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George H. Chen
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2020 – today
- 2024
- [j6]George H. Chen
, Linhong Li, Ren Zuo
, Amanda Coston
, Jeremy C. Weiss:
Neural topic models with survival supervision: Jointly predicting time-to-event outcomes and learning how clinical features relate. Artif. Intell. Medicine 154: 102898 (2024) - [j5]Emaad Manzoor
, George H. Chen, Dokyun Lee
, Michael D. Smith
:
Influence via Ethos: On the Persuasive Power of Reputation in Deliberation Online. Manag. Sci. 70(3): 1613-1634 (2024) - [c21]Yan Ju, Shu Hu, Shan Jia, George H. Chen, Siwei Lyu:
Improving Fairness in Deepfake Detection. WACV 2024: 4643-4653 - [i25]Hyewon Jeong, Sarah Jabbour, Yuzhe Yang, Rahul Thapa, Hussein Mozannar, William Jongwon Han, Nikita Mehandru, Michael Wornow, Vladislav Lialin, Xin Liu, Alejandro Lozano, Jiacheng Zhu, Rafal Dariusz Kocielnik, Keith Harrigian, Haoran Zhang, Edward Lee, Milos Vukadinovic, Aparna Balagopalan, Vincent Jeanselme, Katherine Matton, Ilker Demirel, Jason A. Fries, Parisa Rashidi, Brett K. Beaulieu-Jones, Xuhai Orson Xu, Matthew B. A. McDermott, Tristan Naumann, Monica Agrawal, Marinka Zitnik, Berk Ustun, Edward Choi, Kristen Yeom, Gamze Gürsoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang
, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo:
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR abs/2403.01628 (2024) - 2023
- [j4]Zheng Li, Yue Zhao
, Xiyang Hu, Nicola Botta, Cezar Ionescu, George H. Chen
:
ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions. IEEE Trans. Knowl. Data Eng. 35(12): 12181-12193 (2023) - [c20]George H. Chen:
A General Framework for Visualizing Embedding Spaces of Neural Survival Analysis Models Based on Angular Information. CHIL 2023: 440-476 - [c19]Shahriar Noroozizadeh, Jeremy C. Weiss, George H. Chen:
Temporal Supervised Contrastive Learning for Modeling Patient Risk Progression. ML4H@NeurIPS 2023: 403-427 - [c18]Xiaobin Shen, Jonathan Elmer, George H. Chen:
Neurological Prognostication of Post-Cardiac-Arrest Coma Patients Using EEG Data: A Dynamic Survival Analysis Framework with Competing Risks. MLHC 2023: 667-690 - [i24]George H. Chen:
A General Framework for Visualizing Embedding Spaces of Neural Survival Analysis Models Based on Angular Information. CoRR abs/2305.06862 (2023) - [i23]Yan Ju, Shu Hu, Shan Jia, George H. Chen, Siwei Lyu:
Improving Fairness in Deepfake Detection. CoRR abs/2306.16635 (2023) - [i22]Xiaobin Shen, Jonathan Elmer, George H. Chen:
Neurological Prognostication of Post-Cardiac-Arrest Coma Patients Using EEG Data: A Dynamic Survival Analysis Framework with Competing Risks. CoRR abs/2308.11645 (2023) - [i21]Shahriar Noroozizadeh, Jeremy C. Weiss, George H. Chen:
Temporal Supervised Contrastive Learning for Modeling Patient Risk Progression. CoRR abs/2312.05933 (2023) - 2022
- [j3]Yue Zhao, George H. Chen, Zhihao Jia:
TOD: GPU-accelerated Outlier Detection via Tensor Operations. Proc. VLDB Endow. 16(3): 546-560 (2022) - [c17]Gerardo Flores, George H. Chen, Tom J. Pollard, Ayah Zirikly, Michael C. Hughes, Tasmie Sarker, Joyce C. Ho, Tristan Naumann:
Conference on Health, Inference, and Learning (CHIL) 2022. CHIL 2022: 1-4 - [c16]Shu Hu, George H. Chen:
Distributionally Robust Survival Analysis: A Novel Fairness Loss Without Demographics. ML4H@NeurIPS 2022: 62-87 - [c15]Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu:
