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144 Publications


2020 | Published | Conference Paper | IST-REx-ID: 8383
Alistarh, Dan-Adrian, James Aspnes, Faith Ellen, Rati Gelashvili, and Leqi Zhu. “Brief Announcement: Why Extension-Based Proofs Fail.” In Proceedings of the 39th Symposium on Principles of Distributed Computing, 54–56. Association for Computing Machinery, 2020. https://doi.org/10.1145/3382734.3405743.
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2020 | Published | Conference Paper | IST-REx-ID: 7213 | OA
Bhatia, Sumit, Bapi Chatterjee, Deepak Nathani, and Manohar Kaul. “A Persistent Homology Perspective to the Link Prediction Problem.” In Complex Networks and Their Applications VIII, 881:27–39. Springer Nature, 2020. https://doi.org/10.1007/978-3-030-36687-2_3.
[Submitted Version] View | Files available | DOI | WoS
 

2020 | Published | Journal Article | IST-REx-ID: 7224 | OA
Rybicki, Joel, Nerea Abrego, and Otso Ovaskainen. “Habitat Fragmentation and Species Diversity in Competitive Communities.” Ecology Letters. Wiley, 2020. https://doi.org/10.1111/ele.13450.
[Published Version] View | Files available | DOI | WoS
 

2020 | Published | Conference Paper | IST-REx-ID: 7272 | OA
Arbel-Raviv, Maya, Trevor A Brown, and Adam Morrison. “Getting to the Root of Concurrent Binary Search Tree Performance.” In Proceedings of the 2018 USENIX Annual Technical Conference, 295–306. USENIX Association, 2020.
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2020 | Published | Conference Paper | IST-REx-ID: 8724 | OA
Konstantinov, Nikola H, Elias Frantar, Dan-Adrian Alistarh, and Christoph Lampert. “On the Sample Complexity of Adversarial Multi-Source PAC Learning.” In Proceedings of the 37th International Conference on Machine Learning, 119:5416–25. ML Research Press, 2020.
[Published Version] View | Files available | arXiv
 

2020 | Published | Conference Paper | IST-REx-ID: 9198 | OA
Shevchenko, Aleksandr, and Marco Mondelli. “Landscape Connectivity and Dropout Stability of SGD Solutions for Over-Parameterized Neural Networks.” In Proceedings of the 37th International Conference on Machine Learning, 119:8773–84. ML Research Press, 2020.
[Published Version] View | Files available | arXiv
 

2019 | Published | Conference Paper | IST-REx-ID: 6673 | OA
Alistarh, Dan-Adrian, Giorgi Nadiradze, and Nikita Koval. “Efficiency Guarantees for Parallel Incremental Algorithms under Relaxed Schedulers.” In 31st ACM Symposium on Parallelism in Algorithms and Architectures, 145–54. ACM Press, 2019. https://doi.org/10.1145/3323165.3323201.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2019 | Published | Conference Poster | IST-REx-ID: 6485
Koval, Nikita, Dan-Adrian Alistarh, and Roman Elizarov. Lock-Free Channels for Programming via Communicating Sequential Processes. Proceedings of the 24th Symposium on Principles and Practice of Parallel Programming. ACM, 2019. https://doi.org/10.1145/3293883.3297000.
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2019 | Published | Conference Paper | IST-REx-ID: 5947 | OA
Chatterjee, Bapi, Sathya Peri, Muktikanta Sa, and Nandini Singhal. “A Simple and Practical Concurrent Non-Blocking Unbounded Graph with Linearizable Reachability Queries.” In ACM International Conference Proceeding Series, 168–77. ACM, 2019. https://doi.org/10.1145/3288599.3288617.
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2019 | Published | Conference Paper | IST-REx-ID: 7437 | OA
Yu, Chen, Hanlin Tang, Cedric Renggli, Simon Kassing, Ankit Singla, Dan-Adrian Alistarh, Ce Zhang, and Ji Liu. “Distributed Learning over Unreliable Networks.” In 36th International Conference on Machine Learning, ICML 2019, 2019–June:12481–512. IMLS, 2019.
[Preprint] View | Download Preprint (ext.) | WoS | arXiv
 

