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Keyword Search Criteria: machine learning returned 107 record(s)
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Sunday, 07/29/2018
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Advantageous Statistical Tools for Stock Market Investing
Kenneth Davis
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Big Data Detectives: Improving Human Health Through Informing Policy
Kristin Linn, University of Pennsylvania; Laura Hatfield, Harvard Medical School; Julian Wolfson, University of Minnesota; Sherri Rose, Harvard Medical School
2:05 PM
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Advantageous Statistical Tools for Stock Market Investing
Kenneth Davis
2:05 PM
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Statistics at Consumer Reports
Michael Saccucci, Consumer Reports
2:45 PM
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Exploring Clustering Applications in Outlier Detection for Administrative Data Sources
Elizabeth Ayres, Statistics Canada
2:50 PM
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Data Adaptive Evaluation of Preprocessing Methods Using Ensemble Machine Learning
Rachael Phillips, Biostatistics, UC Berkeley
4:05 PM
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Entity Resolution with Societal Impacts in Statistical Machine Learning
Rebecca C. Steorts, Duke University
4:30 PM
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Predictive and Interpretable Bayesian Machine Learning Models for Understanding Microbiome Dynamics
Georg Kurt Gerber, Harvard Medical School / Brigham and Women's Hospital
4:45 PM
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Precision Medicine in Dynamic-Time Systems
Michael Lawson
5:05 PM
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Monday, 07/30/2018
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Predicting Hospital Readmission for Diabetes Patients by Classical and Machine Learning Approaches
Gabrielle LaRosa, University of Pittsburgh; Chathurangi Pathiravsan, Southern Illinois University Carbondale; Rajapaksha Wasala M Anusha Madushani, University of Florida
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The Classification of Stellar Systems Through Singular Spectrum Analysis
Kevin Matheson, Western Washington University; Kevin Covey, Western Washington University; Kimihiro Noguchi, Western Washington University
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Machine Learning with Ensemble Feature Selections for Mass Spectrometry Data in Cancer Study
Yulan Liang, University of Maryland Baltimore; Amin Gharipour, Griffith University; Arpad Kelemen, University of Maryland Baltimore; Adam Kelemen, University of Maryland College Park; Hui Zhang, Johns Hopkins Medical Institutions
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Bayesian and Unsupervised Machine Learning Machines for Jazz Music Analysis
Qiuyi Wu, ASA; Ernest Fokoue, ASA
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Comparison of Methods for Predicting High-Cost Patients Captured Within the Oncology Care Model (OCM): a Simulation Study
Jung-Yi Lin, Icahn School of Medicine at Mount Sinai; Wei Zhang, UALR; Mark Liu, Mount Sinai Health System; Mark Sanderson, Mount Sinai Health System; Luis Isola, Mount Sinai Health System; Madhu Mazumdar, Icahn School of Medicine at Mount Sinai; Liangyuan Hu, Icahn School of Medicine at Mount Sinai
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Model Class Reliance: Variable Importance Measures for Any Machine Learning Model Class, from the
Aaron Fisher, Harvard University; Cynthia Rudin, Duke University; Francesca Dominici, Harvard T. H. Chan School of Public Health
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BENCHMARKING the EFFECTIVENESS of CATEGORICAL RESPONSE VARIABLE MODELS and THEIR VISUALIZATIONS on WEATHER DATA
Kristen Bystrom; Zhi Yuh Ou Yang, Simon Fraser University; Lei Chen, Simon Fraser University
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New Applications of Machine Learning to Estimating Large Physician Demand Models
Bryan Sayer, Social & Scientific Systems, Inc.; William Encinosa, Agency for Health Care Quality and Research
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Battle Royale: Machine Learning vs. Mechanistically Motivated Spatio-Temporal Models for Atmospheric and Oceanic Processes
Christopher K. Wikle, University of Missouri
8:35 AM
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Model Class Reliance: Variable Importance Measures for Any Machine Learning Model Class, from the
Aaron Fisher, Harvard University; Cynthia Rudin, Duke University; Francesca Dominici, Harvard T. H. Chan School of Public Health
