SCS Recruiting Seminar: Ellen Vitercik

Event Details
  • Date/Time:
    • Tuesday January 19, 2021 - Wednesday January 20, 2021
      11:00 am - 11:59 am
  • Location: BlueJeans
  • Phone:
  • URL:
  • Email:
  • Fee(s):
    N/A
  • Extras:
Contact

Tess Malone, Communications Officer

tess.malone@cc.gatech.edu

Summaries

Summary Sentence: Integrating Machine Learning into Algorithm Design

Full Summary: No summary paragraph submitted.

Media
  • Ellen Vitercik Ellen Vitercik
    (image/jpeg)

TITLE:  Integrating Machine Learning into Algorithm Design

ABSTRACT:

An important property of those algorithms that are typically used in practice is broad applicability — the ability to solve problems across diverse domains. However, the default, out-of-the-box performance of these algorithms can be unsatisfactory with slow runtime, poor solution quality, and even negative long-term social ramifications. In practice, there is often ample data available about the types of problems an algorithm will be run on, data that can potentially be harnessed to fine-tune the algorithm’s performance. We therefore need principled approaches for using this data to obtain strong application-specific performance guarantees.

In this talk, I will give an overview of my research that provides practical methods built on firm theoretical foundations for incorporating machine learning and optimization into the process of algorithm design, selection, and configuration. I will describe my contributions across several diverse domains, including integer programming, clustering, mechanism design, and computational biology. As I will demonstrate, these seemingly disparate areas are connected by overarching structure which implies broadly-applicable guarantees.

 

BIO:

Ellen Vitercik is a Ph.D. student at Carnegie Mellon University, where she is co-advised by Maria-Florina Balcan and Tuomas Sandholm. Her research revolves around artificial intelligence, algorithm design, and the interface between economics and computation with a particular focus on machine learning theory. Among other honors, she is a recipient of the Exemplary Artificial Intelligence Track Paper Award at EC’19, the Best Presentation by a Student or Postdoctoral Researcher Award at EC’19, the NSF Graduate Research Fellowship, the IBM PhD Fellowship, the Fellowship in Digital Health from CMU’s Center for Machine Learning and Health, and the Teaching Assistant of the Year Award from CMU’s Machine Learning Department.

Watch here.

 

Additional Information

In Campus Calendar
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Groups

College of Computing, School of Computer Science

Invited Audience
Faculty/Staff, Postdoc, Public, Graduate students, Undergraduate students
Categories
Seminar/Lecture/Colloquium
Keywords
No keywords were submitted.
Status
  • Created By: Tess Malone
  • Workflow Status: Published
  • Created On: Jan 15, 2021 - 11:47am
  • Last Updated: Jan 19, 2021 - 10:30am