Add to ORKGModern deep learning based classifiers show very high accuracy on test data but this does not provide sufficient guarantees for safe deployment, especially in high-stake AI applications such as medical diagnosis. Usually, predictions are obtained without a reliable uncertainty estimate or a formal guarantee. Conformal prediction (CP) addresses these issues by using the classifier's predictions, e.g., its probability estimates, to predict confidence sets containing the true class with a user-specified probability. However, using CP as a separate processing step after training prevents the underlying model from adapting to the prediction of confidence sets. Thus, this paper explores strategies to differentiate through CP during training with ...
We extend conformal prediction to control the expected value of any monotone loss function. The algo...
The talk reviews a modern machine learning technique called Conformal Predictors. The approach has b...
Conformal prediction is a new framework producingregion predictions with a guaranteed error rate. In...
Deep neural networks are powerful tools to detect hidden patterns in data and leverage them to make ...
Conformal prediction (CP) generates a set of predictions for a given test sample such that the predi...
Safe deployment of deep neural networks in high-stake real-world applications require theoretically ...
Deep Learning predictions with measurable confidence are increasingly desirable for real-world probl...
Conformal prediction has emerged as a rigorous means of providing deep learning models with reliable...
When one observes a sequence of variables $(x_1, y_1), \ldots, (x_n, y_n)$, Conformal Prediction (CP...
Quantifying the data uncertainty in learning tasks is often done by learning a prediction interval o...
Conformal prediction is a learning framework that produces models that associate witheach of their p...
Conformal prediction (CP) is a wrapper around traditional machine learning models, giving coverage g...
Conformal prediction is a learning framework that produces models that associate with each of their ...
Modern image classifiers achieve high predictive accuracy, but the predictions typically come withou...
Conformal prediction is a statistical-learning framework that complements predictions with a reliabl...
We extend conformal prediction to control the expected value of any monotone loss function. The algo...
The talk reviews a modern machine learning technique called Conformal Predictors. The approach has b...
Conformal prediction is a new framework producingregion predictions with a guaranteed error rate. In...
Deep neural networks are powerful tools to detect hidden patterns in data and leverage them to make ...
Conformal prediction (CP) generates a set of predictions for a given test sample such that the predi...
Safe deployment of deep neural networks in high-stake real-world applications require theoretically ...
Deep Learning predictions with measurable confidence are increasingly desirable for real-world probl...
Conformal prediction has emerged as a rigorous means of providing deep learning models with reliable...
When one observes a sequence of variables $(x_1, y_1), \ldots, (x_n, y_n)$, Conformal Prediction (CP...
Quantifying the data uncertainty in learning tasks is often done by learning a prediction interval o...
Conformal prediction is a learning framework that produces models that associate witheach of their p...
Conformal prediction (CP) is a wrapper around traditional machine learning models, giving coverage g...
Conformal prediction is a learning framework that produces models that associate with each of their ...
Modern image classifiers achieve high predictive accuracy, but the predictions typically come withou...
Conformal prediction is a statistical-learning framework that complements predictions with a reliabl...
We extend conformal prediction to control the expected value of any monotone loss function. The algo...
The talk reviews a modern machine learning technique called Conformal Predictors. The approach has b...
Conformal prediction is a new framework producingregion predictions with a guaranteed error rate. In...
