Sangdon Park

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Insup LeeProfessor, Computer and Information Science, University of PennsylvaniaDirección de correo verificada de cis.upenn.edu
Osbert BastaniUniversity of PennsylvaniaDirección de correo verificada de seas.upenn.edu
Edgar DobribanStatistics & Computer Science, University of PennsylvaniaDirección de correo verificada de upenn.edu
Anirban RoySenior Scientist, SRI InternationalDirección de correo verificada de sri.com
Ramneet KaurAdvanced Computer Scientist, SRIDirección de correo verificada de sri.com
Oleg SokolskyUniversity of PennsylvaniaDirección de correo verificada de cis.upenn.edu
Susmit JhaDirector, Neurosymbolic Computing and Intelligence, SRI InternationalDirección de correo verificada de sri.com
Shuo LiPh.D. Candidate, University of PennsylvaniaDirección de correo verificada de seas.upenn.edu
James WeimerVanderbilt UniversityDirección de correo verificada de vanderbilt.edu
Nikolai MatniAssistant Professor of Electrical and Systems Engineering, University of PennsylvaniaDirección de correo verificada de seas.upenn.edu
Sooyong JangUniversity of PennsylvaniaDirección de correo verificada de seas.upenn.edu
Kaustubh SridharUniversity of PennsylvaniaDirección de correo verificada de seas.upenn.edu
Taesoo KimGeorgia Institute of TechnologyDirección de correo verificada de gatech.edu
Kyoung Mu LeeProfessor, Department of Electrical and Computer Engineering, Seoul National UniversityDirección de correo verificada de snu.ac.kr
Wonsik KimGoogleDirección de correo verificada de google.com
Yiannis KantarosAssistant Professor, Washington University in St. LouisDirección de correo verificada de wustl.edu
Xiayan JiUniversity of PennsylvaniaDirección de correo verificada de seas.upenn.edu

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Sangdon Park

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Trustworthy AI Machine Learning Computer Security Cyber-Physical Systems


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction S Park, O Bastani, N Matni, I Lee International Conference on Learning Representations (ICLR), 2020	72	2020
Calibrated Predictions with Covariate Shift via Unsupervised Domain Adaptation S Park, O Bastani, J Weimer, I Lee International Conference on Artificial Intelligence and Statistics (AISTATS), 2020	60	2020
iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detection R Kaur, S Jha, A Roy, S Park, E Dobriban, O Sokolsky, I Lee Association for the Advancement of Artificial Intelligence (AAAI), 2022	53	2022
PAC Prediction Sets Under Covariate Shift S Park, E Dobriban, I Lee, O Bastani International Conference on Learning Representations (ICLR), 2022	43	2022
PAC Confidence Predictions for Deep Neural Network Classifiers S Park, S Li, I Lee, O Bastani International Conference on Learning Representations (ICLR), 2021	34	2021
Integrated intelligence for human-robot teams J Oh, TM Howard, MR Walter, D Barber, M Zhu, S Park, A Suppe, ... International Symposium on Experimental Robotics (ISER), 309-322, 2016	30	2016
CODiT: Conformal Out-of-Distribution Detection in Time-Series Data for Cyber-Physical Systems R Kaur, K Sridhar, S Park, Y Yang, S Jha, A Roy, O Sokolsky, I Lee Proceedings of the ACM/IEEE 14th International Conference on Cyber-Physical …, 2023	26*	2023
Detecting oods as datapoints with high uncertainty R Kaur, S Jha, A Roy, S Park, O Sokolsky, I Lee arXiv preprint arXiv:2108.06380, 2021	17	2021
Abnormal object detection by canonical scene-based contextual model S Park, W Kim, KM Lee European Conference on Computer Vision (ECCV), 2012	17	2012
PAC Prediction Sets for Meta-Learning S Park, E Dobriban, I Lee, O Bastani Neural Information Processing Systems (NeurIPS), 2022	15	2022
VisionGuard: Runtime detection of adversarial inputs to perception systems Y Kantaros, T Carpenter, S Park, R Ivanov, S Jang, I Lee, J Weimer arXiv preprint arXiv:2002.09792, 2020	14	2020
TRAQ: Trustworthy Retrieval Augmented Question Answering via Conformal Prediction S Li, S Park, I Lee, O Bastani Proceedings of the 2024 Conference of the North American Chapter of the …, 2024	13*	2024
Sequential Covariate Shift Detection Using Classifier Two-Sample Tests S Jang, S Park, I Lee, O Bastani International Conference on Machine Learning (ICML), 9845-9880, 2022	13	2022
PAC Prediction Sets Under Label Shift W Si, S Park, I Lee, E Dobriban, O Bastani arXiv preprint arXiv:2310.12964, 2023	9	2023
Resilient linear classification: an approach to deal with attacks on training data S Park, J Weimer, I Lee International Conference on Cyber-Physical Systems (ICCPS), 2017	9	2017
US army research laboratory (ARL) robotics collaborative technology alliance 2014 capstone experiment M Childers, C Lennon, B Bodt, J Pusey, S Hill, R Camden, J Oh, R Dean, ... US Army Research Laboratory Aberdeen Proving Ground United States, 2016	9	2016
Angelic Patches for Improving Third-Party Object Detector Performance W Si, S Li, S Park, I Lee, O Bastani Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023	7	2023
MedBN: Robust Test-Time Adaptation against Malicious Test Samples H Park, J Hwang, S Mun, S Park, J Ok IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 5997-6007, 2024	6	2024
ACon: Adaptive Conformal Consensus for Provable Blockchain Oracles S Park, O Bastani, T Kim USENIX Security Symposium (Security), 2023	5	2023
Towards PAC Multi-Object Detection and Tracking S Li, S Park, X Ji, I Lee, O Bastani arXiv preprint arXiv:2204.07482, 2022	5	2022

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