2019 | Published | Conference Paper | IST-REx-ID: 7542 | OA
Wendler, Chris, Dan-Adrian Alistarh, and Markus Püschel. “Powerset Convolutional Neural Networks,” 32:927–38. Neural Information Processing Systems Foundation, 2019.
[Published Version] View | Download Published Version (ext.) | WoS | arXiv
 

2019 | Published | Conference Paper | IST-REx-ID: 6676 | OA
Alistarh, Dan-Adrian, James Aspnes, Faith Ellen, Rati Gelashvili, and Leqi Zhu. “Why Extension-Based Proofs Fail.” In Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 986–96. ACM Press, 2019. https://doi.org/10.1145/3313276.3316407.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2019 | Published | Conference Paper | IST-REx-ID: 6931 | OA
Nowak, Thomas, and Joel Rybicki. “Byzantine Approximate Agreement on Graphs.” In 33rd International Symposium on Distributed Computing, 146:29:1--29:17. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2019. https://doi.org/10.4230/LIPICS.DISC.2019.29.
[Published Version] View | Files available | DOI | arXiv
 

2019 | Published | Conference Paper | IST-REx-ID: 6933 | OA
Censor-Hillel, Keren, Michal Dory, Janne Korhonen, and Dean Leitersdorf. “Fast Approximate Shortest Paths in the Congested Clique.” In Proceedings of the 2019 ACM Symposium on Principles of Distributed Computin, 74–83. ACM, 2019. https://doi.org/10.1145/3293611.3331633.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

2019 | Published | Conference Paper | IST-REx-ID: 6935 | OA
Foerster, Klaus-Tycho, Janne Korhonen, Joel Rybicki, and Stefan Schmid. “Does Preprocessing Help under Congestion?” In Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing, 259–61. ACM, 2019. https://doi.org/10.1145/3293611.3331581.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2019 | Published | Journal Article | IST-REx-ID: 6936 | OA
Ovaskainen, Otso, Joel Rybicki, and Nerea Abrego. “What Can Observational Data Reveal about Metacommunity Processes?” Ecography. Wiley, 2019. https://doi.org/10.1111/ecog.04444.
[Published Version] View | Files available | DOI | WoS
 

2019 | Published | Journal Article | IST-REx-ID: 6972 | OA
Lenzen, Christoph, and Joel Rybicki. “Self-Stabilising Byzantine Clock Synchronisation Is Almost as Easy as Consensus.” Journal of the ACM. ACM, 2019. https://doi.org/10.1145/3339471.
[Published Version] View | Files available | DOI | WoS | arXiv
 

2019 | Published | Conference Paper | IST-REx-ID: 7122
Khirirat, Sarit, Mikael Johansson, and Dan-Adrian Alistarh. “Gradient Compression for Communication-Limited Convex Optimization.” In 2018 IEEE Conference on Decision and Control. IEEE, 2019. https://doi.org/10.1109/cdc.2018.8619625.
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2019 | Published | Conference Paper | IST-REx-ID: 7201 | OA
Renggli, Cedric, Saleh Ashkboos, Mehdi Aghagolzadeh, Dan-Adrian Alistarh, and Torsten Hoefler. “SparCML: High-Performance Sparse Communication for Machine Learning.” In International Conference for High Performance Computing, Networking, Storage and Analysis, SC. ACM, 2019. https://doi.org/10.1145/3295500.3356222.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

2019 | Published | Journal Article | IST-REx-ID: 7214 | OA
Aganezov, Sergey, Ilya Zban, Vitalii Aksenov, Nikita Alexeev, and Michael C. Schatz. “Recovering Rearranged Cancer Chromosomes from Karyotype Graphs.” BMC Bioinformatics. BMC, 2019. https://doi.org/10.1186/s12859-019-3208-4.
[Published Version] View | Files available | DOI | WoS
 

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