Laure Thompson

Cornell University

237 Gates Hall

laurejt [at] cs [dot] cornell [dot] edu

I am a PhD candidate in Computer Science at Cornell University. My research interests are in the areas of natural language processing, machine learning, and digital humanities.

My advisor is David Mimno. I develop computational tools for the digital humanities, with a particular emphasis on classics and classical archaeology. My current works focuses on how preprocessing intentional data modification can be used to both understand and change what models learn. In practice, my research uses a wide range of corpora from texts of science fiction novels and the Patrologia Graeca to images of avante-garde journals and magical gems.

I am a recipient of a NSF Graduate Research Fellowship and Cornell University Fellowship.

Publications

Authorless Topic Models: Biasing Models Away from Known Structure.
Laure Thompson and David Mimno.
Conference on Computational Linguistics (COLING), 2018.
Best Paper Award: Best NLP Engineering Experiment.
[pdf] [repo]

The Strange Geometry of Skip-Gram with Negative Sampling.
David Mimno and Laure Thompson.
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017.
Outstanding Paper (Best Paper Honorable Mention).
[pdf]

Quantifying the Effects of Text Duplication on Semantic Models.
Alexandra Schofield, Laure Thompson, and David Mimno.
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017.
[pdf]

Vale: Verifying High-Performance Crytographic Assembly Code.
Barry Bond, Chris Hawblitzel, Manos Kapritsos, Rustan Leino, Jay Lorch, Bryan Parno,
Ashay Rane, Srinath Setty, and Laure Thompson.
USENIX Security Symposium, 2017.
Distinguished Paper Award.
[pdf]

A Coalgebraic Decision Procedure for NetKAT.
Nate Foster, Dexter Kozen, Matthew Milano, Alexandra Silva, and Laure Thompson.
ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL), 2015.
[pdf]

Talks

Authorless Topic Models: Biasing Models Away from Known Structure.
Poster presentation.
Ninth Annual Conference on New Directions in Analyzing Text as Data (TADA), 2018.

Authorless Topic Models: Biasing Models Away from Known Structure.
Conference on Computational Linguistics (COLING), 2018.

Data Analysis for the Humanities.
Cornell Summer Graduate Fellowship program, 2018.

Bilingual Topic Modeling in the Patrologia Graeca
Joint talk with David Mimno.
Future Philologies: Digital Directions in Ancient World Text, 2018.

The Strange Geometry of Skip-Gram with Negative Sampling: A story of geometric observations.
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017.

Measuring Oracular Authenticity: Distinguishing the Historical from the Legendary in the Oracles of Delphi.
LAWDNY Digital Antiquity Workshop 2016 at ISAW.

A Coalgebraic Decision Procedure for NetKAT.
ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL), 2015.

Teaching Assistantships

Cornell University

Text Mining for History and Literature (INFO 3350 / INFO 6350): Fall 2017, instructor: David Mimno

System Security (CS 5430): Spring 2015, instructor: Michael Clarkson

University of Washington

Introduction to Compiler Construction (CSE401): Winter 2013, instructor: Michael Ringenburg

Software Design and Implementation (CSE331): Winter 2012, instructor: Hal Perkins

Last updated October 2018.

I stole this page from Franzi Roesner.