This workshop is being live streamed on our website. Full participation (including the capacity to ask questions) will be available via Zoom webinar. 

All talk times are in Pacific Time. 

–
Welcome Remarks
–
Crash Course on Probabilistically Checkable Proofs (PCP): Introduction

Irit Dinur, Weizmann Institute
Video
–
Break
–
Remarks on the Discrete Cube

Ramon van Handel, Princeton University
Video
–
Introductions
–
Crash Course on Probabilistically Checkable Proofs (PCP): A Self-Contained Proof of a Weak PCP Theorem (Exponential-Sized)

Dana Moshkovitz, University of Texas at Austin
Video
–
Break
–
Remarks on the Discrete Cube

Ramon van Handel, Princeton University
Video
–
Introductions
–
Crash Course on Probabilistically Checkable Proofs (PCP): Parallel Repetition

Irit Dinur, Weizmann Institute
Video
–
Break
–
Remarks on the Discrete Cube

Ramon van Handel, Princeton University
Video
–
Break
–
Sketching High-Dimensional Data

Jelani Nelson, UC Berkeley
Video
–
Introductions
–
Crash Course on Probabilistically Checkable Proofs (PCP): Optimal Inapproximability Results

Dana Moshkovitz, University of Texas at Austin
Video
–
Break
–
Remarks on the Discrete Cube

Ramon van Handel, Princeton University
Video
–
Break
–
Sketching High-Dimensional Data

Jelani Nelson, UC Berkeley
Video
–
Introductions
–
Statistical Physics and Computation in High Dimension

Florent Krzakala, ENS,
Lenka Zdeborova, CEA Saclay
Video
–
Break
–
Recent Progress in High-Dimensional Learning

Ankur Moitra, MIT
Video
–
Break
–
Sketching High-Dimensional Data

Jelani Nelson, UC Berkeley
Video
–
Introductions
–
Statistical Physics and Computation in High Dimension

Florent Krzakala, ENS,
Lenka Zdeborova, CEA Saclay
Video
–
Break
–
Recent Progress in High-Dimensional Learning

Ankur Moitra, MIT
Video
–
Break
–
Sketching High-Dimensional Data

Jelani Nelson, UC Berkeley
Video
–
Introductions
–
Statistical Physics and Computation in High Dimension

Florent Krzakala, ENS,
Lenka Zdeborova, CEA Saclay
Video
–
Break
–
Recent Progress in High-Dimensional Learning

Ankur Moitra, MIT
Video
–
Reception
–
Introductions
–
Statistical Physics and Computation in High Dimension

Florent Krzakala, ENS,
Lenka Zdeborova, CEA Saclay
Video
–
Break
–
Recent Progress in High-Dimensional Learning

Ankur Moitra, MIT
Video