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Computational Statistics

Data Visualization

Education

Machine Learning

Practice and Applications

Software & Data Science Technologies

Wednesday, June 3

Machine Learning 1 Fill out evaluation
Contributed Refereed

Wed, Jun 3, 1:15 PM - 2:50 PM

Chair(s): Xiaotong Jiang , University of North Carolina at Chapel Hill

1:20 PM

RankFromSets: Scalable Set Recommendation with Optimal Recall
Jaan Altosaar, Princeton University

1:50 PM

Counterfactual Demand Predictions with Deep Learning
Presentation Mingyu (Max) Joo, UC Riverside

2:20 PM

Explaining the Practical Success of Random Forests
Presentation Siyu Zhou, University of Pittsburgh

Thursday, June 4

Anomaly Detection in Complex Data Fill out evaluation
Invited

Thu, Jun 4, 10:00 AM - 11:35 AM

Organizer(s): Sarah Rajtmajer, Penn State University

Chair(s): Sarah Rajtmajer, Penn State University

10:05 AM

High Temperature Structure Detection in Ferromagnets
Presentation Matey Neykov, University of Pittsburgh

10:35 AM

Toward Secure and Interpretable AI: Scalable Methods, Interactive Visualizations, and Practical Tools
Presentation Polo Chau, Georgia Tech

11:05 AM

Detecting Anomalies in Graph-Structured Data
James Sharpnack, UC Davis

Modern Inference in Statistical Machine Learning Fill out evaluation
Invited

Thu, Jun 4, 11:40 AM - 12:45 PM

Organizer(s): Ryan Tibshirani, Carnegie Mellon University

Chair(s): Nicholas Schmidt, BLDS

11:45 AM

Predictive Inference with Random Forests
Lucas Mentch, University of Pittsburgh

12:15 PM

Semiparametric Estimation in High Dimensions
Presentation Mladen Kolar, U Chicago Booth

Machine Learning 5 Fill out evaluation
Contributed Refereed

Thu, Jun 4, 11:40 AM - 12:45 PM

Chair(s): Thomas Carpenito, Northeastern University

11:45 AM

Modernizing k-Nearest Neighbors Software
Presentation Norm Matloff, UC Davis

12:15 PM

Heterogeneous Treatment Effects of Medicaid and Efficient Policies
Presentation Shishir Shakya, West Virginia University

Machine Learning 6 Fill out evaluation
Contributed Refereed

Thu, Jun 4, 11:40 AM - 12:45 PM

Chair(s): Yirui Hu, Geisinger

11:45 AM

Functional Singular Spectrum Analysis
Mehdi Maadooliat, Department of MSSC at Marquette University

12:15 PM

Statistical Learning and Energy Statistics for High-Dimensional Time Series
John Steven Schuler, George Mason University

Interactive Machine Learning Fill out evaluation
Invited

Thu, Jun 4, 1:20 PM - 2:55 PM

Organizer(s): James Sharpnack, UC Davis

Chair(s): James Sharpnack, UC Davis

1:25 PM

On the Global Convergence of Policy Optimization in Deep Reinforcement Learning
Zhaoran Wang, Northwestern University

1:55 PM

WITHDRAWN: Marginal Posterior Sampling for Slate Bandits

2:25 PM

Interactive Learning Using Labels and Comparisons
Aarti Singh, Carnegie Mellon University

Machine Learning and Software and Data Science Technologies Posters
E-Poster

Thu, Jun 4, 2:00 PM - 5:00 PM

Poster Q&A will be available during these designated hours as part of the virtual conference.

WITHDRAWN: Prediction of Hospital Readmissions: A Comparison of Predictive Methods on Binary and Survival Outcomes

WITHDRAWN Prediction of Inpatient Quality Indicators: A Comparison of Predictive Methods with and Without Random Hospital Effect

Can Big Data Algorithms Be Used to Improve Cybersecurity?
Allen Sina Rahrooh, University of Central Florida

WITHDRAWN: BLNN: An R Package for Training Neural Networks

WITHDRAWN Decision Tree Model-Based Gene Selection and Classification for Breast Cancer Risk Prediction

Learning the Stock Market States via a Logistic Regression Model and Its Applications
Qiyu Wang, Zhejiang Univ of Finance and Econ

Multiple Sequence Alignment Using Tensor Analysis
Mian Arif Shams Adnan, Bowling Green State University

Investigation of the Interplay Between Random Forest and Kernel Methods in Big Data
Richard Baumgartner, Merck&Co., Inc.

