44 citations · 63 across the 6 of their papers we have counts for
6 papers
Query-Adaptive Predictive Inference with Partial Labels
Maxime Cauchois, John Duchi
The cost and scarcity of fully supervised labels in statistical machine learning encourage using partially labeled data for model validation as a cheaper and more accessible altern…
Predictive Inference with Weak Supervision
Maxime Cauchois, Suyash Gupta, Alnur Ali +1
The expense of acquiring labels in large-scale statistical machine learning makes partially and weakly-labeled data attractive, though it is not always apparent how to leverage suc…
The Lifecycle of a Statistical Model: Model Failure Detection, Identification, and Refitting
Alnur Ali, Maxime Cauchois, John C. Duchi
The statistical machine learning community has demonstrated considerable resourcefulness over the years in developing highly expressive tools for estimation, prediction, and infere…
A comment and erratum on "Excess Optimism: How Biased is the Apparent Error of an Estimator Tuned by SURE?"
Maxime Cauchois, Alnur Ali, John Duchi
We identify and correct an error in the paper "Excess Optimism: How Biased is the Apparent Error of an Estimator Tuned by SURE?" This correction allows new guarantees on the excess…
Robust Validation: Confident Predictions Even When Distributions Shift
Maxime Cauchois, Suyash Gupta, Alnur Ali +1
While the traditional viewpoint in machine learning and statistics assumes training and testing samples come from the same population, practice belies this fiction. One strategy --…
Knowing what you know: valid and validated confidence sets in multiclass and multilabel prediction
Maxime Cauchois, Suyash Gupta, John Duchi
We develop conformal prediction methods for constructing valid predictive confidence sets in multiclass and multilabel problems without assumptions on the data generating distribut…