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AW

Ansgar Wenzel

University of Sussex
PhD student
London, United Kingdom

8:00am PDT

Registration check-in McCaw Hall

9:00am PDT

Machine Learning Algorithmic Deep Dive (Part 1) Campbell Rehearsal Hall

10:15am PDT

Coffee Break McDowell & Cranston Coffee Break Lane Coffee Break Barnes Coffee Break SIEPR 130 Coffee Break Wallenberg Hall 124 Coffee Break Econ 140 Coffee Break SIEPR 120 Coffee Break Campbell Rehearsal Hall Coffee Break Lyons & Lodato

10:30am PDT

Machine Learning Algorithmic Deep Dive (Part 2) Campbell Rehearsal Hall

12:00pm PDT

Lunch SIEPR 120

1:00pm PDT

Effective Shiny Programming (Part 1) McCaw Hall Extracting data from the web APIs and beyond (Part 1) Campbell Rehearsal Hall

2:15pm PDT

Coffee Break Campbell Rehearsal Hall

2:30pm PDT

Effective Shiny Programming (Part 2) McCaw Hall Extracting data from the web APIs and beyond (Part 2) Campbell Rehearsal Hall

8:30am PDT

Opening Session McCaw Hall

9:00am PDT

Forty years of S McCaw Hall

10:00am PDT

Coffee Break with Poster Exhibits McCaw Hall

10:30am PDT

R in machine learning competitions McCaw Hall

10:48am PDT

RcppParallel: A Toolkit for Portable, High-Performance Algorithms SIEPR 130

11:06am PDT

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

11:24am PDT

Automating our work away: One consulting firm's experience with KnitR Econ 140

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

Zero-overhead integration of R, JS, Ruby and C/C++ Lane & Lyons & Lodato

2:12pm PDT

Wrap your model in an R package! SIEPR 120

2:30pm PDT

Coffee Break w/ Poster Session McCaw Hall

3:30pm PDT

Literate Programming McCaw Hall

4:30pm PDT

Short Break McCaw Hall

4:45pm PDT

How to keep your R code simple while tackling big datasets Barnes & McDowell & Cranston

5:03pm PDT

New Paradigms In Shiny App Development: Designer + Data Scientist Pairing Lane & Lyons & Lodato

5:21pm PDT

Data validation infrastructure: the validate package Barnes & McDowell & Cranston

5:39pm PDT

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

5:57pm PDT

Colour schemes in data visualisation: Bias and Precision McCaw Hall

6:30pm PDT

Welcome Reception Bing Concert Hall

8:00am PDT

Registration check-in McCaw Hall

9:00am PDT

Towards a grammar of interactive graphics McCaw Hall

10:00am PDT

Coffee Break with Poster Exhibits McCaw Hall

10:30am PDT

Profvis: Profiling tools for faster R code Econ 140

10:48am PDT

Size of Datasets for Analytics and Implications for R Econ 140

11:06am PDT

Resource-Aware Scheduling Strategies for Parallel Machine Learning R Programs though RAMBO Econ 140

11:24am PDT

Heatmaps in R: Overview and best practices Barnes & McDowell & Cranston

11:42am PDT

Exploring the R / SQL boundary SIEPR 130

12:00pm PDT

Lunch with Poster Exhibits McCaw Hall

1:00pm PDT

Reusable R for automation, small area estimation and legacy systems Barnes & McDowell & Cranston

1:18pm PDT

Tools for Robust R Packages SIEPR 130

1:36pm PDT

Adding R, Jupyter and Spark to the toolset for understanding the complex computing systems at CERN's Large Hadron Collider McCaw Hall

1:54pm PDT

How to do one's taxes with R McCaw Hall

2:12pm PDT

brglm: Reduced-bias inference in generalized linear models Econ 140

2:30pm PDT

Coffee Break with Poster Session McCaw Hall

3:30pm PDT

Flexible and Interpretable Regression Using Convex Penalties McCaw Hall

4:30pm PDT

Cruise & Conference Dinner McCaw Hall

9:00am PDT

Statistical Thinking in a Data Science Course McCaw Hall

10:00am PDT

Coffee Break w/ Poster Exhibits 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

11:06am PDT

viztrackr: Tracking and discovering plots via automatic semantic annotations SIEPR 130

11:24am PDT

ggduo: Pairs plot for two group data SIEPR 130

11:42am PDT

Most Likely Transformations McCaw Hall

12:00pm PDT

Lunch w/ Poster Exhibits McCaw Hall

1:00pm PDT

Estimating causal dose response functions using the causaldrf R package McCaw Hall

1:30pm PDT

Thinking about Energy Markets with interactivity SIEPR 130

2:00pm PDT

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

3:00pm PDT

Closing Remarks McCaw Hall