8:40 AM
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Breaking Computational Chicken-And-Egg Loop in Adaptive Sampling and Estimations Using Locality Sensitive Sampling (LSS)
Anshumali Shrivastava, Rice University
8:55 AM
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Learning Individualized Treatment Rules from Electronic Health Records Data
Yuanjia Wang, Columbia University
9:00 AM
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Comparison of Methods for Predicting High-Cost Patients Captured Within the Oncology Care Model (OCM): a Simulation Study
Jung-Yi Lin, Icahn School of Medicine at Mount Sinai; Wei Zhang, UALR; Mark Liu, Mount Sinai Health System; Mark Sanderson, Mount Sinai Health System; Luis Isola, Mount Sinai Health System; Madhu Mazumdar, Icahn School of Medicine at Mount Sinai; Liangyuan Hu, Icahn School of Medicine at Mount Sinai
9:10 AM
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An Analysis on the Accuracy of Weather Forecasts
Benjamin William Schweitzer, Miami University; Nichole Rook, Miami University; Ryan Estep, Miami University; Robert Garrett, Miami University; Thomas Fisher, Miami University
9:30 AM
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Visual Analytics in the Real World Evidence Data Realm
Melvin Munsaka, AbbVie, Inc.; Kefei Zhou, Theravance Biopharma; Krishan P. Singh, GlaxoSmithKline
9:35 AM
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A Venn-Diagram Analysis of the Role of Statistics in Data Science
John McKenzie, Babson College
9:50 AM
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BENCHMARKING the EFFECTIVENESS of CATEGORICAL RESPONSE VARIABLE MODELS and THEIR VISUALIZATIONS on WEATHER DATA
Kristen Bystrom; Zhi Yuh Ou Yang, Simon Fraser University; Lei Chen, Simon Fraser University
9:50 AM
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New Applications of Machine Learning to Estimating Large Physician Demand Models
Bryan Sayer, Social & Scientific Systems, Inc.; William Encinosa, Agency for Health Care Quality and Research
10:05 AM
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Risk Analysis in Banking
Vijayan Nair, 215157
10:55 AM
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General Techniques for Successful Data Science Competitions
Ian Michael Mouzon, Iowa State University
11:35 AM
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Edward: a Library for Probabilistic Machine Learning and Statistics
Dustin Tran, Columbia University; David Blei, Columbia University
11:35 AM
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Using Concomitant and Nested Simulation for Tail Risk Measure Estimation
Mingbin Feng, University of Waterloo
11:55 AM
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Comparison of Interval Estimation in Machine Learning
Dai Feng, Merck; Andy Liaw, Merck & Co., Inc.; Vladimir Svetnik, Merck
2:05 PM
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Nonparametric Variable Importance Assessment Using Machine Learning Techniques
Brian Williamson, University of Washington; Peter Gilbert, Fred Hutchinson Cancer Research Center; Noah Simon, University of Washington; Marco Carone, University of Washington
2:25 PM
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Prediction Using Machine Learning Algorithms by Small Sample Size Data
Yan Wang, Field School of Public Health, UCLA; Honghu Liu, UCLA; Jian L Zhang, Kaiser Permanente
3:20 PM
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Ensemble of Iterative Classifier Chains for Multi-Label Classification
Zhoushanyue He, University of Waterloo; Matthias Schonlau, University of Waterloo
3:35 PM
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Tuesday, 07/31/2018
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Interpretable Statistical Machine Learning for Validation and Uncertainty Quantification of Complex Models
Ana Kupresanin, Lawrence Livermore National Laboratory
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An Application of Machine Learning for 3D IC Defect Detection
Meihui Guo, National Sun Yat-Sen University; Yu-Jung Huang, I-Shou University
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A Machine Learning (ML) Approach to Prognostic and Predictive Covariate Identification for Subgroup Analysis and Hypotheses Generation
David A James, Novartis
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Targeted Maximum Likelihood Estimation of Causal Effects Based on Observing a Single Time Series
Ivana Malenica; Mark van der Laan, UC Berkeley
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Machine Learning to Evaluate the Quality of Patient Reported Epidemiological Data
