Abstract: Random samples without replacement are extracted from a distributed set of items by leveraging techniques for aggregating sampled subsets of the distributed set. This provides a uniform random sample without replacement representative of the distributed set, allowing statistical information to be gleaned from extremely large sets of distributed information. Subset random samples without replacement are extracted from independent subsets of the distributed set of items. The subset random samples are then aggregated to provide a uniform random sample without replacement of a fixed size that is representative of a distributed set of items of unknown size. In one instance, a multivariate hyper-geometric distribution is sampled by breaking up the multivariate hyper-geometric distribution into a set of univariate hyper-geometric distributions.

Abstract: An apparatus is provided for attaching a surgical component to a bone at a surgical site. The apparatus includes an elongated pin and a cam mounted to the pin. The cam is engaged with the surgical component such that rotating the cam about the shaft axis changes the surgical component position relative to the bone.

Abstract: A publisher union comprises a plurality of publishers, a channel, and a publisher union administrator. The publisher union is administered by receiving a channel proposal, determining whether the channel proposal is acceptable, forming a channel, and presenting the channel for monetization. User information is gathered by the publisher union by establishing a domain, collecting user information, aggregating the user information, and providing the aggregated user information to publisher union members.

Abstract: A system to facilitate trading of advertising comprises a publisher broker representing at least one publisher and to determine an ask for an advertisement space on the publisher's webpage, an advertiser broker representing at least one advertiser and to manage an advertiser's bid for the advertisement space, and an exchange to facilitate a transaction for the advertisement space between the publisher broker and the advertiser broker. A method of facilitating trading of advertising comprises receiving an ask from a publisher broker for advertisement space on a webpage, receiving a bid from an advertiser broker for the advertisement space, and pairing the ask with the bid. A method for enriching user information comprises aggregating user information about a user, storing the aggregate user information according to a user identifier, receiving the user identifier from an exchange, and sending the aggregate user information to the exchange.

Abstract: Determining the near-optimal block size for incremental-type expectation maximization (EM) algorithms is disclosed. Block size is determined based on the novel insight that the speed increase resulting from using an incremental-type EM algorithm as opposed to the standard EM algorithm is roughly the same for a given range of block sizes. Furthermore, this block size can be determined by an initial version of the EM algorithm that does not reach convergence. For a current block size, the speed increase is determined, and if the speed increase is the greatest determined so far, the current block size is set as the target block size. This process is repeated for new block sizes, until no new block sizes can be determined.

Abstract: The subject disclosure pertains to systems and methods that optimize advertisement campaigns. In particular, total utility that can be derived by an advertiser given particular keywords is maximized. The price of each keyword/slot pair can be determined or estimated and bids adjusted automatically to maximize advertiser utility or return on investment for a campaign.

Abstract: The present invention utilizes generic and user-specific features of handwriting samples to provide adaptive handwriting recognition with a minimum level of user-specific enrollment data. By allowing generic and user-specific classifiers to facilitate in a recognition process, the features of a specific user's handwriting can be exploited to quickly ascertain characteristics of handwriting characters not yet entered by the user. Thus, new characters can be recognized without requiring a user to first enter that character as enrollment or “training” data. In one instance of the present invention, processing of generic features is accomplished by a generic classifier trained on multiple users. In another instance of the present invention, a user-specific classifier is employed to modify a generic classifier's classification as required to provide user-specific handwriting recognition.

Abstract: An advertisement display system comprises an analyzer component that analyzes one or more of data associated with at least a portion of a multimedia item, demographic information associated with a user, and contextual data. A presentation component selectively provides at least one advertisement from a plurality of advertisements to a reviewer of the multimedia item based at least in part upon the analysis. The system, for example, can further comprise an ad server, wherein the presentation component receives the at least one advertisement from the ad server based at least in part upon the analysis.

Abstract: The present invention leverages machine learning techniques to provide automatic generation of conditioning variables for constructing a data perspective for a given target variable. The present invention determines and analyzes the best target variable predictors for a given target variable, employing them to facilitate the conveying of information about the target variable to a user. It automatically discretizes continuous and discrete variables utilized as target variable predictors to establish their granularity. In other instances of the present invention, a complexity and/or utility parameter can be specified to facilitate generation of the data perspective via analyzing a best target variable predictor versus the complexity of the conditioning variable(s) and/or utility. The present invention can also adjust the conditioning variables (i.e.

Abstract: The invention performs handwriting recognition using mixtures of Bayesian networks. A mixture of Bayesian networks (MBN) consists of plural hypothesis-specific Bayesian networks (HSBNs) having possibly hidden and observed variables. A common external hidden variable is associated with the MBN, but is not included in any of the HSBNs. Each HSBN models the world under the hypothesis that the common external hidden variable is in a corresponding one of its states. The MBNs encode the probabilities of observing the sets of visual observations corresponding to a handwritten character. Each of the HSBNs encodes the probabilities of observing the sets of visual observations corresponding to a handwritten character and given a hidden common variable being in a particular state.

Abstract: The user interfaces, methods and systems described herein facilitate user interaction with an ad space by conveying additional advertising content via a preview pane and facilitate automatically generating the content of the preview pane. By way of example, an electronic advertisement is conveyed to a user in an ad space provided by a third party, and a secondary advertisement generating component automatically generates at least part of the content of a secondary advertisement. The secondary advertisement provides content associated with the electronic advertisement and occurs upon receiving a user indication. A context acquiring component also may provide context information to the secondary advertisement generating component to automatically generate at least part of the content of the secondary advertisement. By way of another example, a user is provided with one or more ads from a plurality of different advertisers in a first ad space maintained by an ad space supplier.

