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Journal Articles
- 2024
[j13]Xiaotong Jiang
, Xin Zhou, Michael R. Kosorok:
Deep doubly robust outcome weighted learning. Mach. Learn. 113(2): 815-842 (2024)- [j12]Fei Yu, Helal El-Zaatari, Michael R. Kosorok, Andrea Carnegie, Gaurav Dave:
The application of exponential random graph models to collaboration networks in biomedical and health sciences: a review. Netw. Model. Anal. Health Informatics Bioinform. 13(1): 5 (2024) - 2022
- [j11]Hunyong Cho, Nicholas P. Jewell, Michael R. Kosorok:
Interval Censored Recursive Forests. J. Comput. Graph. Stat. 31(1): 390-402 (2022) - [j10]Teeranan Pokaprakarn, Rebecca Kitzmiller, J. Randall Moorman, Douglas E. Lake, Ashok Kumar Krishnamurthy, Michael R. Kosorok:
Sequence to Sequence ECG Cardiac Rhythm Classification Using Convolutional Recurrent Neural Networks. IEEE J. Biomed. Health Informatics 26(2): 572-580 (2022) - 2021
- [j9]Jingxiang Chen, Quoc Tran-Dinh, Michael R. Kosorok, Yufeng Liu:
Identifying Heterogeneous Effect Using Latent Supervised Clustering With Adaptive Fusion. J. Comput. Graph. Stat. 30(1): 43-54 (2021) - [j8]Daniel J. Luckett, Eric B. Laber, Siyeon Kim, Michael R. Kosorok:
Estimation and Optimization of Composite Outcomes. J. Mach. Learn. Res. 22: 167:1-167:40 (2021) - 2020
- [j7]Akram Yazdani, Raul Mendez-Giraldez, Azam Yazdani, Michael R. Kosorok, Panos Roussos:
Differential gene regulatory pattern in the human brain from schizophrenia using transcriptomic-causal network. BMC Bioinform. 21(1): 469 (2020) - [j6]John Sperger, Nikki L. B. Freeman, Xiaotong Jiang, David Bang, Daniel de Marchi, Michael R. Kosorok:
The future of precision health is data-driven decision support. Stat. Anal. Data Min. 13(6): 537-543 (2020) - 2018
- [j5]Sebastian J. Teran Hidalgo, Michael C. Wu, Stephanie M. Engel, Michael R. Kosorok:
Goodness-of-fit test for nonparametric regression models: Smoothing spline ANOVA models as example. Comput. Stat. Data Anal. 122: 135-155 (2018) - 2016
- [j4]Guanhua Chen, Yufeng Liu, Dinggang Shen, Michael R. Kosorok:
Composite large margin classifiers with latent subclasses for heterogeneous biomedical data. Stat. Anal. Data Min. 9(2): 75-88 (2016) - 2010
- [j3]Shuangge Ma, Michael R. Kosorok:
Detection of gene pathways with predictive power for breast cancer prognosis. BMC Bioinform. 11: 1 (2010) - 2009
- [j2]Shuangge Ma, Michael R. Kosorok:
Identification of differential gene pathways with principal component analysis. Bioinform. 25(7): 882-889 (2009) - [j1]Guang Cheng, Michael R. Kosorok:
The penalized profile sampler. J. Multivar. Anal. 100(3): 345-362 (2009)
Conference and Workshop Papers
- 2023
- [c3]Joshua P. Zitovsky, Daniel de Marchi, Rishabh Agarwal, Michael Rene Kosorok:
Revisiting Bellman Errors for Offline Model Selection. ICML 2023: 43369-43406 - 2020
- [c2]Liangyu Zhu, Wenbin Lu, Michael R. Kosorok, Rui Song:
Kernel Assisted Learning for Personalized Dose Finding. KDD 2020: 56-65 - 2019
- [c1]Tarek M. Zikry, Katarzyna M. Kedziora, Michael R. Kosorok, Jeremy E. Purvis:
In and out of the nucleus: CNN based segmentation of cell nuclei from images of a translocating sensor. PEARC 2019: 70:1-70:4
