A Self-boosted Framework for Calibrated Ranking.pdf
Attended Temperature Scaling - A Practical Approach for Calibrating Deep Neural Networks.pdf
Beta calibration - a well-founded and easily implemented improvement on logistic calibration for binary classifiers.pdf
Beyond temperature scaling - Obtaining well-calibrated multiclass probabilities with Dirichlet calibration.pdf
CALIBRATION OF NEURAL NETWORKS USING SPLINES.pdf
Calibrating User Response Predictions in Online Advertising.pdf
Crank up the volume - preference bias amplificationin collaborative recommendation.pdf
Deep Ensemble Shape Calibration - Multi-Field Post-hoc Calibration in Online Advertising.pdf
Distribution-free calibration guarantees for histogram binning without sample splitting.pdf
Field-aware Calibration - A Simple and Empirically Strong Method for Reliable Probabilistic Predictions.pdf
MBCT - Tree-Based Feature-Aware Binning for Individual Uncertainty Calibration.pdf
Measuring Calibration in Deep Learning.pdf
Mitigating Bias in Calibration Error Estimation.pdf
Obtaining Well Calibrated Probabilities Using Bayesian Binning.pdf
Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers.pdf
On Calibration of Modern Neural Networks.pdf
Posterior Probability Matters - Doubly-Adaptive Calibration for Neural Predictions in Online Advertising.pdf
Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods.pdf
Regression Compatible Listwise Objectives for Calibrated Ranking with Binary Relevance.pdf
Transforming Classifier Scores into Accurate Multiclass Probability Estimates.pdf
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