Robert L. Wood, Resonate & Wichita State University; Futoshi Yumoto, Resonate; Rochelle Tractenberg, Georgetown University
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Predicting Overflow: A Novel Application of Latrine Sensors and Machine Learning for Optimizing Sanitation Services in Informal Settlements
Phillip Turman-Bryant, Portland State University; Evan Thomas, Portland State University
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A Modified Approach to Component-Wise Gradient Boosting for High-Dimensional Regression Models
Brandon Butcher, University of Iowa; Brian J. Smith, University of Iowa
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Committee on Law and Justice Statistics
Joel Hunt, National Institute of Justice; Patryk Miziula, deepsense.ai; George Mohler, IUPUI; Tuanjie Tong, Intuidex, Inc.; Dylan Fitzpatrick, Carnegie Mellon University
8:35 AM
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Personalization Through Uplift Modeling: Techniques and Business Applications
Victor Lo, Fidelity Investments
8:35 AM
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A Comparison of Similarity Scores Between Bullet Casings: Forensic Analysts Versus an Algorithm
Maria Cuellar, Carnegie Mellon University
8:35 AM
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Improving the Value of Public Data with Recount2 and Phenotype Prediction
Shannon Ellis, Johns Hopkins University, Bloomberg School of Public Health
8:55 AM
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Analyzing Large Scale Genomics Data with Apache Spark and ADAM
Frank Nothaft, Databricks
9:15 AM
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Machine Learning Methods for Animal Movement
Dhanushi A Wijeyakulasuriya, Pennsylvania State University; Ephraim Hanks, The Pennsylvania State University; Benjamin Shaby, Penn State University
9:35 AM
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New Approaches Towards Translational Neuroimaging
Martin A Lindquist, Johns Hopkins University
9:50 AM
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Budget-Constrained Feature Selection for Binary Classification: a Neyman-Pearson Approach
Yiling Chen, University of California, Los Angeles; Xin Tong, University of Southern California; Jingyi Li, University of California, Los Angeles
10:05 AM
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Targeted Maximum Likelihood Estimation of Causal Effects Based on Observing a Single Time Series
Ivana Malenica; Mark van der Laan, UC Berkeley
10:35 AM
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Using Genomic Features to Make Smart Clinical Decisions: The Power of Machine Learning with RNA-Seq
Jing Huang, Veracyte Inc; Su yeon Kim , Veracyte Inc; Yangyang Hao, Veracyte Inc; Jing Lu, Veracyte Inc; Joshua Babiarz, Veracyte Inc; Sean Walsh, Veracyte Inc; Giulia Kennedy, Veracyte Inc
11:00 AM
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Personalized Solution Recommendation for Google Cloud Marketplace
Tianhong He, Google; Sangho Yoon, Google
11:05 AM
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Spectral Methods for Kernel Learning
Charlotte Haley, Argonne National Lab; Christopher J Geoga, Argonne National Laboratory; Mihai Anitescu, Argonne National Laboratory
11:20 AM
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Ensemble Learning for Estimating Individualized Treatment Effects in Student Success Studies
Richard Levine, San Diego State University; Joshua Beemer, San Diego State University; Juanjuan Fan, San Diego State University
11:20 AM
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Spatial Statistics Vs Machine Learning: Evaluating Air Pollution Exposure Prediction Models
Gregory Watson, UCLA; Donatello Telesca, UCLA
11:20 AM
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A Machine Learning (ML) Approach to Prognostic and Predictive Covariate Identification for Subgroup Analysis and Hypotheses Generation
David A James, Novartis
11:35 AM
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An Application of Machine Learning for 3D IC Defect Detection
Meihui Guo, National Sun Yat-Sen University; Yu-Jung Huang, I-Shou University
11:40 AM
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A Modified Approach to Component-Wise Gradient Boosting for High-Dimensional Regression Models
Brandon Butcher, University of Iowa; Brian J. Smith, University of Iowa
11:45 AM
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Predicting Overflow: A Novel Application of Latrine Sensors and Machine Learning for Optimizing Sanitation Services in Informal Settlements
Phillip Turman-Bryant, Portland State University; Evan Thomas, Portland State University
11:55 AM
