as how many connections may receive at least a portion of the message and/or a likelihood of at least a portion of the message reaching respective connections in the social network.
    Type: Application
    Filed: June 17, 2013
    Publication date: October 24, 2013
    Inventors: Tauhid Rashed Zaman, Jurgen Anne Francois Marie Van Gael, David Stern, Ralf Herbrich, Gilad Lotan
  • Patent number: 8560528
    Abstract: Data structures for collaborative filtering systems are described. In an embodiment sketches which extremely concisely represent a list of items that a user has rated are created and stored for use by a collaborative filtering system to recommend items. For example, the sketches are created by using several versions of a cryptographic hash function to permute the item list and store a minimal value from each permutation in the sketch together with a user rating. In examples the sketches are used to compute estimates of similarity measures between pairs of users such as rank correlations including Spearman's Rho and Kendall's Tau. For example, the similarity measures are used by a collaborative filtering system to accurately and efficiently recommend items to users. For example the sketches are so concise that massive amounts of data can be taken into account in order to give high quality recommendations in a practical manner.
    Type: Grant
    Filed: March 17, 2010
    Date of Patent: October 15, 2013
    Assignee: Microsoft Corporation
    Inventors: Ralf Herbrich, Yoram Bachrach
  • Patent number: 8538910
    Abstract: There is a desire to provide a way to determine relative skills of players of games such as computer games, chess, tennis and any other suitable type of game. Our earlier Bayesian Scoring system is implemented in Xbox Live (trade mark) and is currently commercially available under the trade name TrueSkill (trade mark). Here we build on our earlier work and use a new method of computation to enable processing times to be significantly reduced. Message passing techniques are adapted to enable computation of updated skill beliefs to be obtained quickly even in the case of multiple teams of multiple players.
    Type: Grant
    Filed: January 16, 2007
    Date of Patent: September 17, 2013
    Assignee: Microsoft Corporation
    Inventors: Thomas Minka, Thore K H Graepel, Ralf Herbrich
  • Patent number: 8473437
    Abstract: One or more techniques and/or systems are disclosed for predicting propagation of a message on a social network. A predictive model is trained to determine a probability of propagation of information on the social network using both positive and negative information propagation feedback, which may be collected while monitoring the social network over a desired period of time for information propagation. A particular message can be input to the predictive model, which can determine a probability of propagation of the message on the social network, such as how many connections may receive at least a portion of the message and/or a likelihood of at least a portion of the message reaching respective connections in the social network.
    Type: Grant
    Filed: December 17, 2010
    Date of Patent: June 25, 2013
    Assignee: Microsoft Corporation
    Inventors: Tauhid Rashed Zaman, Jurgen Anne Francois Marie Van Gael, David Stern, Ralf Herbrich, Gilad Lotan
  • Patent number: 8433660
    Abstract: Managing a portfolio of experts is described where the experts may be for example, automated experts or human experts. In an embodiment a selection engine selects an expert from a portfolio of experts and assigns the expert to a specified task. For example, the selection engine has a Bayesian machine learning system which is iteratively updated each time an experts performance on a task is observed. For example, sparsely active binary task and expert feature vectors are input to the selection engine which maps those feature vectors to a multi-dimensional trait space using a mapping learnt by the machine learning system. In examples, an inner product of the mapped vectors gives an estimate of a probability distribution over expert performance. In an embodiment the experts are automated problem solvers and the task is a hard combinatorial problem such as a constraint satisfaction problem or combinatorial auction.
    Type: Grant
    Filed: December 1, 2009
    Date of Patent: April 30, 2013
    Assignee: Microsoft Corporation
    Inventors: David Stern, Horst Cornelius Samulowitz, Ralf Herbrich, Thore Graepel
  • Patent number: 8417650
    Abstract: Event prediction in dynamic environments is described. In an embodiment a prediction engine may use the learnt information to predict events in order to control a system such as for internet advertising, email filtering, fraud detection or other applications. In an example one or more variables exists for pre-specified features describing or associated with events and each variable is considered to have an associated weight and time stamp. For example, belief about each weight is represented using a probability distribution and a dynamics process is used to modify the probability distribution in a manner dependent on the time stamp for that weight. For example, the uncertainty about the associated variable's influence on prediction of future events is increased. Examples of different schedules for applying the dynamics process are given.
