** Registration for this event has reached capacity and is now closed **
This event will be held at Penn Pavilion on the campus of Duke University.
Recommended parking: Bryan Center Parking Garage (Parking Garage IV)
Modeled after similar events occurring in New York and Boston, the goal is to bring together researchers and applied scientists working in all different areas of machine learning, including industrial applications, academic theory, and everything in between, for a day of technical talks and posters.
Topics include predictive modeling and data science applications, algorithm design, reinforcement learning, natural language processing, etc.
The program will include a poster session, and anyone wishing to contribute a poster must submit an abstract; not all abstracts will be selected as posters, depending on space limitations. The due date for poster submissions is August 29, 2019. Send poster titles to firstname.lastname@example.org. Poster selections will be announced on September 5th.
Heavy snacks will be provided for all participants, lunch and breakfast are on your own. There are a large number of restaurants at the neighboring Brodhead Center.
If your company would like to sponsor TMLD, contact Sue McDonald.
For technical questions involving this event, contact Professor Cynthia Rudin.
General logistical questions can be directed to email@example.com.
** Notice of Consent **
SAMSI values the proprietary and intellectual property of our participants. The materials presented at our various workshops and programs are in high demand by event participants and the applied mathematics and statistics community that comprise our audience. Therefore, we encourage all of our invited speakers to share their materials, as appropriate, in order to pass along the valuable research that is being done in your field of study and is a focus of this event. In addition, unless SAMSI is give written approval from our speakers we ARE NOT authorized to share the materials presented at this event.
Please click HERE to complete a SAMSI Consent form for this event. SAMSI appreciates your time and willingness to share this valuable content with others and we hope you enjoy this event!
For any questions or concerns about our consent policy, please contact us at: firstname.lastname@example.org
** NOTE: Because capacity has been reached for this event, SAMSI is pleased to announce we will also be LIVE STREAMING the event from our You Tube Channel. To watch LIVE on the day of the event, click HERE. **
Schedule and Supporting Media
|8:50-9:00am||Welcome: Cynthia Rudin, Duke University and Associate Director, SAMSI|
|9:00-9:30am||Machine Learning for 3D Imaging||Sayan Mukherjee, Duke University|
|9:30-10:00am||Active Learning for Probabilistic Record Linkage||Ted Enamorado, University of North Carolina at Chapel Hill|
|10:00-10:30am||Data-driven Decision Making in Healthcare Operations||Nilay Talik Argon, University of North Carolina at Chapel Hill|
|10:45-11:20am||Industry Keynote: What You Didn’t Learn About Machine Learning in School||Wayne Thompson, SAS|
|11:25am-12:30pm||Spotlight Poster Talks (3 minutes each)|
|12:30-1:45pm||Lunch and posters|
|1:45-2:15pm||Adaptive Deep Reuse for Deep Learning||Xipeng Shen, N.C. State University|
|2:15-2:45pm||Stacking Audience Models – Using an Ensemble Approach for Predictive Modeling||Susan Xia, Valassis|
|2:45-3:15pm||Academic Keynote: Machine Learning from De-Identified Coded Electronic Health Records (EHRs)||David Page, Duke University|
|3:30-4:00pm||Biomedical Image Understanding and EHRs at LifeOmic: Harnessing the Power of the Cloud||Matthew Phillips, LifeOmic|
|4:00-4:30pm||Spotlight Poster Talks (3 minutes each)|
|4:30-5:15pm||Posters and Networking|