Distribution-Free Statistical Dispersion Control for Societal Applications

Explicit finite-sample statistical guarantees on model performance are an important ingredient in responsible machine learning. Previous work has focused mainly on bounding either the expected loss of a predictor or the probability that an individual prediction will incur a loss value in a specified range. However, for many high-stakes applications, it is crucial to understand and control the dispersion of a loss distribution, or the extent to which different members of a population experience unequal effects of algorithmic decisions. We initiate the study of distribution-free control of statistical dispersion measures with societal implications and propose a simple yet flexible framework that allows us to handle a much richer class of statistical functionals beyond previous work. Our methods are verified through experiments in toxic comment detection, medical imaging, and film recommendation.Comment: Accepted by NeurIPS as spotlight (top 3% among submissions

Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions

Rigorous guarantees about the performance of predictive algorithms are necessary in order to ensure their responsible use. Previous work has largely focused on bounding the expected loss of a predictor, but this is not sufficient in many risk-sensitive applications where the distribution of errors is important. In this work, we propose a flexible framework to produce a family of bounds on quantiles of the loss distribution incurred by a predictor. Our method takes advantage of the order statistics of the observed loss values rather than relying on the sample mean alone. We show that a quantile is an informative way of quantifying predictive performance, and that our framework applies to a variety of quantile-based metrics, each targeting important subsets of the data distribution. We analyze the theoretical properties of our proposed method and demonstrate its ability to rigorously control loss quantiles on several real-world datasets.Comment: 24 pages, 4 figures. Code is available at https://github.com/jakesnell/quantile-risk-contro

Fairness in Algorithmic Decision Making: An Excursion Through the Lens of Causality

As virtually all aspects of our lives are increasingly impacted by algorithmic decision making systems, it is incumbent upon us as a society to ensure such systems do not become instruments of unfair discrimination on the basis of gender, race, ethnicity, religion, etc. We consider the problem of determining whether the decisions made by such systems are discriminatory, through the lens of causal models. We introduce two definitions of group fairness grounded in causality: fair on average causal effect (FACE), and fair on average causal effect on the treated (FACT). We use the Rubin-Neyman potential outcomes framework for the analysis of cause-effect relationships to robustly estimate FACE and FACT. We demonstrate the effectiveness of our proposed approach on synthetic data. Our analyses of two real-world data sets, the Adult income data set from the UCI repository (with gender as the protected attribute), and the NYC Stop and Frisk data set (with race as the protected attribute), show that the evidence of discrimination obtained by FACE and FACT, or lack thereof, is often in agreement with the findings from other studies. We further show that FACT, being somewhat more nuanced compared to FACE, can yield findings of discrimination that differ from those obtained using FACE.Comment: 7 pages, 2 figures, 2 tables.To appear in Proceedings of the International Conference on World Wide Web (WWW), 201

Oriented coloring: complexity and approximation

International audienceThis paper is devoted to an oriented coloring problem motivated by a task assignment model. A recent result established the NP-completeness of deciding whether a digraph is k-oriented colorable; we extend this result to the classes of bipartite digraphs and circuit-free digraphs. Finally, we investigate the approximation of this problem: both positive and negative results are devised

Effects of the Dietary Approaches to Stop Hypertension (DASH) Eating Plan on Cardiovascular Risks Among Type 2 Diabetic Patients: A randomized crossover clinical trial

Objective: To determine the effects of the Dietary Approaches to Stop Hypertension (DASH) eating pattern on cardiometabolic risks in type 2 diabetic patients. Research design and methods: A randomized crossover clinical trial was undertaken in 31 type 2 diabetic patients. For 8 weeks, participants were randomly assigned to a control diet or the DASH eating pattern. Results: After following the DASH eating pattern, body weight (P = 0.007) and waist circumference (P = 0.002) reduced significantly. Fasting blood glucose levels and A1C decreased after adoption of the DASH diet (−29.4 ± 6.3 mg/dl; P = 0.04 and −1.7 ± 0.1%; P = 0.04, respectively). After the DASH diet, the mean change for HDL cholesterol levels was higher (4.3 ± 0.9 mg/dl; P = 0.001) and LDL cholesterol was reduced (−17.2 ± 3.5 mg/dl; P = 0.02). Additionally, DASH had beneficial effects on systolic (−13.6 ± 3.5 vs. −3.1 ± 2.7 mmHg; P = 0.02) and diastolic blood pressure (−9.5 ± 2.6 vs. −0.7 ± 3.3 mmHg; P = 0.04). Conclusions: Among diabetic patients, the DASH diet had beneficial effects on cardiometabolic risks

Effects of dairy intake on weight maintenance

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Towards Fairer Datasets: Filtering and Balancing the Distribution of the People Subtree in the ImageNet Hierarchy

