Microsoft

About: Microsoft is a company organization based out in Redmond, Washington, United States. It is known for research contribution in the topics: User interface & Context (language use). The organization has 49501 authors who have published 86900 publications receiving 4195429 citations. The organization is also known as: MS & MSFT.

SkipNet: a scalable overlay network with practical locality properties

Abstract: Scalable overlay networks such as Chord, CAN, Pastry, and Tapestry have recently emerged as flexible infrastructure for building large peer-to-peer systems. In practice, such systems have two disadvantages: They provide no control over where data is stored and no guarantee that routing paths remain within an administrative domain whenever possible. SkipNet is a scalable overlay network that provides controlled data placement and guaranteed routing locality by organizing data primarily by string names. SkipNet allows for both fine-grained and coarse-grained control over data placement: Content can be placed either on a pre-determined node or distributed uniformly across the nodes of a hierarchical naming sub-tree. An additional useful consequence of SkipNet's locality properties is that partition failures, in which an entire organization disconnects from the rest of the system, can result in two disjoint, but well-connected overlay networks.

Learning 6D Object Pose Estimation Using 3D Object Coordinates

Abstract: This work addresses the problem of estimating the 6D Pose of specific objects from a single RGB-D image. We present a flexible approach that can deal with generic objects, both textured and texture-less. The key new concept is a learned, intermediate representation in form of a dense 3D object coordinate labelling paired with a dense class labelling. We are able to show that for a common dataset with texture-less objects, where template-based techniques are suitable and state of the art, our approach is slightly superior in terms of accuracy. We also demonstrate the benefits of our approach, compared to template-based techniques, in terms of robustness with respect to varying lighting conditions. Towards this end, we contribute a new ground truth dataset with 10k images of 20 objects captured each under three different lighting conditions. We demonstrate that our approach scales well with the number of objects and has capabilities to run fast.

Electronic shopping and merchandising system

Abstract: The present invention provides a merchant system for online shopping and merchandising. The merchant system architecture provides great flexibility for a merchant to adapt the merchant system to their existing business practices, promotions and databases. The merchant system includes a dynamic page generator, a configurable order processing module and a database module capable of retrieving data from the database without regard to its schema. The present invention enables merchants to create electronic orders which are easily adaptable for different sales situations. The order processing module includes multiple configurable stages to process a merchant's electronic orders. The merchant system is capable of generating pages dynamically using templates having embedded directives. The database module and the dynamic page generator allow merchants to modify their databases and page displays without having to reengineer the merchant system.

The Diffusion of Microfinance

Abstract: To study the impact of the choice of injection points in the diffusion of a new product in a society, we developed a model of word-of-mouth diffusion and then applied it to data on social networks and participation in a newly available microfinance loan program in 43 Indian villages. Our model allows us to distinguish information passing among neighbors from direct influence of neighbors' participation decisions, as well as information passing by participants versus nonparticipants. The model estimates suggest that participants are seven times as likely to pass information compared to informed nonparticipants, but information passed by nonparticipants still accounts for roughly one-third of eventual participation. An informed household is not more likely to participate if its informed friends participate. We then propose two new measures of how effective a given household would be as an injection point. We show that the centrality of the injection points according to these measures constitutes a strong and significant predictor of eventual village-level participation.

The Design of High-Level Features for Photo Quality Assessment

Abstract: We propose a principled method for designing high level features forphoto quality assessment. Our resulting system can classify between high quality professional photos and low quality snapshots. Instead of using the bag of low-level features approach, we first determine the perceptual factors that distinguish between professional photos and snapshots. Then, we design high level semantic features to measure the perceptual differences. We test our features on a large and diverse dataset and our system is able to achieve a classification rate of 72% on this difficult task. Since our system is able to achieve a precision of over 90% in low recall scenarios, we show excellent results in a web image search application.