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs. NeurIPS 2022 - [e1]Gerardo Flores, George H. Chen, Tom J. Pollard, Joyce C. Ho, Tristan Naumann:
Conference on Health, Inference, and Learning, CHIL 2022, 7-8 April 2022, Virtual Event. Proceedings of Machine Learning Research 174, PMLR 2022 [contents] - [i20]Zheng Li, Yue Zhao, Xiyang Hu, Nicola Botta, Cezar Ionescu, George H. Chen:
ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions. CoRR abs/2201.00382 (2022) - [i19]Kay Liu
, Yingtong Dou, Yue Zhao, Xueying Ding
, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, George H. Chen, Zhihao Jia, Philip S. Yu:
PyGOD: A Python Library for Graph Outlier Detection. CoRR abs/2204.12095 (2022) - [i18]Gerardo Flores, George H. Chen, Tom J. Pollard, Joyce C. Ho, Tristan Naumann:
A collection of invited non-archival papers for the Conference on Health, Inference, and Learning (CHIL) 2022. CoRR abs/2205.02752 (2022) - [i17]Kay Liu
, Yingtong Dou, Yue Zhao, Xueying Ding
, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu:
Benchmarking Node Outlier Detection on Graphs. CoRR abs/2206.10071 (2022) - [i16]George H. Chen:
Survival Kernets: Scalable and Interpretable Deep Kernel Survival Analysis with an Accuracy Guarantee. CoRR abs/2206.10477 (2022) - [i15]Shu Hu, George H. Chen:
Distributionally Robust Survival Analysis: A Novel Fairness Loss Without Demographics. CoRR abs/2211.10508 (2022) - 2021
- [c14]Wen Wang, Han Zhao, Dokyun Lee, George H. Chen:
Machine Learning for Consumers and Markets. KDD 2021: 4165-4166 - [i14]Yue Zhao
, George H. Chen, Zhihao Jia:
TOD: Tensor-based Outlier Detection. CoRR abs/2110.14007 (2021) - 2020
- [c13]Helen Zhou
, Cheng Cheng
, Zachary C. Lipton
, George H. Chen
, Jeremy C. Weiss
:
Mortality Risk Score for Critically Ill Patients with Viral or Unspecified Pneumonia: Assisting Clinicians with COVID-19 ECMO Planning. AIME 2020: 336-347 - [c12]Linhong Li
, Ren Zuo
, Amanda Coston
, Jeremy C. Weiss
, George H. Chen
:
Neural Topic Models with Survival Supervision: Jointly Predicting Time-to-Event Outcomes and Learning How Clinical Features Relate. AIME 2020: 371-381 - [c11]George H. Chen:
Deep Kernel Survival Analysis and Subject-Specific Survival Time Prediction Intervals. MLHC 2020: 537-565 - [i13]Emaad A. Manzoor, George H. Chen, Dokyun Lee, Michael D. Smith:
Influence via Ethos: On the Persuasive Power of Reputation in Deliberation Online. CoRR abs/2006.00707 (2020) - [i12]Helen Zhou, Cheng Cheng, Zachary C. Lipton, George H. Chen, Jeremy C. Weiss:
Predicting Mortality Risk in Viral and Unspecified Pneumonia to Assist Clinicians with COVID-19 ECMO Planning. CoRR abs/2006.01898 (2020) - [i11]Linhong Li, Ren Zuo, Amanda Coston, Jeremy C. Weiss, George H. Chen:
Neural Topic Models with Survival Supervision: Jointly Predicting Time-to-Event Outcomes and Learning How Clinical Features Relate. CoRR abs/2007.07796 (2020) - [i10]George H. Chen:
Deep Kernel Survival Analysis and Subject-Specific Survival Time Prediction Intervals. CoRR abs/2007.12975 (2020)
2010 – 2019
- 2019
- [c10]Lynn H. Kaack, George H. Chen, M. Granger Morgan:
Truck traffic monitoring with satellite images. COMPASS 2019: 155-164 - [c9]George H. Chen:
Nearest Neighbor and Kernel Survival Analysis: Nonasymptotic Error Bounds and Strong Consistency Rates. ICML 2019: 1001-1010 - [c8]Wei Ma
, Kendall Nowocin, Niraj Marathe, George H. Chen:
