- About
- Events
- Events
- Calendar
- Graduation Information
- Cornell Learning Machines Seminar
- Student Colloquium
- BOOM
- Spring 2025 Colloquium
- Conway-Walker Lecture Series
- Salton 2024 Lecture Series
- Seminars / Lectures
- Big Red Hacks
- Cornell University / Cornell Tech - High School Programming Workshop and Contest 2025
- Game Design Initiative
- CSMore: The Rising Sophomore Summer Program in Computer Science
- Explore CS Research
- ACSU Research Night
- Cornell Junior Theorists' Workshop 2024
- People
- Courses
- Research
- Undergraduate
- M Eng
- MS
- PhD
- PhD
- Admissions
- Current Students
- Computer Science Graduate Office Hours
- Advising Guide for Research Students
- Business Card Policy
- Cornell Tech
- Curricular Practical Training
- A & B 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
- Travel Reimbursement Guide
- The Outside Minor Requirement
- Robotics Ph. D. prgram
- Diversity and Inclusion
- Graduation Information
- CS Graduate Minor
- Outreach Opportunities
- Parental Accommodation Policy
- Special Masters
- Student Spotlights
- Contact PhD Office
Fooling Polytopes
Abstract: We give an explicit pseudorandom generator with seed length poly(log m, 1/\delta) * log n that \delta-fools the class of all m-facet polytopes over {0,1}^n. The previous best seed length had linear dependence on m. As a corollary, we obtain a deterministic quasipolynomial time algorithm for approximately counting the number of feasible solutions of general {0,1}-integer programs.
Joint work with Ryan O'Donnell (CMU) and Li-Yang Tan (Stanford).
Bio: Rocco Servedio is a professor and chair of the Department of Computer Science at Columbia University, where he does research in theoretical computer science. His main research interests lie in computational complexity theory, computational learning theory, property testing, and the role of randomness in computation.