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Machine Learning to Evaluate the Quality of Patient Reported Epidemiological Data
Robert L. Wood, Resonate & Wichita State University; Futoshi Yumoto, Resonate; Rochelle Tractenberg, Georgetown University
12:10 PM
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Inference of Transcription Factor Binding Sites in New Cell Types from Open Chromatin and Gene Expression Data
Michael M. Hoffman, Princess Margaret Cancer Centre/University of Toronto; Mehran Karimzadeh, University of Toronto
2:05 PM
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Evidence-based Policy for People with Disabilities: An Analysis of Disabilities in the DPRK within the Global Context of Disability Studies
Giang Huong Nguyen, University of Iowa; Allison Conners, University of Toronto; Sophie Lee, ISR Foundation Center for Interdisciplinary Research; Nema Dean, University of Glasgow; Paul Chun, ISR Foundation Center for Interdisciplinary Research
2:05 PM
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Predicting Panel Drop-Outs with Machine Learning
Christoph Kern, University of Mannheim
2:20 PM
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Causal Inference Using EMRs with Missing Data: a Machine Learning Approach with an Application on the Evaluation of Implantable Cardioverter Defibrillators
Changyu Shen, Beth Israel Deaconess Medical Center, Harvard Medical School; Xiaochun Li, Indiana University; Zuoyi Zhang, Regenstrief Institute; Alfred E Buxton, Beth Israel Deaconess Medical Center
2:25 PM
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Unsupervised Learning for Deciphering Mutational Signatures in Human Cancer
Ludmil B Alexandrov, University of California, San Diego; Velimir V Vesselinov, Los Alamos National Lab; Boian S Alexandrov, Los Alamos National Lab
2:55 PM
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The Use of Machine Learning Methods to Improve the US National Resources Inventory Survey
Zhengyuan Zhu, Iowa State University
3:05 PM
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Compressing Scientific Data: Reducing Storage While Preserving Information
Dorit Hammerling, National Center for Atmospheric Research; Joseph Guinness, NC State University; Allison Baker, National Center for Atmospheric Research
3:25 PM
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Wednesday, 08/01/2018
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Preparing Statistician to Successfully Data Scientist in Big Data Era
Ming Li, Amazon
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Improving Object Detection with Image Preprocessing
Timothy J. Park, Purdue University
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Analyzing Bias in Object Detection Data Sets
Meera Haridasa, Purdue University; Cailey Farrell, Purdue University
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A Stagewise Prognostic Control Predictive Approach (SPCPA) for Subgroup Identification and Its Application in a Phase II Study
Wanying Li, Gilead Sciences; Wangshu Zhang, Gilead Sciences; Lovely Goyal, Gilead Sciences; Yuanyuan Xiao, Gilead Sciences
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Exposure-Response Analysis with Random Forest
Zifang Guo, Merck; Thomas Jemielita, Merck & Co.; John Kang, Merck
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Identifying Misclassifications in Consumer Expenditure Data
Clayton Knappenberger, U.S. Bureau of Labor Statistics
8:35 AM
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A Stagewise Prognostic Control Predictive Approach (SPCPA) for Subgroup Identification and Its Application in a Phase II Study
Wanying Li, Gilead Sciences; Wangshu Zhang, Gilead Sciences; Lovely Goyal, Gilead Sciences; Yuanyuan Xiao, Gilead Sciences
8:35 AM
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Estimation of Economic Models with Non-Euclidean Data
Suyong Song, University of Iowa; Stephen Baek, University of Iowa
8:35 AM
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Mortality Prediction with Multiple Unordered Treatments for Aortic Valve Replacement
Samrachana Adhikari, Harvard Medical School; Sherri Rose, Harvard Medical School; Sharon-Lise Normand, Harvard University; Jordan Bloom, Harvard Medical School; David Shahian, Harvard Medical School; Jake Spertus, Harvard Medical School
8:55 AM
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The CFR Miner: Natural Language Processing of the Code of Federal Regulations Using R Studio and Shiny
Richard Schwinn, U.S. Small Business Administration
9:15 AM
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Can We Train Machine Learning Methods to Outperform the High-Dimensional Propensity Score Algorithm?
