POPL 2023
Sun 15 - Sat 21 January 2023
Boston, Massachusetts, United States
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- Introduction to the tensor-programs framework, a PL approach that helps analyse theoretical properties of deep learning.
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POPL 2023
(
series
) /
CPP 2023 (
series
) /
CPP 2023
/
Program Committee
CPP
Brigitte Pientka
PC Chair
McGill University
Canada
Steve Zdancewic
PC Chair
University of Pennsylvania
United States
Reynald Affeldt
National Institute of Advanced Industrial Science and Technology (AIST)
Japan
Koen Claessen
Chalmers University of Technology
Sweden
Ranald Clouston
ANU
Australia
Leonardo de Moura
Microsoft Research
United States
Tej Chajed
VMware Research
United States
Xinyu Feng
Nanjing University
China
Denis Firsov
Tallinn University of Technology
Estonia
Yannick Forster
Inria
France
Milos Gligoric
University of Texas at Austin
United States
Stephane Graham-Lengrand
SRI
United States
Elsa Gunter
University of Illinois
United States
Chris Hawblitzel
Microsoft Research
United States
Chantal Keller
Université Paris Saclay
France
Marie Kerjean
CNRS, Université Sorbonne Paris Nord
France
Yoonseung Kim
Yale University
United States
Kenji Maillard
Inria Nantes
France
César Muñoz
Amazon Web Services
United States
Tobias Nipkow
Technische Universität München
Germany
Lawrence Paulson
University of Cambridge
United Kingdom
Anja Petković Komel
TU Wien, Vienna
Austria
Clément Pit-Claudel
EPFL
Switzerland
Pierre-Marie Pédrot
INRIA
France
Christine Rizkallah
University of Melbourne
Australia
Cody Roux
AWS
United States
Kazuhiko Sakaguchi
Inria
France
Anna Slobodova
Intel
United States
Aaron Stump
University of Iowa
United States
René Thiemann
University of Innsbruck
Austria
Amin Timany
Aarhus University
Denmark
Josef Urban
Czech Technical University in Prague
Czechia
Viktor Vafeiadis
MPI-SWS
Germany
Yuting Wang
Shanghai Jiao Tong University
China
Tjark Weber
Uppsala University
Sweden
x
Sun 25 May 17:53