Interfacing Statistical Software Packages with R and Python
Neil Polhemus, Statgraphics Technologies, Inc.

TF-IDF-Weighted Similarity Estimates for Unseen Categories
Handong David Bang, UNC Chapel Hill Department of Biostatistics

Developing a Computational Framework for Precise TAD Boundary Prediction Using Genomic Elements
Spiro C Stilianoudakis, Virginia Commonwealth University

Predicting 30-Day Readmission After Surgery Among Colorectal Cancer Patients
Anshul Saxena, Baptist Health south Florida

R Package mase
Iris Griffith, Reed College

Friday, June 5

Interpretable and Fair Machine Learning in Finance Fill out evaluation
Invited

Fri, Jun 5, 11:15 AM - 12:50 PM

Organizer(s): Patrick Hall, H2O.ai

Chair(s): Patrick Hall, H2O.ai

This session will not be recorded/available for registrants to access on-demand.

11:20 AM

Adaptive Explainable Neural Networks (AxNN)
Presentation Jie Chen, Wells Fargo

11:50 AM

Responsible Data Science: Identifying and Fixing Biased AI
Nicholas Schmidt, BLDS

12:20 PM

A New Approach to Providing Explanations for Machine Learning Algorithms
Tom Prendergast, Synchrony Financial

Machine Learning 2 Fill out evaluation
Contributed Refereed

Fri, Jun 5, 1:25 PM - 3:00 PM

Chair(s): Lynne Steuerle Schofield, Swarthmore College

This session will not be recorded/available for registrants to access on-demand.

1:30 PM

Deep Doubly Robust Outcome-Weighted Learning
Xiaotong Jiang, University of North Carolina at Chapel Hill

2:00 PM

Locally Optimized Random Forests: A Solution to Forecasting Severe Hurricane Power Outages
Presentation Tim Coleman, University of Pittsburgh, Department of Statistics

2:30 PM

Modern Multiple Imputation Applied to Functional Data
Aniruddha Rajendra Rao, Pennsylvania State University

Machine Learning 4 Fill out evaluation
Contributed Refereed

Fri, Jun 5, 1:25 PM - 3:00 PM

Chair(s): Andee Kaplan, Colorado State

1:30 PM

A General Framework for Empirical Bayes Estimation in Discrete Linear Exponential Family
Trambak Banerjee, University of Southern California

2:00 PM

Multivariate Functional Singular Spectrum Analysis Over Different Dimensional Domains
Jordan Christopher Trinka, Department of MSSC at Marquette Univeristy

2:30 PM

A One-Class Peeling Method for Anomaly Detection
Waldyn Gerardo Martinez, Miami University

Machine Learning 3 Fill out evaluation
Contributed Refereed

Fri, Jun 5, 3:30 PM - 5:05 PM

Chair(s): Claire McKay Bowen, Urban Institute

3:35 PM

Machine Learning Model Selection with Complex Sample Survey Data
Brian Kim, University of Maryland

3:50 PM

Permutation-Based Uncertainty Quantification
Vaidehi Ulhas Dixit, North Carolina State University

4:05 PM

Toward Sequential Data Clustering via Long Short-Term Memory Auto-Encoder
Presentation Yirui Hu, Geisinger

4:20 PM

MISL: Multiple Imputation by Super Learning
Presentation Thomas Carpenito, Northeastern University

4:35 PM

Self-Supervised Learning for Outlier Detection
Jan Diers, Friedrich-Schiller-University Jena

4:50 PM

Q&A

Online Program

Viewing Track 'Machine Learning' only

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ASA Meetings Department