Search Results for author: Maxime Cauchois

Found 5 papers, 0 papers with code

Query-Adaptive Predictive Inference with Partial Labels

no code implementations15 Jun 2022 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 alternative.

Structured Prediction

The Lifecycle of a Statistical Model: Model Failure Detection, Identification, and Refitting

no code implementations8 Feb 2022 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 inference.

Time Series Time Series Analysis

Predictive Inference with Weak Supervision

no code implementations20 Jan 2022 Maxime Cauchois, Suyash Gupta, Alnur Ali, John Duchi

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 such data for model fitting or validation.

Conformal Prediction Structured Prediction +1

Robust Validation: Confident Predictions Even When Distributions Shift

no code implementations10 Aug 2020 Maxime Cauchois, Suyash Gupta, Alnur Ali, John C. Duchi

One strategy -- coming from robust statistics and optimization -- is thus to build a model robust to distributional perturbations.

valid

Knowing what you know: valid and validated confidence sets in multiclass and multilabel prediction

no code implementations21 Apr 2020 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 distribution.

Conformal Prediction valid

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