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Soo-heang Eo

Korea University
Researcher
Seongbuk-gu, Seoul, Korea

8:00am PDT

Registration check-in McCaw Hall

9:00am PDT

Never Tell Me the Odds! Machine Learning with Class Imbalances (Part 1) Econ 140

10:30am PDT

Never Tell Me the Odds! Machine Learning with Class Imbalances (Part 2) Econ 140

1:00pm PDT

Introduction to SparkR (Part 1) Econ 140

2:30pm PDT

Introduction to SparkR (Part 2) Econ 140

4:15pm PDT

What's up with the R consortium? McCaw Hall

8:30am PDT

Opening Session McCaw Hall

9:00am PDT

Forty years of S McCaw Hall

10:30am PDT

edeaR: Extracting knowledge from process data Econ 140

10:48am PDT

Two-sample testing in high dimensions Lane & Lyons & Lodato

11:06am PDT

trackeR: Intrastructure for running and cycling data from GPS-enabled tracking devices in R McCaw Hall

11:24am PDT

United Nations World Population Projections with R McCaw Hall

11:42am PDT

FlashR: Enable Parallel, Scalable Data Analysis in R SIEPR 130

12:00pm PDT

Lunch with Poster Exhibits Sponsor Pavilion

1:00pm PDT

Group and sparse group partial least squares approaches applied in a genomics context Barnes & McDowell & Cranston

1:18pm PDT

Fast additive quantile regression in R Barnes & McDowell & Cranston

1:36pm PDT

bigKRLS: Optimizing non-parametric regression in R Barnes & McDowell & Cranston

1:54pm PDT

Multiple Hurdle Tobit models in R: The mhurdle package Barnes & McDowell & Cranston

2:12pm PDT

Detection of Differential Item Functioning with difNLR function Barnes & McDowell & Cranston

2:30pm PDT

Urban Mobility Modeling using R and Big Data from Mobile Phones Sponsor Pavilion

3:30pm PDT

Literate Programming McCaw Hall

4:45pm PDT

Covr: Bringing Code Coverage to R Econ 140

5:03pm PDT

Deep Learning for R with MXNet SIEPR 130

5:21pm PDT

Interactive Naive Bayes using Shiny: Text Retrieval, Classification, Quantification SIEPR 130

5:39pm PDT

xgboost: An R package for Fast and Accurate Gradient Boosting SIEPR 130

5:57pm PDT

Rectools: An Advanced Recommender System SIEPR 130

6:30pm PDT

Welcome Reception Bing Concert Hall

9:00am PDT

Towards a grammar of interactive graphics McCaw Hall

10:30am PDT

Importing modern data into R SIEPR 130

10:48am PDT

ETL for medium data SIEPR 130

11:06am PDT

Efficient tabular data ingestion and manipulation with MonetDBLite SIEPR 130

11:24am PDT

Efficient in-memory non-equi joins using data.table SIEPR 130

11:42am PDT

Classifying Murderers in Imbalanced Data Using randomForest McCaw Hall

1:00pm PDT

mumm: An R-package for fitting multiplicative mixed models using the Template Model Builder (TMB) Econ 140

1:18pm PDT

Visualizing multifactorial and multi-attribute effect sizes in linear mixed models with a view towards sensometrics Econ 140

1:36pm PDT

Revisiting the Boston data set (Harrison and Rubinfeld, 1978) SIEPR 120

1:54pm PDT

Spatial data in R: simple features and future perspectives SIEPR 120

2:12pm PDT

High performance climate downscaling in R SIEPR 120

2:30pm PDT

Profile Analysis of Multivariate Data Using the profileR Package Sponsor Pavilion

3:30pm PDT

Flexible and Interpretable Regression Using Convex Penalties McCaw Hall

9:00am PDT

Statistical Thinking in a Data Science Course McCaw Hall

10:30am PDT

Gradient Boosted Trees Model: deploying R models into production environments* Lane & Lyons & Lodato

10:50am PDT

ranger: A fast implementation of random forests for high dimensional data Lane & Lyons & Lodato

11:08am PDT

Superheat: Supervised heatmaps for visualizing complex data Lane & Lyons & Lodato

11:26am PDT

Big data algorithms for rank-based estimation Lane & Lyons & Lodato

11:42am PDT

Most Likely Transformations McCaw Hall

1:00pm PDT

Catching up with Rstudio Lane & Lyons & Lodato

1:20pm PDT

R for Big Data and Applications: Using R at Oracle Lane & Lyons & Lodato

1:35pm PDT

Scalable Machine Learning in R with H2O Lane & Lyons & Lodato

2:00pm PDT

RCloud - Collaborative Environment for Visualization and Big Data Analytics McCaw Hall