N.B. This workshop has already occurred.
However, you can find the slides available at the following places.
Rob's slides
BART Workshop, June 2023
Rodney's slides
https://community.amstat.org/wisconsinchapter/viewdocument/ensemble-learning-with-bayesian-add?CommunityKey=fa822db7-e8a1-4b8b-a94e-781e30e44b33&tab=librarydocuments
The Wisconsin Chapter of the American Statistical Association (ASA)
in association with
The Division of Biostatistics at the Medical College of Wisconsin (MCW)
proudly presents
a hybrid in-person/virtual workshop
Ensemble Learning with Bayesian Additive Regression Trees
by Professor Robert E McCulloch
School of Mathematical and Statistical Sciences at Arizona State University
and Associate Professor Rodney Sparapani
Division of Biostatistics at the Medical College of Wisconsin
More info on the workshop; see below.
Dates: June 7 and 8 (Wednesday and Thursday)
Times: 8:30 to 4:30 CDT
Location: Online with Zoom or in-person at
The Medical College of Wisconsin
Kerrigan Auditorium, M1540
8701 Watertown Plank Road
Located SW of intersection with 87th Street
Milwaukee, WI 53226
Parking: After registering, you will receive info on Visitor Parking
Lunch: On your own, there are two cafeterias on campus
Dinner with the speaker: 5PM Wednesday at TBD, please RSVP
In-person: $20 Current Wisconsin ASA Chapter members in good standing
$20 Students enrolled at a college/university in Wisconsin
$50 All others (including $10 Wisconsin Chapter 1 year membership)
Bring your laptops for hands-on!
Hybrid: $ 5 Current Wisconsin ASA Chapter members in good standing
$ 5 Students enrolled at a college/university in Wisconsin
$35 All others (including $10 Wisconsin Chapter 1 year membership)
Registration deadline: 06/01/2023
You can make payment via PayPal to the Treasurer
elizabethsmith@asawisconsin.onmicrosoft.com
or send a check made out to The Wisconsin Chapter of the ASA
(please put your email address in the memo field for contact)
Elizabeth Smith
6001 W Donges Lane
Brown Deer, WI 53223
Ensemble Learning with Bayesian Additive Regression Trees
by Robert E McCulloch, PhD
School of Mathematical and Statistical Sciences at Arizona State University
https://www.rob-mcculloch.org
and Rodney Sparapani, PhD
Division of Biostatistics at the Medical College of Wisconsin
https://www.linkedin.com/in/rodneysparapani
Abstract:
Modern computing power has led to breakthroughs in our ability to
learn high-dimensional, complex relationships from data. Recently,
the two key modeling approaches in this arena are deep learning with
neural networks and ensemble learning with trees. In this workshop,
you will learn a Bayesian approach to modeling with ensembles of trees
called Bayesian Additive Regression Trees (BART). The Bayesian
approach allows for a Markov chain Monte Carlo stochastic exploration
of the model space, uncertainty quantification, and Bayesian posterior
inference. BART is a modern nonparametric approach that exploits the
elegance and convenience of the Bayesian conceptual toolkit.
Schedule:
Wednesday June 7
08:30 Welcoming with President Tucker Keuter
09:00 Introduction and Background to Bayesianism with Rob
09:30 Bayesian Additive Regression Trees (BART) with Rob
10:30 Break
11:00 BART and Posterior Inference with Rob
12:00 Lunch on your own (but please be social in-person!)
13:00 Hands-on with BART Software with Rodney
14:30 Break
15:00 BART and Categorical Outcomes with Rodney
16:00 Questions and Answers
16:30 End of day 1
17:00 Dinner with the speakers at Eddie Martini's (please RSVP)
Thursday June 8
08:30 Welcoming VP (and President-elect) Kai Yang
09:00 Variable Selection with Rob and Rodney
10:30 Break
11:00 Monotonicity, Outliers and Influencers with Rob and Rodney
12:00 Lunch on your own (but please be social in-person!)
13:00 Time-to-event Outcomes with Rodney
14:30 Break
15:00 A Wider View of BART Developments with Rob and Rodney
16:00 Questions and Answers
16:30 End of day 2