Ellen Vitercik

About me:

I am a fourth-year PhD student in the Computer Science Department at Carnegie Mellon University, where I am advised by Nina Balcan and Tuomas Sandholm. I am broadly interested in theoretical computer science, machine learning theory, computational economics, and artificial intelligence. I am supported by the NSF Graduate Research Fellowship Program (NSF GRFP).

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Algorithmic greenlining: An approach to increase diversity

with Christian Borgs, Jennifer Chayes, Nika Haghtalab, and Adam Tauman Kalai
AIES 2019

Dispersion for Data-Driven Algorithm Design, Online Learning, and Private Optimization

with Maria-Florina Balcan and Travis Dick
FOCS 2018
Preliminary versions in the ICML Workshop on Private Secure Machine Learning 2017 and the ICML Workshop on Privacy in Machine Learning and Artificial Intelligence 2018

Learning to Branch

with Maria-Florina Balcan, Travis Dick, and Tuomas Sandholm
ICML 2018

A General Theory of Sample Complexity for Multi-Item Profit Maximization

with Maria-Florina Balcan and Tuomas Sandholm
EC 2018
Preliminary versions in the EC Workshop on Algorithmic Game Theory and Data Science '17 and the AAMAS-IJCAI Workshop on Agents and Incentives in Artificial Intelligence '18

Synchronization Strings: Channel Simulations and Interactive Coding for Insertions and Deletions

with Bernhard Haeupler and Amirbehshad Shahrasbi
ICALP 2018

Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems

with Maria-Florina Balcan, Vaishnavh Nagarajan, and Colin White
COLT 2017

Sample Complexity of Automated Mechanism Design

with Maria-Florina Balcan and Tuomas Sandholm
NIPS 2016

Learning Combinatorial Functions from Pairwise Comparisons

with Maria-Florina Balcan and Colin White
COLT 2016

Machine Learning in Automated Mechanism Design for Pricing and Auctions

ICML 2018 tutorial

Differentially Private Algorithm and Auction Configuration

CMU Theory Lunch 2017
Subset of material from Dispersion for Data-Driven Algorithm Design, Online Learning, and Private Optimization

CMU 10-701: Introduction to Machine Learning

TA for Ziv Bar-Joseph and Barnabás Póczos
Fall 2017
Won the Machine Learning Department's Teaching Assistant of the Year award.

Columbia COMS W3261: Computer Science Theory

TA for Tal Malkin
Spring 2015

The photo of rust at the top of the page is by Carol Murray. See the full photo here and all of her photos here.