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Journal of the ACM

Volume 71, Issue 2

April 2024

The Journal of the ACM (JACM) provides coverage of the most significant work on principles of computer science, broadly construed. The scope of research covered encompasses contributions of lasting value to any area of computer science. To be accepted, a paper must be judged to be truly outstanding in its field. JACM is interested in work in core computer science and in work at the boundaries, both the boundaries of subdisciplines of computer science and the boundaries between computer science and other fields.

Editor-in-Chief:

Venkatesan Guruswami

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ACM Updates Its Peer Review Policy

ACM is pleased to announce that its Publications Board has approved an updated Peer Review Policy. If you have any questions regarding the update, the associated FAQ addresses topics such as confidentiality, the use of large language models in the peer review process, conflicts of interest, and several other relevant concerns. If there are any issues that are not addressed in the FAQ, please contact ACM’s Director of Publications, Scott Delman.

New ACM Policy on Authorship

ACM has a new Policy on Authorship, covering a range of key topics, including the use of generative AI tools. Please familiarize yourself with the new policy and the associated list of Frequently Asked Questions.

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Latest Issue

Volume 71, Issue 2 April 2024
ISSN:0004-5411
EISSN:1557-735X
View Table of Contents
research-article
Open Access
A Compositional Theory of Linearizability
- Arthur Oliveira Vale
  Yale University, New Haven, USA
  ,
- Zhong Shao
  Yale University, New Haven, USA
  ,
- Yixuan Chen
  Yale University, New Haven, USA
April 2024Article No.: 14 pp 1-107 https://doi.org/10.1145/3643668
research-article
Learning to Branch: Generalization Guarantees and Limits of Data-Independent Discretization
- Maria-Florina Balcan
  Carnegie Mellon University, Pittsburgh, United States
  ,
- Travis Dick
  Google, New York, United States
  ,
- Tuomas Sandholm
  Carnegie Mellon University, Pittsburgh, United States, Strategic Machine, Inc., Pittsburgh, United States, Strategy Robot, Inc., Pittsburgh, United States, and Optimized Markets, Inc., Pittsburgh, United States
  ,
- Ellen Vitercik
  Stanford University, Stanford, United States
April 2024Article No.: 13 pp 1-73 https://doi.org/10.1145/3637840

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Latest Issue

Volume 71, Issue 2 April 2024
ISSN:0004-5411
EISSN:1557-735X
View Table of Contents
research-article
Open Access
A Compositional Theory of Linearizability
- Arthur Oliveira Vale
  Yale University, New Haven, USA
  ,
- Zhong Shao
  Yale University, New Haven, USA
  ,
- Yixuan Chen
  Yale University, New Haven, USA
April 2024Article No.: 14 pp 1-107 https://doi.org/10.1145/3643668
research-article
Learning to Branch: Generalization Guarantees and Limits of Data-Independent Discretization
- Maria-Florina Balcan
  Carnegie Mellon University, Pittsburgh, United States
  ,
- Travis Dick
  Google, New York, United States
  ,
- Tuomas Sandholm
  Carnegie Mellon University, Pittsburgh, United States, Strategic Machine, Inc., Pittsburgh, United States, Strategy Robot, Inc., Pittsburgh, United States, and Optimized Markets, Inc., Pittsburgh, United States
  ,
- Ellen Vitercik
  Stanford University, Stanford, United States
April 2024Article No.: 13 pp 1-73 https://doi.org/10.1145/3637840