REMS-DeepSpec 2020
Mon 15 - Tue 16 June 2020
co-located with
PLDI 2020
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Room information: MAPL live stream
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Tue 16 Jun
Displayed time zone:
Pacific Time (US & Canada)
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08:00 - 10:00
Graph Neural Networks for Program Reasoning
MAPL
at
MAPL live stream
Chair(s):
Ke Wang
Visa Research
08:00
30m
Talk
Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs
MAPL
Elizabeth Dinella
University of Pennsylvania
08:30
60m
Tutorial
A Gentle Tutorial on Graph Neural Networks and Its Application to Programming Languages
MAPL
Yizhou Sun
UCLA
09:30
30m
Talk
LambdaNet: Probabilistic Type Inference using Graph Neural Networks
MAPL
Işıl Dillig
University of Texas at Austin, USA
10:00 - 10:30
Break
MAPL
at
MAPL live stream
10:30 - 11:30
Deep Learning and Program Verification
MAPL
at
MAPL live stream
Chair(s):
Xujie Si
McGill University, Canada
10:30
30m
Talk
An Abstraction-Based Framework for Neural Network Verification
MAPL
Guy Katz
Hebrew University
11:00
30m
Talk
Generating Correctness Proofs with Neural Networks
MAPL
Alex Sanchez-Stern
University of California, San Diego
,
Yousef Alhessi
University of California, San Diego
,
Lawrence Saul
University of California, San Diego
,
Sorin Lerner
University of California at San Diego, USA
11:30 - 12:30
Compilers for Deep Learning Frameworks
MAPL
at
MAPL live stream
Chair(s):
Charles Sutton
Google Research
11:30
30m
Talk
On the Challenges in Programming Mixed-Precision Deep Neural Networks
MAPL
Ruizhe Zhao
Imperial College London
,
Wayne Luk
Imperial College London
,
Chao Xiong
Corerain Technologies
,
Xinyu Niu
Corerain Technologies
,
Kuen Hung Tsoi
Corerain Technologies
12:00
30m
Talk
Semi-static Type, Shape and Symbolic Shape Inference for Dynamic Computation Graphs
MAPL
Momoko Hattori
The University of Tokyo
,
Shimpei Sawada
Preferred Networks
,
Shinichiro Hamaji
Preferred Networks
,
Masahiro Sakai
Preferred Networks
,
Shunsuke Shimizu
Preferred Networks
12:30 - 13:00
Break
MAPL
at
MAPL live stream
13:00 - 14:00
Keynote Talk
MAPL
at
MAPL live stream
Chair(s):
Justin Gottschlich
Intel Labs / Penn
13:00
60m
Talk
Program Optimization for Machine Learning
MAPL
Alex Aiken
Stanford University, USA
14:00 - 15:00
Formal Methods and Reinforcement Learning
MAPL
at
MAPL live stream
Chair(s):
Aws Albarghouthi
University of Wisconsin-Madison, USA
14:00
30m
Talk
Learned Garbage Collection
MAPL
Lujing Cen
MIT CSAIL
,
Ryan Marcus
MIT CSAIL / Intel Labs
,
Hongzi Mao
MIT CSAIL
,
Justin Gottschlich
Intel Labs / Penn
,
Mohammad Alizadeh
MIT CSAIL
,
Tim Kraska
MIT CSAIL
14:30
30m
Talk
Trustworthy Autonomy through Program Synthesis
MAPL
Swarat Chaudhuri
Rice University
15:00 - 15:30
Break
MAPL
at
MAPL live stream
15:30 - 17:00
Program Synthesis
MAPL
at
MAPL live stream
Chair(s):
Satish Chandra
Facebook
15:30
30m
Talk
Neurosymbolic Reasoning and the Third Wave of Program Synthesis
MAPL
Armando Solar-Lezama
Massachusetts Institute of Technology, USA
16:00
30m
Talk
Learning Quantitative Representation Synthesis
MAPL
Mayur Patil
University of California, Riverside
,
Farzin Houshmand
University of California, Riverside
,
Mohsen Lesani
University of California, Riverside
16:30
30m
Talk
Towards Human-Like Program Synthesis
MAPL
Rishabh Singh
Google Brain
17:00 - 17:30
Break
MAPL
at
MAPL live stream
Tue 16 Jun
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MAPL live stream
MAPL
Graph Neural Networks for Program Reasoning
MAPL
Break
MAPL
Deep Learning and Program Verification
MAPL
Compilers for Deep Learning Frameworks
MAPL
Break
MAPL
Keynote Talk
MAPL
Formal Methods and Reinforcement Learning
MAPL
Break
MAPL
Program Synthesis
MAPL
Break
Tue 16 Jun
Displayed time zone:
Pacific Time (US & Canada)
change
Room
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MAPL live stream
MAPL
Hoppity: Learning Graph Transformations to Detect and Fix Bugs in Programs
08:00 - 08:30
MAPL
A Gentle Tutorial on Graph Neural Networks and Its Application to Progr ...
08:30 - 09:30
MAPL
LambdaNet: Probabilistic Type Inference using Graph Neural Networks
09:30 - 10:00
MAPL
An Abstraction-Based Framework for Neural Network Verification
10:30 - 11:00
MAPL
Generating Correctness Proofs with Neural Networks
11:00 - 11:30
MAPL
On the Challenges in Programming Mixed-Precision Deep Neural Networks
11:30 - 12:00
MAPL
Semi-static Type, Shape and Symbolic Shape Inference for Dynamic Comput ...
12:00 - 12:30
MAPL
Program Optimization for Machine Learning
13:00 - 14:00
MAPL
Learned Garbage Collection
14:00 - 14:30
MAPL
Trustworthy Autonomy through Program Synthesis
14:30 - 15:00
MAPL
Neurosymbolic Reasoning and the Third Wave of Program Synthesis
15:30 - 16:00
MAPL
Learning Quantitative Representation Synthesis
16:00 - 16:30
MAPL
Towards Human-Like Program Synthesis
16:30 - 17:00
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Fri 8 Nov 22:55