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2020 – today
- 2024
[j3]Mario Beraha, Stefano Favaro, Matteo Sesia:
Random measure priors in Bayesian recovery from sketches. J. Mach. Learn. Res. 25: 249:1-249:53 (2024)- [c10]Xinmeng Huang, Shuo Li, Mengxin Yu, Matteo Sesia, Hamed Hassani, Insup Lee, Osbert Bastani, Edgar Dobriban:
Uncertainty in Language Models: Assessment through Rank-Calibration. EMNLP 2024: 284-312 - [c9]Yanfei Zhou, Lars Lindemann, Matteo Sesia:
Conformalized Adaptive Forecasting of Heterogeneous Trajectories. ICML 2024 - [c8]Yanfei Zhou, Matteo Sesia:
Conformal Classification with Equalized Coverage for Adaptively Selected Groups. NeurIPS 2024 - [i11]Yanfei Zhou, Lars Lindemann, Matteo Sesia:
Conformalized Adaptive Forecasting of Heterogeneous Trajectories. CoRR abs/2402.09623 (2024) - [i10]Xinmeng Huang, Shuo Li, Mengxin Yu, Matteo Sesia, Hamed Hassani, Insup Lee, Osbert Bastani, Edgar Dobriban:
Uncertainty in Language Models: Assessment through Rank-Calibration. CoRR abs/2404.03163 (2024) - [i9]Yanfei Zhou, Matteo Sesia:
Conformal Classification with Equalized Coverage for Adaptively Selected Groups. CoRR abs/2405.15106 (2024) - [i8]Matteo Sesia, Vladimir Svetnik:
Doubly Robust Conformalized Survival Analysis with Right-Censored Data. CoRR abs/2412.09729 (2024) - 2023
- [j2]Matteo Sesia, Stefano Favaro, Edgar Dobriban:
Conformal Frequency Estimation using Discrete Sketched Data with Coverage for Distinct Queries. J. Mach. Learn. Res. 24: 348:1-348:80 (2023) - [c7]Ziyi Liang, Yanfei Zhou, Matteo Sesia:
Conformal Inference is (almost) Free for Neural Networks Trained with Early Stopping. ICML 2023: 20810-20851 - [c6]Meshi Bashari, Amir Epstein, Yaniv Romano, Matteo Sesia:
Derandomized novelty detection with FDR control via conformal e-values. NeurIPS 2023 - [i7]Ziyi Liang, Yanfei Zhou, Matteo Sesia:
Conformal inference is (almost) free for neural networks trained with early stopping. CoRR abs/2301.11556 (2023) - [i6]Meshi Bashari, Amir Epstein, Yaniv Romano, Matteo Sesia:
Derandomized Novelty Detection with FDR Control via Conformal E-values. CoRR abs/2302.07294 (2023) - [i5]Matteo Sesia, Y. X. Rachel Wang, Xin Tong:
Adaptive conformal classification with noisy labels. CoRR abs/2309.05092 (2023) - [i4]Mario Beraha, Stefano Favaro, Matteo Sesia:
Frequency and cardinality recovery from sketched data: a novel approach bridging Bayesian and frequentist views. CoRR abs/2309.15408 (2023) - 2022
- [j1]Charmaine Chia, Matteo Sesia
, Chi-Sing Ho, Stefanie S. Jeffrey, Jennifer A. Dionne, Emmanuel J. Candès, Roger T. Howe:
Interpretable Classification of Bacterial Raman Spectra With Knockoff Wavelets. IEEE J. Biomed. Health Informatics 26(2): 740-748 (2022) - [c5]Nitai Fingerhut, Matteo Sesia, Yaniv Romano:
Coordinated Double Machine Learning. ICML 2022: 6499-6513 - [c4]Bat-Sheva Einbinder, Yaniv Romano, Matteo Sesia, Yanfei Zhou:
Training Uncertainty-Aware Classifiers with Conformalized Deep Learning. NeurIPS 2022 - [c3]Matteo Sesia, Stefano Favaro:
Conformal Frequency Estimation with Sketched Data. NeurIPS 2022 - [i3]Bat-Sheva Einbinder, Yaniv Romano, Matteo Sesia, Yanfei Zhou:
Training Uncertainty-Aware Classifiers with Conformalized Deep Learning. CoRR abs/2205.05878 (2022) - [i2]Nitai Fingerhut, Matteo Sesia, Yaniv Romano:
Coordinated Double Machine Learning. CoRR abs/2206.00885 (2022) - [i1]Ziyi Liang, Matteo Sesia, Wenguang Sun:
Integrative conformal p-values for powerful out-of-distribution testing with labeled outliers. CoRR abs/2208.11111 (2022) - 2021
- [c2]Matteo Sesia, Yaniv Romano:
Conformal Prediction using Conditional Histograms. NeurIPS 2021: 6304-6315 - 2020
- [c1]Yaniv Romano, Matteo Sesia, Emmanuel J. Candès:
Classification with Valid and Adaptive Coverage. NeurIPS 2020
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