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56th Annual ACM Symposium on Theory of Computing (STOC 2024),
June 24–28, 2024,
Vancouver, BC, Canada
Frontmatter
Keynotes
1A (Best Papers)
2A
2B
2C
2D
3A
3B
3C
3D
4A
4B
4C
4D
Maximum Weight Independent Set in Graphs with no Long Claws in Quasi-Polynomial Time
Peter Gartland,
Daniel Lokshtanov,
Tomáš Masařík,
Marcin Pilipczuk,
Michał Pilipczuk, and
Paweł Rzążewski
(University of California at Santa Barbara, USA; University of Warsaw, Poland; IT University of Copenhagen, Copenhagen, Denmark; Warsaw University of Technology, Poland)
Publisher's Version
Packing Even Directed Circuits Quarter-Integrally
Maximilian Gorsky,
Ken-ichi Kawarabayashi,
Stephan Kreutzer, and
Sebastian Wiederrecht
(TU Berlin, Berlin, Germany; National Institute of Informatics, Tokyo, Japan; University of Tokyo, Tokyo, Japan; Institute for Basic Science, Daejeon, South Korea)
Publisher's Version
5A
5B
5C
6A
6B
6C
6D
7A
Almost-Linear Time Algorithms for Incremental Graphs: Cycle Detection, SCCs, s-t Shortest Path, and Minimum-Cost Flow
Li Chen,
Rasmus Kyng,
Yang P. Liu,
Simon Meierhans, and
Maximilian Probst Gutenberg
(Carnegie Mellon University, USA; ETH Zurich, Switzerland; Institute for Advanced Study, Princeton, USA)
Publisher's Version
7B
7C
7D
Learning Shallow Quantum Circuits
Hsin-Yuan Huang,
Yunchao Liu,
Michael Broughton,
Isaac Kim,
Anurag Anshu,
Zeph Landau, and
Jarrod R. McClean
(California Institute of Technology, USA; Google Quantum AI, USA; University of California at Berkeley, USA; University of California at Davis, USA; Harvard University, USA)
Publisher's Version
8A
8B
8C
8D
9A (Best Student Papers)
10A
Understanding the Cluster Linear Program for Correlation Clustering
Nairen Cao,
Vincent Cohen-Addad,
Euiwoong Lee,
Shi Li,
Alantha Newman, and
Lukas Vogl
(Boston College, USA; Google Research, France; University of Michigan, USA; Nanjing University, China; CNRS - Université Grenoble Alpes, France; EPFL, Lausanne, Switzerland)
Publisher's Version
Info
10B
10C
10D
A New Information Complexity Measure for Multi-pass Streaming with Applications
Mark Braverman,
Sumegha Garg,
Qian Li,
Shuo Wang,
David P. Woodruff, and
Jiapeng Zhang
(Princeton University, USA; Rutgers University, USA; Shenzhen Research Institute of Big Data, China; Shanghai Jiao Tong University, China; Carnegie Mellon University, USA; University of Southern California, USA)
Publisher's Version
11A
11B
No Distributed Quantum Advantage for Approximate Graph Coloring
Xavier Coiteux-Roy,
Francesco d'Amore,
Rishikesh Gajjala,
Fabian Kuhn,
François Le Gall,
Henrik Lievonen,
Augusto Modanese,
Marc-Olivier Renou,
Gustav Schmid, and
Jukka Suomela
(TU Munich, Germany; Munich Center for Quantum Science and Technology, Germany; Aalto University, Finland; Bocconi University, Italy; Indian Institute of Science, India; University of Freiburg, Freiburg, Germany; Nagoya University, Nagoya, Japan; Inria, France; Université Paris-Saclay, France; Institut Polytechnique de Paris, France)
Publisher's Version
11C
11D
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