Regression
Errors-in-variables Fréchet Regression with Low-rank Covariate Approximation
Fréchet regression has emerged as a promising approach for regression analysis involving non-Euclidean response variables.
Stratified Prediction-Powered Inference for Hybrid Language Model Evaluation Adam Fisch, Joshua Maynez, R. Alex Hofer Bhuwan Dhingra Amir Globerson William W. Cohen
Evaluating machine learning models requires evaluation data.
New Bounds for Hyperparameter Tuning of Regression Problems Across Instances
In this work, we investigate an alternative setting for tuning regularization parameters, namely data-driven algorithm design, following the previous line of work by Balcan et al. [
Self-Calibrating Conformal Prediction
In machine learning, model calibration and predictive inference are essential for producing reliable predictions and quantifying uncertainty to support decision-making.
SMF_NeurIPS_2023-6
Our framework applies to a wide range of SMF-type problems for multi-class classification with auxiliary features.
