probabilistic classifier

FROC: Building Fair ROC from a Trained Classifier AAAI 2025 I-trustworthy Models. A framework for trustworthiness evaluation of probabilistic classifiers AISTATS 2025 Wrapped Gaussian on the manifold of Symmetric Positive Definite Matrices ICML 2025 Towards Unbiased Exploration in Partial Label Learning JMLR 2024 On the Calibration of Probabilistic Classifier Sets AISTATS 2023 On the Role of Randomization in Adversarially Robust Classification NeurIPS 2023 Probabilistic Multi-Dimensional Classification UAI 2023 A Consistent and Differentiable Lp Canonical Calibration Error Estimator NeurIPS 2022 Beyond Adult and COMPAS: Fair Multi-Class Prediction via Information Projection NeurIPS 2022 Rashomon Capacity: A Metric for Predictive Multiplicity in Classification NeurIPS 2022 The Hitchhiker's Guide to Prior-Shift Adaptation WACV 2022 Decision-Making Under Selective Labels: Optimal Finite-Domain Policies and Beyond ICML 2021 PopSkipJump: Decision-Based Attack for Probabilistic Classifiers ICML 2021 The Emergence of Individuality ICML 2021 Approximating bounded tree-width Bayesian network classifiers with OBDD PGM 2020 Neural Methods for Point-wise Dependency Estimation NeurIPS 2020 New Off-Board Solution for Predicting Vehicles' Intentions in the Highway On-Ramp Using Probabilistic Classifiers (Student Abstract) AAAI 2020 Bayesian Combination of Probabilistic Classifiers using Multivariate Normal Mixtures JMLR 2019 Classification-by-Components: Probabilistic Modeling of Reasoning over a Set of Components NeurIPS 2019 Complementary Sum Sampling for Likelihood Approximation in Large Scale Classification AISTATS 2017 Optimal Feature Selection for Decision Robustness in Bayesian Networks IJCAI 2017 Bayesian Torrent Classification by File Name and Size Only PGM 2016 Robust Classification Under Sample Selection Bias NeurIPS 2014 Confidence-Weighted Linear Classification for Text Categorization JMLR 2012