    Type: Grant
    Filed: January 27, 2010
    Date of Patent: April 9, 2013
    Assignee: Microsoft Corporation
    Inventors: Thore Graepel, Joaquin Quinonero Candela, Thomas Ivan Borchert, Ralf Herbrich
  • Patent number: 8393944
    Abstract: An automatic algorithm for finding racing lines via computerized minimization of a measure of the curvature of a racing line is derived. Maximum sustainable speed of a car on a track is shown to be inversely proportional to the curvature of the line it is attempting to follow. Low curvature allows for higher speed given that a car has some maximum lateral traction when cornering. The racing line can also be constrained, or “pinned,” at arbitrary points on the track. Pinning may be performed randomly, deterministically, or manually and allows, for example, a line designer to pin the line at any chosen points on the track, such that when the automatic algorithm is run, it will produce the smoothest line that still passes through all the specified pins.
    Type: Grant
    Filed: January 13, 2011
    Date of Patent: March 12, 2013
    Assignee: Microsoft Corporation
    Inventors: Michael E. Tipping, Mark Andrew Hatton, Ralf Herbrich
  • Patent number: 8374973
    Abstract: Reputation systems have been used to promote trust between participants in activities including online activities such as online market places. Existing online market places provide a reputation system which is a simple cumulative registry of user ratings on a given market place member. However, this simple system is open to abuse in situations where, for example, many positive ratings are given in a fraudulent manner. By modeling both reputation of participants and required reputation of participants an improved reputation system is provided. The required reputation may be thought of as a threshold, referred to herein as a required threshold, which may be used in determining how to update an indication of the reputation of a participant in the activity. The reputation system is able to learn information about required reputation and reputation of participants using an update process which is robust to participants who consistently give feedback of a particular type.
    Type: Grant
    Filed: March 29, 2007
    Date of Patent: February 12, 2013
    Assignee: Microsoft Corporation
    Inventors: Ralf Herbrich, Thore Graepel, David Shaw
  • Patent number: 8364612
    Abstract: Machine learning using relational databases is described. In an embodiment a model of a probabilistic relational database is formed by augmenting relation schemas of a relational database with probabilistic attributes. In an example, the model comprises constraints introduced by linking the probabilistic attributes using factor statements. For example, a compiler translates the model into a factor graph data structure which may be passed to an inference engine to carry out machine learning. For example, this enables machine learning to be integrated with the data and it is not necessary to pre-process or reformat large scale data sets for a particular problem domain. In an embodiment a machine learning system for estimating skills of players in an online gaming environment is provided. In another example, a machine learning system for data mining of medical data is provided. In some examples, missing attribute values are filled using machine learning results.
    Type: Grant
    Filed: September 15, 2009
    Date of Patent: January 29, 2013
    Assignee: Microsoft Corporation
    Inventors: Jurgen Anne Francios Marie Van Gael, Ralf Herbrich, Thore Graepel
  • Publication number: 20130024448
    Abstract: Document features or document ranking values can be associated with a distribution of values. Feature values, feature value coefficients, and/or document ranking values can be generated based on sampled values from the distribution of values. This can allow the relative ranking of a document to vary.
    Type: Application
    Filed: July 21, 2011
    Publication date: January 24, 2013
    Applicant: MICROSOFT CORPORATION
    Inventors: RALF HERBRICH, WILLIAM RAMSEY, ANTOINE ATALLAH, THORE GRAEPEL, PAUL VIOLA
  • Publication number: 20120221129
    Abstract: Skill scores represent a ranking or other indication of the skill of the player based on the outcome of the game in a gaming environment. Skills scores can be used in matching compatible players on the same team and matching opposing players or teams to obtain an evenly-matched competition. An initial skill score of a player in a new gaming environment may be based in whole or in part on the skill score of that player in another game environment. The influence that the skill scores for these other game environments may have in the skill score seeding for the new game environment may be weighted based on a defined compatibility factor with the new game environment. The compatibility factor can be determined based on a game-to-game basis, compatible categories or features, game developer defined parameters, or any combination of considerations.