Mohammad Ehsanul Karim, University of British Columbia; Robert W Platt, McGill University
9:20 AM
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Deep Learning in Medical Imaging: Evaluation and Study Design
Robyn Ball, Stanford University; David Larson, Stanford University; Pranav Rajpurkar, Stanford University; Matthew Chen, Nines AI; Jeremy Irvin, Stanford University; Jaden Yang, Stanford University; Matthew P Lungren, Stanford University
9:20 AM
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Heterogeneous Treatment Effect Estimation through Deep Learning
Ran Chen, Wharton; Hanzhong Liu, Center for Statistical Science, Tsinghua University
9:35 AM
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A Simulation Study on the Performance of Deep Learning Methods for Multi-Category Classification
Dawei Liu, Biogen; Ih Chang, Biogen
9:50 AM
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Exposure-Response Analysis with Random Forest
Zifang Guo, Merck; Thomas Jemielita, Merck & Co.; John Kang, Merck
10:00 AM
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Distributed Data Science with Sparklyr
Javier Luraschi, RStudio; Kevin Kuo, RStudio
11:05 AM
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Time-Constrained Predictive Modeling on Large and Continuously Updating Financial Data Sets
Bernard Lee, HedgeSPA Limited; Nicos Christofides, Imperial College London
11:20 AM
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Distributed Machine Learning with H2O
Navdeep Gill, H2O.ai
11:35 AM
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Data Science in a Hurry
Iyue Sung
11:50 AM
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On the Art and Science of Machine Learning Explanations
Patrick Hall, H20.ai
2:05 PM
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An Algorithm for Removing Sensitive Information
James Johndrow, Stanford University; Kristian Lum, Human Rights Data Analysis Group
2:25 PM
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Local, Model-Agnostic Explanations of Machine Learning Predictions
Sameer Singh, University of California, Irvine
2:45 PM
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Evaluating the Census Planning Database, MSG, and Paradata as Predictors of Household Propensity to Respond
Xiaoshu Zhu, Westat; Robert Baskin, Westat; David Morganstein, Westat
2:50 PM
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Can We Compute an Optimal Sparse Decision Tree?
Cynthia Rudin, Duke University; Elaine Angelino, Berkeley; Nicholas Larus-Stone, Cambridge; Margo Seltzer, Harvard; Daniel Alabi, Harvard
3:05 PM
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Optimal Bayesian Design for Models with Intractable Likelihoods via Machine Learning Methods
Christopher C Drovandi, Queensland University of Technology; Markus Hainy, QUT
3:05 PM
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Beyond Feature Attribution: Quantitative Concept-Based Interpretability with TCAV
Been Kim, Google Brain
3:25 PM
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Thursday, 08/02/2018
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Statistical Consulting in the Age of Cognitive Computing, Deep Learning, and AI: Obsolete or Needed Now More Than Ever?
Nikola Andric, Deloitte Consulting LLP
8:35 AM
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Sequential Prediction, Martingale Tail Bounds and Automatic Machine Learning
Karthik Sridharan, Cornell University
8:35 AM
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Inferential Challenges in Machine Learning and Precision Medicine
Michael Kosorok, University of North Carolina at Chapel Hill
8:35 AM
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Leveraging Adiabatic Quantum Computation for Election Forecasting
Maxwell Henderson, QxBranch
8:35 AM
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Fair Inference Through Semiparametric-Efficient Estimation Over Constraint-Specific Paths
Nima Hejazi, Group in Biostatistics, UC Berkeley
8:35 AM
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A Comparison of Record Linkage Techniques
Lowell Mason, U.S. Bureau of Labor Statistics
8:35 AM
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Automatic Wildfire Smoke Plume Identification from Satellite Imagery with Machine Learning
Alexandra Larsen, North Carolina State University; Ana Rappold, U.S. Environmental Protection Agency; Yi Qin, The Commonwealth Scientific and Industrial Research Organisation; Martin Cope, The Commonwealth Scientific and Industrial Research Organisation; Geoffrey Morgan, The University of Sydney; Ivan Hannigan, The University of Sydney; Brian J. Reich, North Carolina State University
8:35 AM
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The Use of Machine Learning in the Pharmaceutical Industry: The Promise and the Peril
Todd Sanger, Eli Lilly and Company
8:55 AM
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The Use of Machine Learning and Statistics in the Technology Sector
Joseph Kelly, Google
9:15 AM
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Optimal Treatment Recommendation via Subgroup Identification in Randomized Control Trials
Yang (Grace) Zhao, Gilead Sciences; Haoda Fu, Eli Lilly and Company
10:05 AM
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Data Science + Social Science: Using Data Science to Track Arrest-Related Deaths in the US
Duren Banks, RTI International; Peter Baumgartner, RTI International; Michael G. Planty, RTI International
11:00 AM
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A Model for Prioritizing Interventions for People at Risk of Incarceration
Erika Salomon, University of Chicago
11:25 AM
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Targeted Learning for Variable Importance in Precision Medicine
Yue You, Division of Biostatistics, University of California, Berkeley; Alan Hubbard, Division of Biostatistics, University of California, Berkeley; Rachael Callcut, Zuckerberg San Francisco General Hospital, University of California; Lucy Kornblith, Zuckerberg San Francisco General Hospital, UCSF; Sabrinah Christie, Zuckerberg San Francisco General Hospital, UCSF
11:50 AM
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