Showing papers by "Irina Rish published in 2008"

Closed-form supervised dimensionality reduction with generalized linear models

Abstract: We propose a family of supervised dimensionality reduction (SDR) algorithms that combine feature extraction (dimensionality reduction) with learning a predictive model in a unified optimization framework, using data- and class-appropriate generalized linear models (GLMs), and handling both classification and regression problems. Our approach uses simple closed-form update rules and is provably convergent. Promising empirical results are demonstrated on a variety of high-dimensional datasets.

Automated dynamic vehicle blind spot determination

Abstract: A driver's orientation within a vehicle is monitored. A change in the driver's orientation is detected. A change to a blind spot of the vehicle is calculated based upon the detected change in the driver's orientation. This abstract is not to be considered limiting, since other embodiments may deviate from the features described in this abstract.

Photograph authorization system

Abstract: An electronic photographic device that automatically communicates an authorization signal that enables receivers of the authorization signal to authorize use of a likeness captured in a photographic image. The electronic authorization device includes an image capture mechanism for capturing the photographic image, a controller for initiating photographic authorization by generating an authorization signal at the capture of the photographic image by the image capture mechanism and a transmitter for transmitting the authorization signal generated by the controller towards a physical location at which the photographic image is captured. The authorization signal identifies a website URL at which information relating to the captured photographic image can be accessed to allow a person who has received the authorization signal to access the website and provide or deny an authorization for its use.

Active Collaborative Prediction with Maximum Margin Matrix Factorization.

Abstract: Collaborative prediction (CP) is a problem of predicting unobserved entries in sparsely observed matrices, e.g. product ratings by different users in online recommender systems. However, the quality of prediction may be quite sensitive to the choice of available samples, which motivates active sampling approaches. In this paper, we suggest an active sampling method based on the recently proposed Maximum-Margin Matrix Factorization (MMMF) [7], a linear factor model that was shown to outperform state-of-art collaborative prediction techniques. MMMF is formulated as a semidefinite program (SDP) that finds a low-norm (rather than traditional low-rank) matrix factorization, and is also closely related to learning max-margin linear discriminants (SVMs). This relation to SVMs inspires several margin-based active sampling heuristics that augment MMMF and demonstrate promising results in a variety of practical domains, including both traditional recommender systems and novel systems-management applications such as predicting latency and bandwidth in computer networks.

Apparatus and Methods for Determining Availability and Performance of Entities Providing Services in a Distributed System Using Filtered Service Consumer Feedback

Abstract: The invention concerns apparatus and methods that determine availability and performance of entities providing services in a distributed system using filtered service-consumer feedback In particular, apparatus and methods of the invention filter service-consumer feedback in order to reduce the effect of circumstances unique to individual service consumers or to groups of service consumers that do not accurately reflect the actual availability or performance of service-providing entities In this way an accurate appraisal is gained regarding the performance and availability of a service-providing entity Reactive methods of the invention can be combined with proactive methods such as, for example, active status probing, to further improve the accuracy of data concerning the status and availability of service-providing entities

Systems, methods and computer program products for supervised dimensionality reduction with mixed-type features and labels

Abstract: Systems, methods and computer program products for supervised dimensionality reduction. Exemplary embodiments include a method including receiving an input in the form of a data matrix X of size N×D, wherein N is a number of samples, D is a dimensionality, a vector Y of size N×1, hidden variables U of a number K, a data type of the matrix X and the vector Y, and a trade-off constant alpha; selecting loss functions in the form of Lx(X,UV) and Ly(Y,UW) appropriate for the type of data in the matrix X and the vector Y, where U, V and W are matrices, selecting corresponding sets of update rules RU, RV and RW for updating the matrices U,V and W, learning U, V and W that provide a minimum total loss L(U,V,W)=Lx(X,UV)+alpha*Ly(Y,UW), and returning matrices U, V and W.

Presentation of websites to a computer user

Abstract: A method, computer readable storage medium, computer program product and a service. A profile of a computer user is obtained that contains meta tags descriptive of the participants of a first social networking website. A second social networking website having meta tags is selected. A profile from the second social networking website is selected. The meta tags of the first and second social networking websites are compared to determine if there is a match of at least one meta tag. Then, a search is made for related websites having at least one meta tag that matches the at least one meta tag. A list of the related websites is then presented to the computer user.

Automated energy transfer calculation and compensation

Abstract: Thermal energy transfer between the adjoining building units is measured. Actual energy consumption is measured in each of the adjoining building units. An energy compensation is calculated for each of the adjoining building units based upon the measured thermal energy transfer between the adjoining building units and the measured actual energy consumption in each of the adjoining building units. This abstract is not to be considered limiting, since other embodiments may deviate from the features described in this abstract.

Time management method and system

Abstract: Disclosed is a time management method which includes detecting a current activity of a user on a computer, classifying the current activity according to a predetermined characteristic, prioritizing the current activity according to a predetermined order of importance, and prompting the user to work on the highest important activity if not already working on it. Also disclosed is a computer readable storage medium storing instructions that, when executed by a computer, causes the computer to perform a method of time management, a computer program product and a system for time management.

A New Family of Extended Baum-Welch Update Rules

Abstract: In this paper, we consider a generalization of the state-of-art discriminative method for optimizing the conditional likelihood in Hidden Markov Models (HMMs), called the Extended Baum-Welch (EBW) algorithm, that has had significant impact on the speech recognition community. We propose a generalized form of EBW update rules that can be associated with a weighted sum of updated and initial models, and demonstrate that using novel update rules can significantly speed up parameter estimation for Gaussian mixtures.