Abstract: The user interfaces, methods and systems described herein facilitate user interaction with an ad space by conveying additional advertising content via a preview pane and facilitate charging for this functionality. By way of example, a user is provided with one or more ads from a plurality of different advertisers in a first ad space maintained by an ad space supplier. A user input identifying at least one of the ads from the plurality of different advertisers is received and in response a second ad space having a supplemental ad relating to the at least one ad identified by the user input is provided. The advertiser associated with the supplemental ad is charged a fee based on receiving the user input. By way of another example, an electronic advertisement may be conveyed to a user in an ad space provided by a third party. A secondary advertisement providing associated information relating to the electronic advertisement may occur upon receiving a user indication.

Abstract: Random samples without replacement are extracted from a distributed set of items by leveraging techniques for aggregating sampled subsets of the distributed set. This provides a uniform random sample without replacement representative of the distributed set, allowing statistical information to be gleaned from extremely large sets of distributed information. Subset random samples without replacement are extracted from independent subsets of the distributed set of items. The subset random samples are then aggregated to provide a uniform random sample without replacement of a fixed size that is representative of a distributed set of items of unknown size. In one instance, a multivariate hyper-geometric distribution is sampled by breaking up the multivariate hyper-geometric distribution into a set of univariate hyper-geometric distributions.

Abstract: The present invention utilizes generic and user-specific features of handwriting samples to provide adaptive handwriting recognition with a minimum level of user-specific enrollment data. By allowing generic and user-specific classifiers to facilitate in a recognition process, the features of a specific user's handwriting can be exploited to quickly ascertain characteristics of handwriting characters not yet entered by the user. Thus, new characters can be recognized without requiring a user to first enter that character as enrollment or “training” data. In one instance of the present invention, processing of generic features is accomplished by a generic classifier trained on multiple users. In another instance of the present invention, a user-specific classifier is employed to modify a generic classifier's classification as required to provide user-specific handwriting recognition.

Abstract: The present invention leverages approximations of distributions to provide tractable variational approximations, based on at least one continuous variable, for inference utilization in Bayesian networks where local distributions are decision-graphs. These tractable approximations are employed in lieu of exact inferences that are normally NP-hard to solve. By utilizing Jensen's inequality applied to logarithmic distributions composed of a generalized sum including an introduced arbitrary conditional distribution, a means is acquired to resolve a tightly bound likelihood distribution. The means includes application of Mean-Field Theory, approximations of conditional probability distributions, and/or other means that allow for a tractable variational approximation to be achieved.

Abstract: Decision trees populated with classifier models are leveraged to provide enhanced spam detection utilizing separate email classifiers for each feature of an email. This provides a higher probability of spam detection through tailoring of each classifier model to facilitate in more accurately determining spam on a feature-by-feature basis. Classifiers can be constructed based on linear models such as, for example, logistic-regression models and/or support vector machines (SVM) and the like. The classifiers can also be constructed based on decision trees. “Compound features” based on internal and/or external nodes of a decision tree can be utilized to provide linear classifier models as well. Smoothing of the spam detection results can be achieved by utilizing classifier models from other nodes within the decision tree if training data is sparse. This forms a base model for branches of a decision tree that may not have received substantial training data.

Abstract: A computer-implemented system that facilitates establishing price(s) associated with items comprises a clustering component that clusters a collection of non-identical items into one or more sets of non-identical items. A pricing component receives one or more of active bids and stored bids and simulates an auction of at least one non-identical item within one of the one or more sets of non-identical items as if the non-identical items within the set were identical to determine price(s) associated with the at least one non-identical item. For example, the items can be at least portions of search terms received by a search engine.

Abstract: A computer-implemented method is provided for controlling placement of ad impressions, corresponding to ads, displayed on a web page. The method includes recording features corresponding to ad impressions. Recording features can include collecting sufficient statistics for a Naïve Bayes model in some embodiments. A statistical algorithm is then used to automatically control placement of ad impressions.

Abstract: The subject invention provides a unique system and method that facilitates displaying content-targeted advertisements within applications running on an end-user or client computer. To mitigate privacy concerns, one or more advertisements can be stored on a client computer. At least one advertisement can be displayed on the client based at least in part on the context relating to the user's interaction with the client. By doing so, the user's private data or content is not passed to the server—meanwhile content-targeted advertising processing can be run on the user's content to determine which advertisements to display. Different forms of advertisements can be displayed to the user when the client is offline or online to facilitate optimizing use interaction with the advertisements and billing capabilities. To ensure that advertisements are displayed when content is displayed on a client, various encryption and decryption techniques can be employed to mitigate tampering of advertisement display code.

Abstract: A system and method for generating staged mixture model(s) is provided. The staged mixture model includes a plurality of mixture components each having an associated mixture weight, and, an added mixture component having an initial structure, parameters and associated mixture weight. The added mixture component is modified based, at least in part, upon a case that is undesirably addressed by the plurality of mixture components using a structural expectation maximization (SEM) algorithm to modify at the structure, parameters and/or associated mixture weight of the added mixture component. The staged mixture model employs a data-driven staged mixture modeling technique, for example, for building density, regression, and classification model(s). The basic approach is to add mixture component(s) (e.g., sequentially) to the staged mixture model using an SEM algorithm.