Modern data analysis presents a variety of challenges, including the size, the dimensionality, the complexity, and the multiple-modality of the data. In an attempt to keep pace with these growing challenges, data scientists combine tools inspired from mathematics, from computer science, and from statistics. This TRIPODS Summer Bootcamp will provide attendees a hands-on introduction to emerging techniques for using topology with machine learning for the purpose of data analysis.
Topological and machine learning techniques potentially play complimentary roles for analyzing data. In topological data analysis, one leverages the fact that the shape of the data often reflects important and interpretable patterns within, although topological techniques alone typically cannot match the predictive power of machine learning. By contrast, machine learning algorithms provide state-of-the-art accuracies on predictive tasks, but the manner by which they arrive at a prediction is often difficult to interpret. Machine learning would benefit if one could use mathematics to provide more interpretability, even in exchange for reduced predictive power. There are by now a variety of ways to combine topology with machine learning, and the diversity of such approaches is growing. The goal of the TRIPODS Summer Bootcamp is to expose attendees to current tools combining topology and machine learning. The bootcamp will focus not only the successes of such algorithms but also on their inherent challenges, in order to inspire the development of novel approaches.
The bootcamp will consist of a hands-on tutorial during days 1-3, and a research conference during days 4-5.
Days 1-3: Introductory tutorial on applied topology and machine learning
The first three days of the bootcamp will include an introductory tutorial on applied topology, on machine learning, and on the marriage between the two. The featured topic from applied topology will be persistent homology, and the featured topic from machine learning will be classical algorithms such as clustering, support vector machines (SVM), and random forests. Finally, featured topics for combining persistent homology with machine learning will include the bottleneck or Wasserstein distances, persistence landscapes, and persistence images. The tutorial will emphasize hands-on coding exercises with real data. Participants will compare the performance and interpretability of standard algorithms on a variety of machine learning tasks, and they will also create and test variants of their own invention.
We will be doing computational exercises to accompany the bootcamp. Please see our tutorial at https://github.com/ICERM-TRIPODS-Top-ML/Top-ML/wiki and our code at https://github.com/ICERM-TRIPODS-Top-ML/Top-ML.
Days 4-5: Research conference on topology and machine learning
The final two days of the bootcamp will feature a research conference on current trends in topology and machine learning. The conference will be targeted at a more expert audience not necessarily present at the preparatory bootcamp tutorials during the first three days.
Confirmed Speakers & Participants
- Henry Adams
- Shaun Ault
- Elaine Ayo
- Mikhail Belkin
- Jeffrey Brock
- Mathieu Carrière
- Samir Chowdhury
- David Damiano
- Matthew Drnevich
- Tegan Emerson
- Mahmoodreza Jahanseir
- Marija Jelic
- Karim Karimov
- karthik kashinath
- Lara Kassab
- IRENE KIM
- Katherine Kinnaird
- Iryna Kuz
- Michael Marlett
- Melissa McGuirl
- Anthea Monod
- Alexander Neshitov
- Kristine Pelatt
- Archit Rathore
- Carlos Ronchi
- Bjorn Sandstede
- Matthew Schoenbauer
- Don Sheehy
- Joshua Shrader
- Yitzchak Solomon
- Courtney Thatcher
- Sarah Tymochko
- Niels uit de Bos
- Bei Wang
- Lin Yan
- Lori Ziegelmeier
Monday, August 6, 2018
Tuesday, August 7, 2018
Wednesday, August 8, 2018
Thursday, August 9, 2018
Friday, August 10, 2018
- Acceptable Costs
- 1 roundtrip between your home institute and ICERM
- Flights on U.S. or E.U. airlines – economy class to either Providence airport (PVD) or Boston airport (BOS)
- Ground Transportation to and from airports and ICERM.
- Unacceptable Costs
- Flights on non-U.S. or non-E.U. airlines
- Seats in economy plus, business class, or first class
- Change ticket fees of any kind
- Multi-use bus passes
- Meals or incidentals
- Advance Approval Required
- Personal car travel to ICERM from outside New England
- Multiple-destination plane ticket; does not include layovers to reach ICERM
- Arriving or departing from ICERM more than a day before or day after the program
- Multiple trips to ICERM
- Rental car to/from ICERM
- Flights on a Swiss, Japanese, or Australian airlines
- Arriving or departing from airport other than PVD/BOS or home institution's local airport
- 2 one-way plane tickets to create a roundtrip (often purchased from Expedia, Orbitz, etc.)
- Reimbursement Request Form
Refer to the back of your ID badge for more information. Checklists are available at the front desk.
- Reimbursement Tips
- Scanned original receipts are required for all expenses
- Airfare receipt must show full itinerary and payment
- ICERM does not offer per diem or meal reimbursement
- Allowable mileage is reimbursed at prevailing IRS Business Rate and trip documented via pdf of Google Maps result
- Keep all documentation until you receive your reimbursement!
- Reimbursement Timing
6 - 8 weeks after all documentation is sent to ICERM. All reimbursement requests are reviewed by numerous central offices at Brown who may request additional documentation.
- Reimbursement Deadline
Submissions must be received within 30 days of ICERM departure to avoid applicable taxes. Submissions after thirty days will incur applicable taxes. No submissions are accepted more than six months after the program end.