    Type: Application
    Filed: March 5, 2012
    Publication date: August 30, 2012
    Applicant: MICROSOFT CORPORATION
    Inventors: Ralf Herbrich, Thore K.H. Graepel
  • Publication number: 20120158630
    Abstract: One or more techniques and/or systems are disclosed for predicting propagation of a message on a social network. A predictive model is trained to determine a probability of propagation of information on the social network using both positive and negative information propagation feedback, which may be collected while monitoring the social network over a desired period of time for information propagation. A particular message can be input to the predictive model, which can determine a probability of propagation of the message on the social network, such as how many connections may receive at least a portion of the message and/or a likelihood of at least a portion of the message reaching respective connections in the social network.
    Type: Application
    Filed: December 17, 2010
    Publication date: June 21, 2012
    Applicant: Microsoft Corporation
    Inventors: Tauhid Rashed Zaman, Jurgen Anne Francois Marie Van Gael, David Stern, Ralf Herbrich, Gilad Lotan
  • Publication number: 20120158620
    Abstract: Many computing scenarios involve the classification of content items within one or more categories. The content item set may be too large for humans to classify, but an automated classifier (e.g., an artificial neural network) may not be able to classify all content items with acceptable accuracy. Instead, the automated classifier may calculate a classification confidence while classifying respective content items. Content items having a low classification confidence may be sent to a human classifier, and may be added, along with the categories identified by the human classifier, to a training set. The automated classifier may then be retrained using the training set, thereby incrementally improving the classification confidence of the automated classifier while conserving the involvement of human classifiers. Additionally, human classifiers may be rewarded for classifying the content items, and the costs of such rewards may be considered while selecting content items for the training set.
    Type: Application
    Filed: December 16, 2010
    Publication date: June 21, 2012
    Applicant: Microsoft Corporation
    Inventors: Ulrich Paquet, David Stern, Jurgen Anne Francois Mari Van Gael, Ralf Herbrich
  • Publication number: 20120158791
    Abstract: Feature vector construction techniques are described. In one or more implementations, an input is received at a computing device that describes a graph query that specifies one of a plurality of entities to be used to query a knowledge base graph that represents the plurality of entities. A feature vector is constructed, by the computing device, having a number of indicator variables, each of which indicates observance of a sub-graph feature represented by a respective indicator variable in the knowledge base graph.
    Type: Application
    Filed: December 21, 2010
    Publication date: June 21, 2012
    Applicant: MICROSOFT CORPORATION
    Inventors: Gjergji Kasneci, David Hector Stern, Thore Kurt Hartwig Graepel, Ralf Herbrich
  • Patent number: 8204838
    Abstract: A scalable clustering system is described. In an embodiment the clustering system is operable for extremely large scale applications where millions of items having tens of millions of features are clustered. In an embodiment the clustering system uses a probabilistic cluster model which models uncertainty in the data set where the data set may be for example, advertisements which are subscribed to keywords, text documents containing text keywords, images having associated features or other items. In an embodiment the clustering system is used to generate additional features for associating with a given item. For example, additional keywords are suggested which an advertiser may like to subscribe to. The additional features that are generated have associated probability values which may be used to rank those features in some embodiments. User feedback about the generated features is received and used to revise the feature generation process in some examples.
    Type: Grant
    Filed: April 10, 2009
    Date of Patent: June 19, 2012
    Assignee: Microsoft Corporation
    Inventors: Anton Schwaighofer, Joaquin Quiñonero Candela, Thomas Borchert, Thore Graepel, Ralf Herbrich