정유립
1. Kearns et al. – Preventing Fairness Gerrymandering
이경선
3. Kearns et al. – An Empirical Study of Rich Subgroup Fairness for Machine Learning
신윤섭
2. Gohar and Cheng – A Survey on Intersectional Fairness
정한교
4. Molina and Loiseau – Bounding and Approximating Intersectional Fairness
김초은
Fair AI platform
Palantir
ResAD: A Simple Framework for Class Generalizable Anomaly Detection
이지후
TabPFN
Training Unbiased Diffusion Models from Biased Dataset
Deep research
Label-free CBM
이성은
Prompt Engineering
박세현
Deepseek-R1 PPT
박석훈
XBART
Stable Conformal Prediction sets – 2022 ICML
Derandomized novelty detection with FDR control via conformal e-values – 2023 NeurIPS
박진원
Conformalized fairness via quantile regression – 2022 NeurIPS
Improving Expert Predictions with Conformal Prediction – ICML 2023
Improving Uncertainty Quanitifcaion of Deep Classifiers via Neighborhood Conformal Prediction – AAAI 2023
안영민
Class-conditional conformal prediction with many classes – 2023 NeurIPS
김건웅
Conformal Prediction with Large Language Models for Multi-choice Question Answering – ICML 2023 workshop
정휘창
Conformal Prediction with Missing Values – 2023 ICML
Conformal Prediciton via Regression-as-classification – 2024 ICLR
박찬무
Testing for outliers with conformal p-values – 2023 Annals
Verifiably Robust Conformal Prediction – 2024 NeurIPS
최성식
Conformal meta-learners for predictive inference of individual treatment effects. – 2024 NeurIPS
Conformal Prediction for Deep Classifier via Label Ranking – 2024 ICML
이해영
Conformal Language Modeling – 2024 ICLR
An Information Theoretic Perspective on Conformal Prediction – 2024 NeurIPS
Large language model validity via enhanced conformal prediction methods – 2024 NeurIPS
세미나 자료
ML-Section1
ML-Section2
ML-Section3
ML-Section4
ML-Section5
Localization_Analysis.pdf
