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statistical consistency

52 papers

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Co-occurring keywords

surrogate loss (94) binary classification (674) reproducing kernel hilbert space (334) statistical learning (350) density estimation (397) loss function (462) learning theory (518) model selection (454) convex optimization (1320) structured prediction (394)

Papers

Mitigating Underfitting in Learning to Defer with Consistent Losses AISTATS 2024
Progressive Entropic Optimal Transport Solvers NIPS 2024
TopP&R: Robust Support Estimation Approach for Evaluating Fidelity and Diversity in Generative Models NIPS 2023
Consistent Complementary-Label Learning via Order-Preserving Losses AISTATS 2023
On the Consistency of Maximum Likelihood Estimation of Probabilistic Principal Component Analysis NIPS 2023
Evading DeepFake Detectors via Adversarial Statistical Consistency CVPR 2023
Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates AISTATS 2022
Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences ICML 2021
Provably End-to-end Label-noise Learning without Anchor Points ICML 2021
Consistent Plug-in Classifiers for Complex Objectives and Constraints NIPS 2020
Robust Gradient-Based Markov Subsampling AAAI 2020
Consistent Structured Prediction with Max-Min Margin Markov Networks ICML 2020
The Buckley-Osthus model and the block preferential attachment model: statistical analysis and application ICML 2020
Robustness Guarantees for Density Clustering AISTATS 2019
Manifold Structured Prediction NIPS 2018
Locally Consistent Bayesian Network Scores for Multi-Relational Data IJCAI 2017
Conic Scan-and-Cover algorithms for nonparametric topic modeling NIPS 2017
Universal consistency and minimax rates for online Mondrian Forests NIPS 2017
On the Consistency of Quick Shift NIPS 2017
Modal-set estimation with an application to clustering AISTATS 2017
Anchor-Free Correlated Topic Modeling: Identifiability and Algorithm NIPS 2016
A General Framework for Consistency of Principal Component Analysis JMLR 2016
Graphons, mergeons, and so on! NIPS 2016
Active Learning from Imperfect Labelers NIPS 2016
Learning Theory for Distribution Regression JMLR 2016