- About
- Events
- Calendar
- Graduation Information
- Cornell Tech Colloquium
- Student Colloquium
- BOOM
- Fall 2023 Colloquium
- Conway-Walker Lecture Series
- Salton 2023 Lecture Series
- Seminars / Lectures
- Big Red Hacks
- Cornell University High School Programming Contests 2023
- Game Design Initiative
- CSMore: The Rising Sophomore Summer Program in Computer Science
- Explore CS Research
- ACSU Research Night
- Cornell Junior Theorists' Workshop
- People
- Courses
- Research
- Undergraduate
- M Eng
- MS
- PhD
- Admissions
- Current Students
- Computer Science Graduate Office Hours
- Business Card Policy
- Cornell Tech
- Curricular Practical Training
- Exam Scheduling Guidelines
- Fellowship Opportunities
- Field of Computer Science Ph.D. Student Handbook
- Graduate TA Handbook
- Field A Exam Summary Form
- Graduate School Forms
- Instructor / TA Application
- Ph.D. Requirements
- Ph.D. Student Financial Support
- Special Committee Selection
- Travel Funding Opportunities
- The Outside Minor Requirement
- Diversity and Inclusion
- Graduation Information
- CS Graduate Minor
- Outreach Opportunities
- Parental Accommodation Policy
- Special Masters
- Student Spotlights
- Contact PhD Office
Blackwell Dominance in Large Samples* (joint w/Xiaosheng Mu, Luciano Pomatto & Philipp Strack)
We study repeated independent Blackwell experiments; standard examples include drawing multiple samples from a population, or performing a measurement in different locations. In the baseline setting of a binary state of nature, we compare experiments in terms of their informativeness in large samples. Addressing a question due to Blackwell (1951) we show that generically, an experiment is more informative than another in large samples if and only if it has higher Rényi divergences. As an application of our techniques we in addition provide a novel characterization of kth-order stochastic dominance as second-order stochastic dominance of large i.i.d. sums.