Article history: Received 27 September 2010 Received in revised form 10 April 2011 Accepted 5 July 2011 Available online 22 July 2011 Anonymization is a practical approach to protect privacy in data. The major objective of privacy preserving data publishing is to protect private information in data whereas data is still useful for some intended applications, such as building classification mode...

Every time a new phone hits the market, and often even before that, it is run through countless numbers of synthetic benchmarks that showcase its computing prowess. People rarely talk about real-world performance, and if they do, it is either anecdotal (“The phone feels very snappy”, “Only occasional hick-ups”, “Apps launch immediately”), or in the form of manual side-by-side app-launching comp...

The problem of estimating the electricity consumption of individual appliances in a building from a limited number of voltage and/or current measurements in the distribution system has received renewed interest from the research community in recent years. In this paper, we present a Building-Level fUlly-labeled dataset for Electricity Disaggregation (BLUED). The dataset consists of voltage and ...

Large-scale image retrieval has been shown remarkable potential in real-life applications. The standard approach is based on Inverted Indexing, given images are represented using Bag-of-Words model. However, one major limitation of both Inverted Index and Bag-of-Words presentation is that they ignore spatial information of visual words in image presentation and comparison. As a result, retrieva...

Feature selection is an important step in building accurate classifiers and provides better understanding of the data sets. In this paper, we propose a feature subset selection method based on high-dimensional mutual information. We also propose to use the entropy of the class attribute as a criterion to determine the appropriate subset of features when building classifiers. We prove that if th...

Many data-driven personalized services require that private data of users is scored against a trained machine learning model. In this paper we propose a novel protocol for privacypreserving classification of decision trees, a popular machine learning model in these scenarios. Our solutions are composed out of building blocks, namely a secure comparison protocol, a protocol for obliviously selec...

Future generations of processors will exhibit an increase of faults over their lifetime, and it becomes increasingly expensive to solve the resulting reliability issues purely at the hardware level. We propose to model computations in terms of restartable task graphs in order to improve reliability at the software level. As a proof of concept, we present Cobra, a novel design for a shared-memor...

In the United States, university buildings use 17% of total non-residential building energy per year. According to the NREL (National Renewable Energy Laboratory), the average lifecycle of a building in a university is 42 years with an EUI (energy use intensity) of 23 kWh/m/y. Current building and energy codes limit the EUI to 16 kWh/m/y for new school buildings; this benchmark can vary dependi...