3 papers
cs.LG2026
Locally Adaptive Multi-Objective Learning
Jivat Neet Kaur, Isaac Gibbs, Michael I. Jordan
We consider the general problem of learning a predictor that satisfies multiple objectives of interest simultaneously, a broad framework that captures a range of specific learning…
stat.ML2026
Calibrated Multi-Level Quantile Forecasting
Tiffany Ding, Isaac Gibbs, Ryan J. Tibshirani
We develop an online method that guarantees calibration of quantile forecasts at multiple quantile levels simultaneously. In this work, a sequence of quantile forecasts is said to…
cs.LG2025
Sample-Efficient Omniprediction for Proper Losses
Isaac Gibbs, Ryan J. Tibshirani
We consider the problem of constructing probabilistic predictions that lead to accurate decisions when employed by downstream users to inform actions. For a single decision maker,…