Ricerc@Sapienza

This paper describes a novel biometric architecture to implement unsupervised face recognition across varying demographics. The present proposal deals with ethnicity, gender and age, but the same strategy can be crafted for any mix of soft/hard biometrics, sensors, and/or methods. Our aim is not to explicitly distinguish demographic features of a subject (e.g., male vs. female). We rather aim at implicitly exploiting such information to improve the accuracy of subject identification. The role demographics plays in authentication has been reported by many recent studies.

This paper presents an approach to gait recognition based on a single consumer accelerometer, built in most present mobile devices. It does not propose a completely novel

This paper presents a novel strategy to implement a CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart). The aim of these tests is to easily and reliably distinguish between real human users and (malicious) bots. The approach underlying FATCHA is to exploit real time capture of human actions instead of human ability to recognize visual or auditory items. The latter approach explicitly requires proposing a challenge difficult for an automatic responder but easy for a human.

We study the question of fair clustering under the disparate impact doctrine, where each protected class must have approximately equal representation in every cluster. We formulate the fair clustering problem under both the k-center and the k-median objectives, and show that even with two protected classes the problem is challenging, as the optimum solution can violate common conventions - for instance a point may no longer be assigned to its nearest cluster center!

Counting graphlets is a well-studied problem in graph mining and social network analysis. Recently, several papers explored very simple and natural approaches based on Monte Carlo sampling of Markov Chains (MC), and reported encouraging results. We show, perhaps surprisingly, that this approach is outperformed by a carefully engineered version of color coding (CC) [1], a sophisticated algorithmic technique that we extend to the case of graphlet sampling and for which we prove strong statistical guarantees.

Apache Cassandra is an highly scalable and available NoSql datastore, largely used by enterprises of each size and for application areas that range from entertainment to big data analytics. Managed Cassandra service providers are emerging to hide the complexity of the installation, fine tuning and operation of Cassandra virtual data centers (VDCs). This paper address the problem of energy efficient auto-scaling of Cassandra VDC in managed Cassandra data centers. We propose three energy-aware autoscaling algorithms: Opt, LocalOpt and LocalOpt-H.

Today, The cloud industry is adopting the container technology both for internal usage and as commercial offering. The use of containers as base technology for large-scale systems opens many challenges in the area of resource management at run-Time. This paper addresses the problem of selecting the more appropriate performance metrics to activate auto-scaling actions. Specifically, we investigate the use of relative and absolute metrics. Results demonstrate that, for CPU intense workload, the use of absolute metrics enables more accurate scaling decisions.

We propose a highly parallel and distributed multiset computing model having as its underlying structure an undirected graph whose nodes are processors, each endowed with a polarity and with a set of rules all of the same kind, one of increment, decrement or substitution. Processors communicate with each other via a protocol based on the compatibility between their polarization and the polarization of the data, as computed by a valuation mapping. We show that this model can simulate any multiset Turing machine.

Vulnerability due to inter-connectivity of multiple networks has been observed in many complex networks. Previous works mainly focused on robust network design and on recovery strategies after sporadic or massive failures in the case of complete knowledge of failure location. We focus on cascading failures involving the power grid and its communication network with consequent imprecision in damage assessment. We tackle the problem of mitigating the ongoing cascading failure and providing a recovery strategy.

Plasmonic materials have the free electron oscillations in a metal coupled to photons and allow near field amplification of radiation below the plasmon edge. Metals such as Au and Ag can be used for visible wavelengths but these materials are incompatible with silicon foundries due to fast diffusion and the deep level trap states formed.