Encrypted statistical machine learning: new privacy preserving methods

We present two new statistical machine learning methods designed to learn on fully homomorphic encrypted (FHE) data. The introduction of FHE schemes following Gentry (2009) opens up the prospect of privacy preserving statistical machine learning analysis and modelling of encrypted data without compromising security constraints. We propose tailored algorithms for applying extremely random forests, involving a new cryptographic stochastic fraction estimator, and na\"{i}ve Bayes, involving a semi-parametric model for the class decision boundary, and show how they can be used to learn and predict from encrypted data. We demonstrate that these techniques perform competitively on a variety of classification data sets and provide detailed information about the computational practicalities of these and other FHE methods.Comment: 39 page

Encrypted accelerated least squares regression.

Information that is stored in an encrypted format is, by definition, usually not amenable to statistical analysis or machine learning methods. In this paper we present detailed analysis of coordinate and accelerated gradient descent algorithms which are capable of fitting least squares and penalised ridge regression models, using data encrypted under a fully homomorphic encryption scheme. Gradient descent is shown to dominate in terms of encrypted computational speed, and theoretical results are proven to give parameter bounds which ensure correctness of decryption. The characteristics of encrypted computation are empirically shown to favour a non-standard acceleration technique. This demonstrates the possibility of approximating conventional statistical regression methods using encrypted data without compromising privacy

Determinantes da remuneração nas empresas portuguesas

A análise e explicação das determinantes das diversas formas de remuneração em Portugal são o principal objectivo deste trabalho. Apesar da existência de diversos estudos sobre remunerações, até agora não foram desenvolvidos estudos sobre quais as determinantes explicativas da realidade empresarial. Este estudo identifica o conjunto de características das empresas e dos colaboradores que explicam o montante e a probabilidade de auferir remuneração variável e quais as determinantes da remuneração base, comparando-se os dois modelos através do «colaborador padrão». Os resultados mostram que a remuneração variável é mais utilizada nos níveis hierárquicos superiores, na área comercial, em empresas de menor dimensão, em filiais de empresas estrangeiras e para colaboradores com educação superior. Quanto à rendibilidade, os resultados revelam uma relação positiva com a probabilidade de existência de remuneração variável. No entanto, os montantes de remuneração variável são mais elevados nas empresas com menor rendibilidade

Diarylethene-Based Ionic Liquids: Synthesis and Photo-Driven Solution Properties

Funding text The authors acknowledge Fundação para a Ciência e Tecnologia through the PhD grant SFRH/BD/81693/2011 (M. R. C. Soromenho). This work was supported by the Associate Laboratory for Green Chemistry-LAQV (Portugal) (UIDB/50006/2020, UIDP/50006/2020, and LA/P/0008/2020) and by the Instituto de Investigação do Medicamento (iMed.ULisboa) (UIDB/04138/2020, and UIDP/04138/2020) which are financed by national funds from FCT/MCTES. The NMR spectrometers are part of the National NMR Network (PTNMR) are partially supported by Infrastructure Project Nº 022161 (co-financed by FEDER through COMPETE 2020, POCI and PORL and FCT through PIDDAC).In this work, the design and synthesis of a series of photochromic gemini diarylethene-based ionic liquids (GDILs) with different cationic motifs is reported. Several synthetic pathways were optimized for the formation of cationic GDILs with chloride as the counterion. The different cationic motifs were achieved through the N-alkylation of the photochromic organic core unit with different tertiary amines, including different aromatic amines such as imidazole derivatives and pyridinium, and other non-aromatic amines. These novel salts present surprising water solubility with unexplored photochromic features that broaden their known applications. The covalent attachment of the different side groups dictates their water solubility and differences upon photocyclization. The physicochemical properties of GDILs in aqueous and in imidazolium-based ionic liquid (IL) solutions were investigated. Upon irradiation with ultraviolet (UV) light, we have observed changes in the physico-chemical properties of distinct solutions containing these GDILs, at very low concentrations. More specifically, in aqueous solution, the overall conductivity increased with the time of UV photoirradiation. In contrast, in IL solution, these photoinducible changes are dependent on the type of ionic liquid used. These compounds can improve non-ionic and ionic liquids’ solutions since we can change their properties, such as conductivity, viscosity or ionicity, only by UV photoirradiation. The electronic and conformational changes associated with these innovative stimuli GDILs may open new opportunities for their use as photoswitchable materials.publishersversionpublishe