Alistarh, Dan-Adrian, Giorgi Nadiradze, and Nikita Koval. “Efficiency Guarantees for Parallel Incremental Algorithms under Relaxed Schedulers.”https://doi.org/10.1145/3323165.3323201__In 31st ACM Symposium on Parallelism in Algorithms and Architectures, 145–54. ACM Press, 2019.https://doi.org/10.1145/3323165.3323201 .
LibreCat: https://research-explorer.ista.ac.at/record/6673
DOI: 10.1145/3323165.3323201
WoS: 000507618500018
arXiv: 2003.09363

Wendler, Chris, Dan-Adrian Alistarh, and Markus Püschel. “Powerset Convolutional Neural Networks,” 32:927–38. Neural Information Processing Systems Foundation, 2019.
LibreCat: https://research-explorer.ista.ac.at/record/7542
WoS: 000534424300084
arXiv: 1909.02253

Foerster, Klaus-Tycho, Janne Korhonen, Joel Rybicki, and Stefan Schmid. “Does Preprocessing Help under Congestion?”https://doi.org/10.1145/3293611.3331581__In Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing, 259–61. ACM, 2019.https://doi.org/10.1145/3293611.3331581 .
LibreCat: https://research-explorer.ista.ac.at/record/6935
DOI: 10.1145/3293611.3331581
WoS: 000570442000037
arXiv: 1905.03012

Alistarh, Dan-Adrian, James Aspnes, Faith Ellen, Rati Gelashvili, and Leqi Zhu. “Why Extension-Based Proofs Fail.”https://doi.org/10.1145/3313276.3316407__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 .
LibreCat: https://research-explorer.ista.ac.at/record/6676
DOI: 10.1145/3313276.3316407
WoS: 000523199100089
arXiv: 1811.01421

Censor-Hillel, Keren, Michal Dory, Janne Korhonen, and Dean Leitersdorf. “Fast Approximate Shortest Paths in the Congested Clique.”https://doi.org/10.1145/3293611.3331633__In Proceedings of the 2019 ACM Symposium on Principles of Distributed Computin, 74–83. ACM, 2019.https://doi.org/10.1145/3293611.3331633 .
LibreCat: https://research-explorer.ista.ac.at/record/6933
DOI: 10.1145/3293611.3331633
WoS: 000570442000011
arXiv: 1903.05956

Alistarh, Dan-Adrian, James Aspnes, Valerie King, and Jared Saia. “Communication-Efficient Randomized Consensus.”https://doi.org/10.1007/s00446-017-0315-1__Distributed Computing. Springer, 2018.https://doi.org/10.1007/s00446-017-0315-1 .
LibreCat: https://research-explorer.ista.ac.at/record/536
DOI: 10.1007/s00446-017-0315-1

Grubic, Demjan, Leo Tam, Dan-Adrian Alistarh, and Ce Zhang. “Synchronous Multi-GPU Training for Deep Learning with Low-Precision Communications: An Empirical Study.”https://doi.org/10.5441/002/EDBT.2018.14__In Proceedings of the 21st International Conference on Extending Database Technology, 145–56. OpenProceedings, 2018.https://doi.org/10.5441/002/EDBT.2018.14 .
LibreCat: https://research-explorer.ista.ac.at/record/7116
DOI: 10.5441/002/EDBT.2018.14

Alistarh, Dan-Adrian, William Leiserson, Alexander Matveev, and Nir Shavit. “ThreadScan: Automatic and Scalable Memory Reclamation.”https://doi.org/10.1145/3201897__ACM Transactions on Parallel Computing. Association for Computing Machinery, 2018.https://doi.org/10.1145/3201897 .
LibreCat: https://research-explorer.ista.ac.at/record/6001
DOI: 10.1145/3201897

Polino, Antonio, Razvan Pascanu, and Dan-Adrian Alistarh. “Model Compression via Distillation and Quantization.” In 6th International Conference on Learning Representations, 2018.
LibreCat: https://research-explorer.ista.ac.at/record/7812
arXiv: 1802.05668

Arbel Raviv, Maya, and Trevor A Brown. “Harnessing Epoch-Based Reclamation for Efficient Range Queries,”https://doi.org/10.1145/3178487.3178489__53:14–27. ACM, 2018.https://doi.org/10.1145/3178487.3178489 .
LibreCat: https://research-explorer.ista.ac.at/record/397
DOI: 10.1145/3178487.3178489
WoS: 000446161100002

Rybicki, Joel, Eva Kisdi, and Jani Anttila. “Model of Bacterial Toxin-Dependent Pathogenesis Explains Infective Dose.”https://doi.org/10.1073/pnas.1721061115__PNAS. National Academy of Sciences, 2018.https://doi.org/10.1073/pnas.1721061115 .
LibreCat: https://research-explorer.ista.ac.at/record/43
DOI: 10.1073/pnas.1721061115
WoS: 000447491300057

