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PAC Prediction Sets for Meta-Learning


Jul 06, 2022
Sangdon Park, Edgar Dobriban, Insup Lee, Osbert Bastani


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Unified Fourier-based Kernel and Nonlinearity Design for Equivariant Networks on Homogeneous Spaces


Jun 19, 2022
Yinshuang Xu, Jiahui Lei, Edgar Dobriban, Kostas Daniilidis

* Accepted at ICML2022 Thirty-ninth International Conference on Machine Learning 

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Pursuit of a Discriminative Representation for Multiple Subspaces via Sequential Games


Jun 18, 2022
Druv Pai, Michael Psenka, Chih-Yuan Chiu, Manxi Wu, Edgar Dobriban, Yi Ma

* main body is 10 pages and has 4 figures; appendix is 18 pages and has 17 figures; submitted for review at NeurIPS 2022 

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Memory Classifiers: Two-stage Classification for Robustness in Machine Learning


Jun 10, 2022
Souradeep Dutta, Yahan Yang, Elena Bernardis, Edgar Dobriban, Insup Lee


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Collaborative Learning of Distributions under Heterogeneity and Communication Constraints


Jun 07, 2022
Xinmeng Huang, Donghwan Lee, Edgar Dobriban, Hamed Hassani


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PAC-Wrap: Semi-Supervised PAC Anomaly Detection


May 22, 2022
Shuo Li, Xiayan Ji, Edgar Dobriban, Oleg Sokolsky, Insup Lee

* Accepted by SIGKDD 2022 

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Fair Bayes-Optimal Classifiers Under Predictive Parity


May 15, 2022
Xianli Zeng, Edgar Dobriban, Guang Cheng


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SE(3)-Equivariant Attention Networks for Shape Reconstruction in Function Space


Apr 05, 2022
Evangelos Chatzipantazis, Stefanos Pertigkiozoglou, Edgar Dobriban, Kostas Daniilidis


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T-Cal: An optimal test for the calibration of predictive models


Mar 25, 2022
Donghwan Lee, Xinmeng Huang, Hamed Hassani, Edgar Dobriban

* The implementation of T-Cal is available at https://github.com/dh7401/T-Cal 

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Distribution-free Prediction Sets Adaptive to Unknown Covariate Shift


Mar 11, 2022
Hongxiang Qiu, Edgar Dobriban, Eric Tchetgen Tchetgen


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