An interpretable produce price forecasting system for small and marginal farmers in India using collaborative filtering and adaptive nearest neighbors. ICTD 2019: 6:1-6:11 - [c7]Wei Ma, George H. Chen:
Missing Not at Random in Matrix Completion: The Effectiveness of Estimating Missingness Probabilities Under a Low Nuclear Norm Assumption. NeurIPS 2019: 14871-14880 - [i9]George H. Chen:
Nearest Neighbor and Kernel Survival Analysis: Nonasymptotic Error Bounds and Strong Consistency Rates. CoRR abs/1905.05285 (2019) - [i8]Lynn H. Kaack, George H. Chen, M. Granger Morgan:
Truck Traffic Monitoring with Satellite Images. CoRR abs/1907.07660 (2019) - [i7]Wei Ma, George H. Chen:
Missing Not at Random in Matrix Completion: The Effectiveness of Estimating Missingness Probabilities Under a Low Nuclear Norm Assumption. CoRR abs/1910.12774 (2019) - 2018
- [j2]George H. Chen, Devavrat Shah:
Explaining the Success of Nearest Neighbor Methods in Prediction. Found. Trends Mach. Learn. 10(5-6): 337-588 (2018) - [i6]Wei Ma, Kendall Nowocin, Niraj Marathe, George H. Chen:
An Interpretable Produce Price Forecasting System for Small and Marginal Farmers in India using Collaborative Filtering and Adaptive Nearest Neighbors. CoRR abs/1812.05173 (2018) - 2017
- [c6]George H. Chen, Kendall Nowocin, Niraj Marathe:
Toward Reducing Crop Spoilage and Increasing Small Farmer Profits in India: a Simultaneous Hardware and Software Solution. ICTD 2017: 37:1-37:5 - [i5]George H. Chen, Kendall Nowocin, Niraj Marathe:
Toward Reducing Crop Spoilage and Increasing Small Farmer Profits in India: a Simultaneous Hardware and Software Solution. CoRR abs/1710.10515 (2017) - 2015
- [b1]George H. Chen:
Latent source models for nonparametric inference. Massachusetts Institute of Technology, Cambridge, MA, USA, 2015 - [j1]Kush R. Varshney, George H. Chen, Brian Abelson, Kendall Nowocin, Vivek Sakhrani, Ling Xu, Brian L. Spatocco:
Targeting Villages for Rural Development Using Satellite Image Analysis. Big Data 3(1): 41-53 (2015) - [c5]George H. Chen, Devavrat Shah, Polina Golland:
A Latent Source Model for Patch-Based Image Segmentation. MICCAI (3) 2015: 140-148 - [i4]George H. Chen, Devavrat Shah, Polina Golland:
A Latent Source Model for Patch-Based Image Segmentation. CoRR abs/1510.01648 (2015) - 2014
- [c4]Guy Bresler, George H. Chen, Devavrat Shah:
A Latent Source Model for Online Collaborative Filtering. NIPS 2014: 3347-3355 - [i3]Guy Bresler, George H. Chen, Devavrat Shah:
A Latent Source Model for Online Collaborative Filtering. CoRR abs/1411.6591 (2014) - 2013
- [c3]George H. Chen, Christian Wachinger
, Polina Golland:
Sparse Projections of Medical Images onto Manifolds. IPMI 2013: 292-303 - [c2]George H. Chen, Stanislav Nikolov, Devavrat Shah:
A Latent Source Model for Nonparametric Time Series Classification. NIPS 2013: 1088-1096 - [i2]George H. Chen, Stanislav Nikolov, Devavrat Shah:
A Latent Source Model for Online Time Series Classification. CoRR abs/1302.3639 (2013) - [i1]George H. Chen, Christian Wachinger, Polina Golland:
Sparse Projections of Medical Images onto Manifolds. CoRR abs/1303.5508 (2013) - 2011
- [c1]George H. Chen, Evelina Fedorenko, Nancy Kanwisher, Polina Golland:
Deformation-Invariant Sparse Coding for Modeling Spatial Variability of Functional Patterns in the Brain. MLINI 2011: 68-75
Coauthor Index
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last updated on 2024-08-16 18:33 CEST by the dblp team
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