28 citations · 39 across the 4 of their papers we have counts for
4 papers
AutoBalance: Optimized Loss Functions for Imbalanced Data
Mingchen Li, Xuechen Zhang, Christos Thrampoulidis +2
Imbalanced datasets are commonplace in modern machine learning problems. The presence of under-represented classes or groups with sensitive attributes results in concerns about gen…
Post-hoc Models for Performance Estimation of Machine Learning Inference
Xuechen Zhang, Samet Oymak, Jiasi Chen
Estimating how well a machine learning model performs during inference is critical in a variety of scenarios (for example, to quantify uncertainty, or to choose from a library of a…
On the Role of Dataset Quality and Heterogeneity in Model Confidence
Yuan Zhao, Jiasi Chen, Samet Oymak
Safety-critical applications require machine learning models that output accurate and calibrated probabilities. While uncalibrated deep networks are known to make over-confident pr…
Learning Feature Nonlinearities with Non-Convex Regularized Binned Regression
Samet Oymak, Mehrdad Mahdavi, Jiasi Chen
For various applications, the relations between the dependent and independent variables are highly nonlinear. Consequently, for large scale complex problems, neural networks and re…