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Related publications (32)

Time- and Space-Efficient Spatial Data Analytics

Mirjana Pavlovic

Advances in data acquisition technologies and supercomputing for large-scale simulations have led to an exponential growth in the volume of spatial data. This growth is accompanied by an increase in data complexity, such as spatial density, but also by mor ...

EPFL2019

Dictionary Compression in Point Cloud Data Management

Anastasia Ailamaki, Mirjana Pavlovic

Nowadays, massive amounts of point cloud data can be collected thanks to advances in data acquisition and processing technologies such as dense image matching and airborne LiDAR scanning. With the increase in volume and precision, point cloud data offers a ...

ASSOC COMPUTING MACHINERY2019

HetExchange: Encapsulating heterogeneous CPU-GPU parallelism in JIT compiled engines

Anastasia Ailamaki, Manolis Karpathiotakis, Raja Appuswamy, Periklis Chrysogelos

Modern server hardware is increasingly heterogeneous as hardware accelerators, such as GPUs, are used together with multicore CPUs to meet the computational demands of modern data analytics workloads. Unfortunately, query parallelization techniques used by ...

2019

QUASII: QUery-Aware Spatial Incremental Index

Anastasia Ailamaki, Darius Sidlauskas, Thomas Heinis, Mirjana Pavlovic

With large-scale simulations of increasingly detailed models and improvement of data acquisition technologies, massive amounts of data are easily and quickly created and collected. Traditional systems require indexes to be built before analytic queries can ...

2018

Proximity Operators of Discrete Information Divergences

Mireille El Gheche, Giovanni Chierchia

While phi-divergences have been extensively studied in convex analysis, their use in optimization problems often remains challenging. In this regard, one of the main shortcomings of existing methods is that the minimization of phi-divergences is usually pe ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Interactive Visual Exploration of Spatio-Temporal Urban Data Sets using Urbane

Anastasia Ailamaki, Eleni Tzirita Zacharatou, Haoqiong Bian

The recent explosion in the number and size of spatio-temporal data sets from urban environments and social sensors creates new opportunities for data-driven approaches to understand and improve cities. Visual analytics systems like Urbane aim to empower d ...

2018

Practical Private Range Search in Depth

Odysseas Papapetrou, Ioannis Demertzis

We consider a data owner that outsources its dataset to an untrusted server. The owner wishes to enable the server to answer range queries on a single attribute, without compromising the privacy of the data and the queries. There are several schemes on “pr ...

2018

Adding flexibility to multi-tenant networks

Georgios Ioannidis

Cloud computing has been experiencing sharp development over the last years, leading to an increased demand for application migration to the cloud. Cloud providers, in an effort to attract more customers and earn their confidence, offer to tenants the illu ...

EPFL2018

Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning

Karl Aberer, Rémi Philippe Lebret, Hamza Harkous, Kassem Fawaz

Privacy policies are the primary channel through which companies inform users about their data collection and sharing practices. These policies are often long and difficult to comprehend. Short notices based on information extracted from privacy policies h ...

USENIX ASSOC2018

Compilation Techniques for Incremental Collection Processing

Daniel Lupei

Many map-reduce frameworks as well as NoSQL systems rely on collection programming as their interface of choice due to its rich semantics along with an easily parallelizable set of primitives. Unfortunately, the potential of collection programming is not ...

EPFL2017

Distributed Time Series Analytics

Tian Guo

In recent years time series data has become ubiquitous thanks to affordable sensors and advances in embedded technology. Large amount of time-series data are continuously produced in a wide spectrum of applications, such as sensor networks, medical monitor ...

EPFL2017

ReCache: Reactive Caching for Fast Analytics over Heterogeneous Data

Anastasia Ailamaki, Manolis Karpathiotakis, Tahir Azim

As data continues to be generated at exponentially growing rates in heterogeneous formats, fast analytics to extract meaningful information is becoming increasingly important. Systems widely use in-memory caching as one of their primary techniques to speed ...

2017

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