Search
Now showing items 11-20 of 29
The Algorithmic Foundations of Private Computational Social Science
(2022-08-12)
Social scientists, political scientists, economists, and healthcare researchers crucially rely on statistical methods to further the study of individuals, society, and human behavior via inferential analysis. Unfortunately, ...
Invariance versus Adversarial Learning in Domain Generalization with Applications to Neuroscience
(2022-05-23)
We explore the practical application of two modern domain
invariant representation-learning techniques for addressing the domain
generalization problem in statistical machine learning. Specifically, we
investigate the ...
Discriminative Sequence Models Extract Personally Identifiable Information from Public Gene Expression Datasets
(2022-05-25)
The growing scale of functional genomics datasets is enabling researchers to better understand the genetic determinants of gene expression, for example through expression quantitative trait loci (eQTL) studies.
With an ...
The 2020 Presidential Election on Twitter: An Exploration of Candidates’ Social Presence, Campaign Momentum, and the Effect of Misinformation
(2021-06-04)
Twitter has evolved from a site of inconsequential information spread to an instant primary source used as the preferred outlet to discuss and witness any semblance of news the emerges each day. Political outreach thrives ...
Learning Optimal Summaries of Clinical Time-series with Concept Bottleneck Models
(2022-05-23)
Despite machine learning models' state-of-the-art performance in numerous clinical prediction and intervention tasks, their complex black-box processes pose a great barrier to their real-world deployment. Clinical experts ...
Efficient Algorithms for Statistical Estimation
(2021-08-24)
Statistical estimation aims to find parameters or structures relating to an underlying distribution given empirical samples. Many statistical estimation problems are information theoretically solvable, but are not fully ...
Ending Research Subject Overexploitation: Methods to Reduce Respondent Overuse and Privacy Violations while Increasing Insights from Data
(2022-11-23)
The low price of data collection and use in the Internet age has facilitated collective ir- responsibility, where private companies, academics, and governments all fail to internalize the costs to respondents and other ...
OpenDP Programming Framework for Renyi Privacy Filters and Odometers
(2022-05-23)
Data scientists work with large-scale sensitive data, which inevitably leads to privacy risks. Differential Privacy (DP) is a mathematical definition of privacy that aims to mitigate privacy risks inherent in data analysis ...
Improved Generative Evaluation: Utilizing the Manifold Hypothesis
(2022-03-07)
Reliably diagnosing and evaluating generative models remains an open problem. The most common metric employed to measure the performance of image generating models has been the Fréchet Inception Distance (FID) score. It ...
A Multi-resolution Hard Attention Model to Select Regions of Interest on Whole Pathology Slide Images
(2022-05-23)
With drastic improvements in the performance of neural networks and computer vision algorithms, deep learning-based imaging analysis models have been applied to a wide variety of fields. Along with this expansion, many ...