Parts in Books or Collections
- 2016
- [p1]Sebastian J. Teran Hidalgo, Michael T. Lawson, Daniel J. Luckett, Monica Chaudhari, Jingxiang Chen, Arkopal Choudhury, Arianna Di Florio, Xiaotong Jiang, Crystal T. Nguyen, Michael R. Kosorok:
A Master Pipeline for Discovery and Validation of Biomarkers. Machine Learning for Health Informatics 2016: 259-288
Informal and Other Publications
- 2023
- [i12]Daniel de Marchi, Matthew Welch, Michael R. Kosorok:
A Robust Hypothesis Test for Tree Ensemble Pruning. CoRR abs/2301.10115 (2023) - [i11]Joshua P. Zitovsky, Daniel de Marchi, Rishabh Agarwal, Michael R. Kosorok:
Revisiting Bellman Errors for Offline Model Selection. CoRR abs/2302.00141 (2023) - [i10]Joshua P. Zitovsky, Leslie Wilson, Michael R. Kosorok:
A Flexible Framework for Incorporating Patient Preferences Into Q-Learning. CoRR abs/2307.12022 (2023) - [i9]Helal El-Zaatari, Fei Yu, Michael R. Kosorok:
Stochastic Step-wise Feature Selection for Exponential Random Graph Models (ERGMs). CoRR abs/2307.12862 (2023) - 2022
- [i8]Carlos García-Meixide, Marcos Matabuena, Michael R. Kosorok:
Neural interval-censored Cox regression with feature selection. CoRR abs/2206.06885 (2022) - [i7]Zuyue Fu, Zhengling Qi, Zhaoran Wang, Zhuoran Yang, Yanxun Xu, Michael R. Kosorok:
Offline Reinforcement Learning with Instrumental Variables in Confounded Markov Decision Processes. CoRR abs/2209.08666 (2022) - 2020
- [i6]Yifan Cui, Michael R. Kosorok, Stefan Wager, Ruoqing Zhu:
Estimating heterogeneous treatment effects with right-censored data via causal survival forests. CoRR abs/2001.09887 (2020) - [i5]Xiaotong Jiang, Amanda E. Nelson, Rebecca J. Cleveland, Daniel P. Beavers, Todd A. Schwartz, Liubov Arbeeva, Carolina Alvarez, Leigh F. Callahan, Stephen Messier, Richard Loeser, Michael R. Kosorok:
Technical Background for "A Precision Medicine Approach to Develop and Internally Validate Optimal Exercise and Weight Loss Treatments for Overweight and Obese Adults with Knee Osteoarthritis". CoRR abs/2001.09930 (2020) - [i4]Arkopal Choudhury, Michael R. Kosorok:
Missing Data Imputation for Classification Problems. CoRR abs/2002.10709 (2020) - 2019
- [i3]Crystal T. Nguyen, Daniel J. Luckett, Anna R. Kahkoska, Grace E. Shearrer, Donna Spruijt-Metz, Jaimie N. Davis, Michael R. Kosorok:
Estimating Individualized Treatment Regimes from Crossover Designs. CoRR abs/1902.05499 (2019) - [i2]Naim U. Rashid, Daniel J. Luckett, Jingxiang Chen, Michael T. Lawson, Longshaokan Wang, Yunshu Zhang, Eric B. Laber, Yufeng Liu, Jen Jen Yeh, Donglin Zeng, Michael R. Kosorok:
High dimensional precision medicine from patient-derived xenografts. CoRR abs/1912.06667 (2019) - 2018
- [i1]Daniel J. Luckett, Eric B. Laber, Samer S. El-Kamary, Cheng Fan, Ravi Jhaveri, Charles M. Perou, Fatma M. Shebl, Michael R. Kosorok:
Receiver Operating Characteristic Curves and Confidence Bands for Support Vector Machines. CoRR abs/1807.06711 (2018)
Coauthor Index
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last updated on 2024-07-09 04:47 CEST by the dblp team
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