Lenzen, Christoph, and Joel Rybicki. “Near-Optimal Self-Stabilising Counting and Firing Squads.”https://doi.org/10.1007/s00446-018-0342-6__Distributed Computing. Springer, 2018.https://doi.org/10.1007/s00446-018-0342-6 .
LibreCat: https://research-explorer.ista.ac.at/record/76
DOI: 10.1007/s00446-018-0342-6
WoS: 000475627800005

Gilad, Eran, Trevor A Brown, Mark Oskin, and Yoav Etsion. “Snapshot Based Synchronization: A Fast Replacement for Hand-over-Hand Locking,”https://doi.org/10.1007/978-3-319-96983-1_33__11014:465–79. Springer, 2018.https://doi.org/10.1007/978-3-319-96983-1_33 .
LibreCat: https://research-explorer.ista.ac.at/record/85
DOI: 10.1007/978-3-319-96983-1_33
WoS: 000851042300031

Alistarh, Dan-Adrian, Christopher De Sa, and Nikola H Konstantinov. “The Convergence of Stochastic Gradient Descent in Asynchronous Shared Memory.”https://doi.org/10.1145/3212734.3212763__In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, 169–78. ACM Press, 2018.https://doi.org/10.1145/3212734.3212763 .
LibreCat: https://research-explorer.ista.ac.at/record/5962
DOI: 10.1145/3212734.3212763
WoS: 000458186900022
arXiv: 1803.08841

Alistarh, Dan-Adrian. “A Brief Tutorial on Distributed and Concurrent Machine Learning.”https://doi.org/10.1145/3212734.3212798__In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, 487–88. ACM Press, 2018.https://doi.org/10.1145/3212734.3212798 .
LibreCat: https://research-explorer.ista.ac.at/record/5961
DOI: 10.1145/3212734.3212798
WoS: 000458186900063

Alistarh, Dan-Adrian, Trevor A Brown, Justin Kopinsky, and Giorgi Nadiradze. “Relaxed Schedulers Can Efficiently Parallelize Iterative Algorithms.”https://doi.org/10.1145/3212734.3212756__In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, 377–86. ACM Press, 2018.https://doi.org/10.1145/3212734.3212756 .
LibreCat: https://research-explorer.ista.ac.at/record/5963
DOI: 10.1145/3212734.3212756
WoS: 000458186900048
arXiv: 1808.04155

Alistarh, Dan-Adrian, Trevor A Brown, Justin Kopinsky, Jerry Z. Li, and Giorgi Nadiradze. “Distributionally Linearizable Data Structures.”https://doi.org/10.1145/3210377.3210411__In Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures  - SPAA ’18, 133–42. ACM Press, 2018.https://doi.org/10.1145/3210377.3210411 .
LibreCat: https://research-explorer.ista.ac.at/record/5965
DOI: 10.1145/3210377.3210411
WoS: 000545269600016
arXiv: 1804.01018

Alistarh, Dan-Adrian, Syed Kamran Haider, Raphael Kübler, and Giorgi Nadiradze. “The Transactional Conflict Problem.”https://doi.org/10.1145/3210377.3210406__In Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures  - SPAA ’18, 383–92. ACM Press, 2018.https://doi.org/10.1145/3210377.3210406 .
LibreCat: https://research-explorer.ista.ac.at/record/5966
DOI: 10.1145/3210377.3210406
WoS: 000545269600046
arXiv: 1804.00947

Aksenov, Vitaly, Dan-Adrian Alistarh, and Petr Kuznetsov. “Brief Announcement: Performance Prediction for Coarse-Grained Locking.”https://doi.org/10.1145/3212734.3212785__In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing  - PODC ’18, 411–13. ACM Press, 2018.https://doi.org/10.1145/3212734.3212785 .
LibreCat: https://research-explorer.ista.ac.at/record/5964
DOI: 10.1145/3212734.3212785
WoS: 000458186900052

Stojanov, Alen, Tyler Michael Smith, Dan-Adrian Alistarh, and Markus Puschel. “Fast Quantized Arithmetic on : Trading Compute for Data Movement.”https://doi.org/10.1109/SiPS.2018.8598402__In 2018 IEEE International Workshop on Signal Processing Systems, Vol. 2018–October. IEEE, 2018.https://doi.org/10.1109/SiPS.2018.8598402 .
LibreCat: https://research-explorer.ista.ac.at/record/6031
DOI: 10.1109/SiPS.2018.8598402
WoS: 000465106800060