Friday, September 11, 2026
12:30 PM – 1:30 PM EDT
Machine Learning Lunch: Causal Risk Minimization for High-Dimensional Text Treatments
About this event
A Vector and U of T machine learning lunch on causal inference with high-dimensional text treatments, led by Nikita Dhawan. The session is part of a weekly research-talk series for Toronto's ML community.
Machine Learning Lunch at Vector hosts Nikita Dhawan for a research talk on causal risk minimization when the treatment is high-dimensional text. The session examines a machine-learning framing of causal estimation and the practical challenge of drawing conclusions when interventions have many possible variations.
It is part of a weekly, community-oriented lunch series for people in the Vector Institute and University of Toronto ecosystem, with a short student talk, questions and informal discussion afterward. The official schedule lists this special Vector Community Day session from 12:30 PM to 1:30 PM on the Schwartz Reisman Institute's 11th floor. Lunch is provided. An optional attendance form is available through the official series page.
Organized by
A weekly University of Toronto and Vector Institute community lunch series for graduate students, researchers and others working across machine learning theory and applications.