Computer vision technology is being used by many but remains representative of only a few. People have reported misbehavior of computer vision models, including offensive prediction results and lower performance for underrepresented groups. Current computer vision models are typically developed using datasets consisting of manually annotated images or videos; the data and label distributions in these datasets are critical to the models' behavior. In this paper, we examine ImageNet, a large-scale ontology of images that has spurred the development of many modern computer vision methods. We consider three key factors within the "person" subtree of ImageNet that may lead to problematic behavior in downstream computer vision technology: (1) the stagnant concept vocabulary of WordNet, (2) the attempt at exhaustive illustration of all categories with images, and (3) the inequality of representation in the images within concepts. We seek to illuminate the root causes of these concerns and take the first steps to mitigate them constructively.Comment: Accepted to FAT* 202

Sarcopenia and preserved bone mineral density in paediatric survivors of high-risk neuroblastoma with growth failure

Background: Survival from paediatric high-risk neuroblastoma (HR-NBL) has increased, but cis-retinoic acid (cis-RA), the cornerstone of HR-NBL therapy, can cause osteoporosis and premature physeal closure and is a potential threat to skeletal structure in HR-NBL survivors. Sarcopenia is associated with increased morbidity in survivors of paediatric malignancies. Low muscle mass may be associated with poor prognosis in HR-NBL patients but has not been studied in these survivors. The study objective was to assess bone density, body composition and muscle strength in HR-NBL survivors compared with controls. Methods: This prospective cross-sectional study assessed areal bone mineral density (aBMD) of the whole body, lumbar spine, total hip, femoral neck, distal 1/3 and ultradistal radius and body composition (muscle and fat mass) using dual-energy X-ray absorptiometry (DXA) and lower leg muscle strength using a dynamometer. Measures expressed as sex-specific standard deviation scores (Z-scores) included aBMD (adjusted for height Z-score), bone mineral apparent density (BMAD), leg lean mass (adjusted for leg length), whole-body fat mass index (FMI) and ankle dorsiflexion peak torque adjusted for leg length (strength-Z). Muscle-specific force was assessed as strength relative to leg lean mass. Outcomes were compared between HR-NBL survivors and controls using Student's t-test or Mann–Whitney U test. Linear regression models examined correlations between DXA and dynamometer outcomes. Results: We enrolled 20 survivors of HR-NBL treated with cis-RA [13 male; mean age: 12.4 ± 1.6 years; median (range) age at therapy initiation: 2.6 (0.3–9.1) years] and 20 age-, sex- and race-matched controls. Height-Z was significantly lower in HR-NBL survivors compared with controls (−1.73 ± 1.38 vs. 0.34 ± 1.12, P < 0.001). Areal BMD-Z, BMAD-Z, FMI-Z, visceral adipose tissue and subcutaneous adipose tissue were not significantly different in HR-NBL survivors compared with controls. Compared with controls, HR-NBL survivors had lower leg lean mass-Z (−1.46 ± 1.35 vs. − 0.17 ± 0.84, P < 0.001) and strength-Z (−1.13 ± 0.86 vs. − 0.15 ± 0.71, P < 0.001). Muscle-specific force was lower in HR-NBL survivors compared with controls (P < 0.05). Conclusions: Bone mineral density and adiposity are not severely impacted in HR-NBL survivors with growth failure, but significant sarcopenia persists years after treatment. Future studies are needed to determine if sarcopenia improves with muscle-specific interventions in this population of cancer survivors

A pp-adic Approach to the Weil Representation of Discriminant Forms Arising from Even Lattices

Suppose that $M$ is an even lattice with dual $M^{*}$ and level $N$. Then the group $Mp_{2}(\mathbb{Z})$, which is the unique non-trivial double cover of $SL_{2}(\mathbb{Z})$, admits a representation $\rho_{M}$, called the Weil representation, on the space $\mathbb{C}[M^{*}/M]$. The main aim of this paper is to show how the formulae for the $\rho_{M}$-action of a general element of $Mp_{2}(\mathbb{Z})$ can be obtained by a direct evaluation which does not depend on ``external objects'' such as theta functions. We decompose the Weil representation $\rho_{M}$ into $p$-parts, in which each $p$-part can be seen as subspace of the Schwartz functions on the $p$-adic vector space $M_{\mathbb{Q}_{p}}$. Then we consider the Weil representation of $Mp_{2}(\mathbb{Q}_{p})$ on the space of Schwartz functions on $M_{\mathbb{Q}_{p}}$, and see that restricting to $Mp_{2}(\mathbb{Z})$ just gives the $p$-part of $\rho_{M}$ again. The operators attained by the Weil representation are not always those appearing in the formulae from 1964, but are rather their multiples by certain roots of unity. For this, one has to find which pair of elements, lying over a matrix in $SL_{2}(\mathbb{Q}_{p})$, belong to the metaplectic double cover. Some other properties are also investigated.Comment: 29 pages, shortened a lo