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Recent Additions:

N. Hassanpour, R. Greiner. "A Novel Evaluation Methodology for Assessing Off-Policy Learning Methods in Contextual Bandits". NIPS 2017 Workshop on Causal Inference and Machine Learning (WhatIF2017), November 2017. PDFview
N. Borle, M. Feghhi, E. Stroulia, R. Greiner, A. Hindle. "Analyzing The Effects of Test Driven Development In GitHub". Empirical Software Engineering, November 2017. view
J. Guinney, T. Wang, P. DREAM Community, R. Greiner, R. Vega, L. Kumar, J. Patel. "Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowd-sourced challenge with open clinical trial data.". Lancet Oncology, 18(1), pp 132-142, January 2017. view
F. Seyednasrollah, D. Koestler, T. Wang, S. Piccolo, R. Vega, R. Greiner, C. Fuchs, E. Gofer, L. Kumar. "A DREAM Challenge to build prediction models for short-term discontinuation of docetaxel in metastatic castration-resistant prostate cancer". Journal of Clinical Oncology: Clinical Cancer Informatics, July 2017. view
J. Patel, N. Asgarian, P. Robson, R. Greiner, J. Mackey, S. Damaraju. " Gene-environment-lifestyle factors in breast cancer susceptibility: Machine Learning tools to build predictive models". Journal of Carcinogenesis, 14 (Suppl 1), pp S16-S20, January 2015. view
M. Brown, G. Sidhu, R. Greiner, N. Asgarian, M. Bastani, P. Silverstone, A. Greenshaw, S. Dursun. "ADHD-200 Global Competition: Diagnosing ADHD using personal characteristic data can outperform resting state fMRI measurements ". Frontiers in Systems Neuroscience, (ed: Michael Milham), 6(10.3389/fnsys.2012.00069), September 2012. view

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