Promoting Fairness through Hyperparameter Optimization

Considerable research effort has been guided towards algorithmic fairness but real-world adoption of bias reduction techniques is still scarce. Existing methods are either metric- or model-specific, require access to sensitive attributes at inference time, or carry high development or deployment costs. This work explores the unfairness that emerges when optimizing ML models solely for predictive performance, and how to mitigate it with a simple and easily deployed intervention: fairness-aware hyperparameter optimization (HO). We propose and evaluate fairness-aware variants of three popular HO algorithms: Fair Random Search, Fair TPE, and Fairband. We validate our approach on a real-world bank account opening fraud case-study, as well as on three datasets from the fairness literature. Results show that, without extra training cost, it is feasible to find models with 111% mean fairness increase and just 6% decrease in performance when compared with fairness-blind HO.Comment: arXiv admin note: substantial text overlap with arXiv:2010.0366

FairGBM: Gradient Boosting with Fairness Constraints

Machine Learning (ML) algorithms based on gradient boosted decision trees (GBDT) are still favored on many tabular data tasks across various mission critical applications, from healthcare to finance. However, GBDT algorithms are not free of the risk of bias and discriminatory decision-making. Despite GBDT's popularity and the rapid pace of research in fair ML, existing in-processing fair ML methods are either inapplicable to GBDT, incur in significant train time overhead, or are inadequate for problems with high class imbalance. We present FairGBM, a learning framework for training GBDT under fairness constraints with little to no impact on predictive performance when compared to unconstrained LightGBM. Since common fairness metrics are non-differentiable, we employ a "proxy-Lagrangian" formulation using smooth convex error rate proxies to enable gradient-based optimization. Additionally, our open-source implementation shows an order of magnitude speedup in training time when compared with related work, a pivotal aspect to foster the widespread adoption of FairGBM by real-world practitioners

Avaliação sensorial de cerveja pilsen de resíduos de guaraná (Paullinia cupana) / Sensory Evaluation of Pilsner Beer Made with Guarana residues (Paullinia cupana)

O guaraná (Paullinia cupana) é uma planta nativa da América do Sul, encontrada principalmente na Venezuela e Brasil. Seu componente principal é a guaranina, uma substância quimicamente idêntica à cafeína. Nas condições experimentais em que foi conduzido esse trabalho foram produzidas duas cervejas, T1 e T2, onde T1 era uma cerveja testemunha do tipo pilsen e a T2 era uma cerveja produzida com adição do resíduo (casca) do guaraná, onde se tirou os seguintes resultados: Na análise da composição centesimal da amostra do guaraná, podemos observar que as variáveis analisadas se assemelharam com o descrito na literatura, e as mesmas estão de conformidade com a legislação vigente para o produto analisado. A cerveja do tipo pilsen com a adição do resíduo (casca) do guaraná teve a sua tonalidade mais escura. Observou-se que a segunda cerveja (T2) teve um amargor maior quando foi analisado sensorialmente, que deve ter sido originado da adição do resíduo do guaraná. A aceitação global para o tratamento dois (T2) foi superior a 60%, quando a intenção de compra das cervejas o T2 teve 74%, mostrando-se um produto com potencial comercial. O emprego da casca do guaraná como adjunto foi uma alternativa viável na preparação da cerveja

Análise comparativa de tabela de composição nutricional de biscoito salgado cream cracker com resultados laboratoriais / Comparative analysis of table of nutritional composition of biscoito salgado cream cracker with laboratory results

O estudo da composição centesimal serve de ferramenta para a análise de alimentos, tornando-se essencial para o consumo equilibrado de nutrientes, seguindo a Ingestão Diária Recomendada. A determinação dos componentes existentes nos alimentos possibilita a rotulagem nutricional fiel ao conteúdo disponibilizado ao consumidor, sem a qual ele não poderia exercer seu direito de escolha do produto. Este trabalho objetivou realizar um estudo comparativo da composição nutricional apresentada pela embalagem comercial de biscoito salgado cream cracker, com os achados a partir da análise centesimal do produto. A análise centesimal seguiu a metodologia estabelecida pelo Instituto Adolfo Lutz. Os resultados a partir dos dados experimentais diferem dos informados pela embalagem, sendo confirmados pela análise estatística. Portanto, através da análise centesimal realizada foi possível detectar que as informações contidas na embalagem do produto não condizem com as evidenciadas em laboratório

