Institution
University of Cagliari
Education•Cagliari, Italy•
About: University of Cagliari is a education organization based out in Cagliari, Italy. It is known for research contribution in the topics: Population & Dopamine. The organization has 11029 authors who have published 29046 publications receiving 771023 citations. The organization is also known as: Università degli Studi di Cagliari & Universita degli Studi di Cagliari.
Topics: Population, Dopamine, Dopaminergic, Context (language use), Medicine
Papers published on a yearly basis
Papers
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TL;DR: Experimental results on the KDD-Cup 1999 dataset show that the proposed anomaly IDS achieves high attack detection rate and low false alarm rate at the same time.
228 citations
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TL;DR: Results show that the new polarimetric approach is able to assist classification, and the target decomposition theorem is exploited to distinguish oil spills and look-alikes.
Abstract: A study on sea oil spill observation by means of polarimetric synthetic aperture radar (SAR) data is accomplished. It is based on the use of a polarimetric constant false alarm rate filter to detect dark patches over SAR images. Then, the target decomposition theorem is exploited to distinguish oil spills and look-alikes. Experiments are conducted on polarimetric SAR data acquired during the SIR-C/X-SAR mission on October 1994. The data were processed and calibrated at the Jet Propulsion Laboratory, National Aeronautics and Space Administration. Results show that the new polarimetric approach is able to assist classification
228 citations
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TL;DR: The present results suggest that the PVN is the brain area where D2 DA agonists act to induce penile erection and yawning in rats, and for the first time a possible involvement of the incerto-hypothalamic DA system in the expression of penile erections and yawns is suggested.
228 citations
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TL;DR: In this article, track reconstruction efficiency at LHCb using J/psi -> mu(+)mu(-) decays is determined. But the accuracy of track reconstruction was not analyzed.
Abstract: The determination of track reconstruction efficiencies at LHCb using J/psi -> mu(+)mu(-) decays is presented. Efficiencies above 95% are found for the data taking periods in 2010, 2011, and 2012. The ratio of the track reconstruction efficiency of muons in data and simulation is compatible with unity and measured with an uncertainty of 0.8% for data taking in 2010, and at a precision of 0.4% for data taking in 2011 and 2012. For hadrons an additional 1.4% uncertainty due to material interactions is assumed. This result is crucial for accurate cross section and branching fraction measurements in LHCb.
228 citations
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TL;DR: This paper proposes a novel adversary-aware feature selection model that can improve classifier security against evasion attacks, by incorporating specific assumptions on the adversary's data manipulation strategy.
Abstract: Pattern recognition and machine learning techniques have been increasingly adopted in adversarial settings such as spam, intrusion, and malware detection, although their security against well-crafted attacks that aim to evade detection by manipulating data at test time has not yet been thoroughly assessed. While previous work has been mainly focused on devising adversary-aware classification algorithms to counter evasion attempts, only few authors have considered the impact of using reduced feature sets on classifier security against the same attacks. An interesting, preliminary result is that classifier security to evasion may be even worsened by the application of feature selection. In this paper, we provide a more detailed investigation of this aspect, shedding some light on the security properties of feature selection against evasion attacks. Inspired by previous work on adversary-aware classifiers, we propose a novel adversary-aware feature selection model that can improve classifier security against evasion attacks, by incorporating specific assumptions on the adversary’s data manipulation strategy. We focus on an efficient, wrapper-based implementation of our approach, and experimentally validate its soundness on different application examples, including spam and malware detection.
228 citations
Authors
Showing all 11160 results
Name | H-index | Papers | Citations |
---|---|---|---|
Herbert W. Marsh | 152 | 646 | 89512 |
Michele Parrinello | 133 | 637 | 94674 |
Dafna D. Gladman | 129 | 1036 | 75273 |
Peter J. Anderson | 120 | 966 | 63635 |
Alessandro Vespignani | 118 | 419 | 63824 |
C. Patrignani | 117 | 1754 | 110008 |
Hermine Katharina Wöhri | 116 | 629 | 55540 |
Francesco Muntoni | 115 | 963 | 52629 |
Giancarlo Comi | 109 | 961 | 54270 |
Giorgio Parisi | 108 | 941 | 60746 |
Luca Benini | 101 | 1453 | 47862 |
Alessandro Cardini | 101 | 1288 | 53804 |
Nicola Serra | 100 | 1042 | 46640 |
Jurg Keller | 99 | 389 | 35628 |
Giulio Usai | 97 | 517 | 39392 |