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Algorithmic Decision Making and the Cost of Fairness
This work reformulate algorithmic fairness as constrained optimization: the objective is to maximize public safety while satisfying formal fairness constraints designed to reduce racial disparities, and also to human decision makers carrying out structured decision rules.
Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning
- Bo Wang, Junjie Zhu, E. Pierson, D. Ramazzotti, S. Batzoglou
- Computer ScienceNature Methods
- 9 May 2016
It is shown that SIMLR is scalable and greatly enhances clustering performance while improving the visualization and interpretability of single-cell sequencing data.
WILDS: A Benchmark of in-the-Wild Distribution Shifts
WILDS is presented, a benchmark of in-the-wild distribution shifts spanning diverse data modalities and applications, and is hoped to encourage the development of general-purpose methods that are anchored to real-world distribution shifts and that work well across different applications and problem settings.
ZIFA: Dimensionality reduction for zero-inflated single-cell gene expression analysis
A dimensionality-reduction method is developed, (Z)ero (I)nflated (F)actor (A)nalysis (ZIFA), which explicitly models the dropout characteristics, and it is shown that it improves modeling accuracy on simulated and biological data sets.
Mobility network models of COVID-19 explain inequities and inform reopening
A metapopulation susceptible–exposed–infectious–removed (SEIR) model that integrates fine-grained, dynamic mobility networks to simulate the spread of SARS-CoV-2 in ten of the largest US metropolitan areas is introduced and correctly predicts higher infection rates among disadvantaged racial and socioeconomic groups.
Concept Bottleneck Models
On x-ray grading and bird identification, concept bottleneck models achieve competitive accuracy with standard end-to-end models, while enabling interpretation in terms of high-level clinical concepts (“bone spurs”) or bird attributes ( “wing color”).
A large-scale analysis of racial disparities in police stops across the United States
It is found that black drivers were less likely to be stopped after sunset, when a ‘veil of darkness’ masks one’s race, suggesting bias in stop decisions and evidence that the bar for searching black and Hispanic drivers was lower than that for searching white drivers.
Sharing and Specificity of Co-expression Networks across 35 Human Tissues
- E. Pierson, D. Koller, A. Battle, S. Mostafavi
- Biology, Computer SciencePLoS Comput. Biol.
- 29 October 2014
This work infer tissue-specific gene co-expression networks for 35 tissues in the GTEx dataset using a novel algorithm, GNAT, that uses a hierarchy of tissues to share data between related tissues, and shows that modules conserved across tissues are especially likely to have functions common to all tissues.
ZIFA: Dimensionality reduction for zero-inflated single cell gene expression analysis
A dimensionality reduction method is developed, (Z)ero (I)nflated (F)actor (A)nalysis (ZIFA), which explicitly models the dropout characteristics, and it is shown that it improves modelling accuracy on simulated and biological datasets.
SIMLR: a tool for large-scale single-cell analysis by multi-kernel learning
- Bo Wang, D. Ramazzotti, Luca De Sano, Junjie Zhu, E. Pierson, S. Batzoglou
- Computer SciencebioRxiv
- 21 March 2017
An open-source tool that implements a novel framework to learn a cell-to-cell similarity measure from single-cell RNA-seq data, SIMLR can be effectively used to perform tasks such as dimension reduction, clustering, and visualization of heterogeneous populations of cells.