2 citations · 4 across the 3 of their papers we have counts for
7 papers
Identifying biases in legal data: An algorithmic fairness perspective
Jackson Sargent, Melanie Weber
The need to address representation biases and sentencing disparities in legal case data has long been recognized. Here, we study the problem of identifying and measuring biases in…
Neighborhood Growth Determines Geometric Priors for Relational Representation Learning
Melanie Weber
The problem of identifying geometric structure in heterogeneous, high-dimensional data is a cornerstone of representation learning. While there exists a large body of literature on…
Projection-free nonconvex stochastic optimization on Riemannian manifolds
Melanie Weber, Suvrit Sra
We study stochastic projection-free methods for constrained optimization of smooth functions on Riemannian manifolds, i.e., with additional constraints beyond the parameter domain…
The Oracle of DLphi
Dominik Alfke, Weston Baines, Jan Blechschmidt +24
We present a novel technique based on deep learning and set theory which yields exceptional classification and prediction results. Having access to a sufficiently large amount of l…
Forman's Ricci curvature - From networks to hypernetworks
Emil Saucan, Melanie Weber
Networks and their higher order generalizations, such as hypernetworks or multiplex networks are ever more popular models in the applied sciences. However, methods developed for th…
Heuristic Framework for Multi-Scale Testing of the Multi-Manifold Hypothesis
F. Patricia Medina, Linda Ness, Melanie Weber +1
When analyzing empirical data, we often find that global linear models overestimate the number of parameters required. In such cases, we may ask whether the data lies on or near a…