Interpretable Machine Learning for Privacy-Preserving Pervasive Systems

Our everyday interactions with pervasive systems generate traces that capture various aspects of human behavior and enable machine learning algorithms to extract latent information about users. In this paper, we propose a machine learning interpretability framework that enables users to understand how these generated traces violate their privacy

California Community Choice Aggregation Law & Regulation

The purpose of this special topic is to provide a summary of the laws and regulations associated with the development of Community Choice Aggregation (“CCA”) in California and the growing impact of CCA in the California energy market

Non-Local Control of Single Surface Plasmon

Quantum entanglement is a stunning consequence of the superposition principle. This universal property of quantum systems has been intensively explored with photons, atoms, ions and electrons. Collective excitations such as surface plasmons exhibit quantum behaviors. For the first time, we report an experimental evidence of non-local control of single plasmon interferences through entanglement of a single plasmon with a single photon. We achieved photon-plasmon entanglement by converting one photon of an entangled photon pair into a surface plasmon. The plasmon is tested onto a plasmonic platform in a Mach-Zehnder interferometer. A projective measurement on the polarization of the photon allows the non-local control of the interference state of the plasmon. Entanglement between particles of various natures paves the way to the design of hybrid systems in quantum information networks.Comment: 6 pages, 3 figure

Socio-Emotional Functioning and Face Recognition Ability in the Normal Population

Recent research indicates face recognition ability varies within the normal population. To date, two factors have been identified that influence this cognitive process: the age and gender of the perceiver. In this paper, we examine the influence of socio-emotional functioning on face recognition ability. We invited participants with high and low levels of empathy (as indicated by the Empathy Quotient) to take part in a face recognition test. Participants were asked to study a set of faces, and at test viewed the studied faces intermixed with novel faces. As predicted, high empaths achieved higher scores in the face recognition test compared to low empaths. This pattern of findings provides further evidence that face recognition ability varies within the normal population, and suggests socio-emotional functioning may be an additional factor that influences face recognition ability