Machine learning for optimized buildings morphosis

International audienceThe world is rapidly urbanizing, with an increasing number of new building constructions. This involves increasing the world's energy consumption and its associated greenhouse gas emissions. Computational tools are playing an increasing impact on the architectural design process. Recently, Machine learning (ML) has been applied to building design and has evinced its potential to improve building performance. This paper tries to review the use of ML for the building morphosis. We then forecast the use of machine learning for building optimized morphosis in the early design stage particularly for ensuring summer shading and winter solar access between neighbors

Accumulation of Non-Superoxide Anion Reactive Oxygen Species Mediates Nitrogen-Limited Alcoholic Fermentation by Saccharomyces cerevisiae▿

Throughout alcoholic fermentation, nitrogen depletion is one of the most important environmental stresses that can negatively affect the yeast metabolic activity and ultimately leads to fermentation arrest. Thus, the identification of the underlying effects and biomarkers of nitrogen limitation is valuable for controlling, and therefore optimizing, alcoholic fermentation. In this study, reactive oxygen species (ROS), plasma membrane integrity, and cell cycle were evaluated in a wine strain of Saccharomyces cerevisiae during alcoholic fermentation in nitrogen-limiting medium under anaerobic conditions. The results indicated that nitrogen limitation leads to an increase in ROS and that the superoxide anion is a minor component of the ROS, but there is increased activity of both Sod2p and Cta1p. Associated with these effects was a decrease in plasma membrane integrity and a persistent cell cycle arrest at G0/G1 phases. Moreover, under these conditions it appears that autophagy, evaluated by ATG8 expression, is induced, suggesting that this mechanism is essential for cell survival but does not prevent the cell cycle arrest observed in slow fermentation. Conversely, nitrogen refeeding allowed cells to reenter cell cycle by decreasing ROS generation and autophagy. Altogether, the results provide new insights on the understanding of wine fermentations under nitrogen-limiting conditions and further indicate that ROS accumulation, evaluated by the MitoTracker Red dye CM-H2XRos, and plasma membrane integrity could be useful as predictive markers of fermentation problems

Association between histological findings, aminotransferase levels and viral genotype in chronic hepatitis C infection

Made available in DSpace on 2015-04-06T17:18:22Z (GMT). No. of bitstreams: 2 elizabeth_lampeetal_IOC_2014.pdf: 687985 bytes, checksum: ad06942bd96a3507552526d1d9a5b42a (MD5) license.txt: 1914 bytes, checksum: 7d48279ffeed55da8dfe2f8e81f3b81f (MD5) Previous issue date: 2014Universidade Federal do Pará. Núcleo de Medicina Tropical. Laboratório de Patologia Clínica das Doenças Tropicais. Belém, PA, Brasil.Universidade Federal do Pará. Núcleo de Medicina Tropical. Laboratório de Patologia Clínica das Doenças Tropicais. Belém, PA, Brasil.Universidade Federal do Pará. Núcleo de Medicina Tropical. Laboratório de Patologia Clínica das Doenças Tropicais. Belém, PA, Brasil.Universidade Federal do Pará. Núcleo de Medicina Tropical. Laboratório de Patologia Clínica das Doenças Tropicais. Belém, PA, Brasil.Universidade Federal do Pará. Núcleo de Medicina Tropical. Laboratório de Patologia Clínica das Doenças Tropicais. Belém, PA, Brasil.Universidade Federal do Pará. Núcleo de Medicina Tropical. Laboratório de Patologia Clínica das Doenças Tropicais. Belém, PA, Brasil.Universidade Federal do Pará. Núcleo de Medicina Tropical. Laboratório de Patologia Clínica das Doenças Tropicais. Belém, PA, Brasil.Universidade Federal do Pará. Núcleo de Medicina Tropical. Laboratório de Patologia Clínica das Doenças Tropicais. Belém, PA, Brasil.Fundação Oswaldo Cruz. Rio de Janeiro, RJ, Brasil.Universidade Federal do Pará. Núcleo de Medicina Tropical. Laboratório de Patologia Clínica das Doenças Tropicais. Belém, PA, Brasil.Michigan State University. Institute of International Health. Michigan, USA.The genomic heterogeneity of hepatitis C virus (HCV) influences liver disorders. This study aimed to determine the prevalence of HCV genotypes and to investigate the influence of these genotypes on disease progression. Methods: Blood samples and liver biopsies were collected from HCV-seropositive patients for serological analysis, biochemical marker measurements, HCV genotyping and histopathological evaluation. Results: Hepatitis C virus-ribonucleic acid (HCV-RNA) was detected in 107 patients (90.6% with genotype 1 and 9.4% with genotype 3). Patients infected with genotype 1 exhibited higher mean necroinflammatory activity and fibrosis. Conclusions: HCV genotype 1 was the most prevalent and was associated with greater liver dysfunction