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Publications associées (26)

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Adaptive Query Processing on RAW Data

Anastasia Ailamaki, Ioannis Alagiannis, Manolis Karpathiotakis, Miguel Sérgio De Oliveira Branco

Database systems deliver impressive performance for large classes of workloads as the result of decades of research into optimizing database engines. High performance, however, is achieved at the cost of versatility. In particular, database systems only op ...

2014

Spiral in Scala: Towards the Systematic Construction of Generators for Performance Libraries

Martin Odersky, Tiark Rompf

Program generators for high performance libraries are an appealing solution to the recurring problem of porting and optimizing code with every new processor generation, but only few such generators exist to date. This is due to not only the difficulty of t ...

Assoc Computing Machinery2014

Online indexing and distributed querying model-view sensor data in the cloud

Karl Aberer, Tian Guo, Hao Zhuang

As various kinds of sensors penetrate our daily life (e.g., sensor networks for environmental monitoring, GPS for localization and navigation), the efficient management of massive amount of sensor data becomes increasingly important at present. Many sensor ...

Springer-Verlag Berlin2014

Method and apparatus for identifying local features

Martin Vetterli, Alireza Ghasemi

A method of local feature identification, comprising the steps of: retrieving data representing a lightfield (101); forming an epipolar volume (V) from the retrieved data; applying a transform to epipolar planes retrieved from said epipolar volume, so as t ...

2014

TOUCH: In-Memory Spatial Join by Hierarchical Data-Oriented Partitioning

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed

Efficient spatial joins are pivotal for many applications and particularly important for geographical information systems or for the simulation sciences where scientists work with spatial models. Past research has primarily focused on disk-based spatial jo ...

2013

EnviroMeter: A Platform for Querying Community-Sensed Data

Karl Aberer, Dipanjan Chakraborty, Saket Sathe

Efficiently querying data collected from Large-area Communitydriven Sensor Networks (LCSNs) is a new and challenging problem. In our previous works, we proposed adaptive techniques for learning models (e.g., statistical, non-parametric, etc.) from such dat ...

2013