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Dan Alistarh

Jiale Chen

Vage Egiazarian

Eldar Kurtic

Ionut-Vlad Modoranu

Mahdi Nikdan

Andrei Panferov

Sergei Pankratov

Ileana Rugina

Erik Schultheis

Soroush Tabesh

Alexandra Volkova

Filipp Zmushko

Sharareh Alipour

Vitalii Aksenov

Trevor Brown

Bapi Chatterjee

Elvir Crncevic

Peter Davies

Alexander Fedorov

Elias Frantar

Janne Korhonen

Roberto Lopez Castro

Ilia Markov

Giorgi Nadiradze

Alexandra Krumes

Joel Rybicki

Mher Safaryan

Sidak Singh

Martin Töpfer

Sokolova, Mariia



170 Publications

2020 | Published | Conference Paper | IST-REx-ID: 8722 | OA
Taming unbalanced training workloads in deep learning with partial collective operations
S. Li, T.B.-N. Tal Ben-Nun, S.D. Girolamo, D.-A. Alistarh, T. Hoefler, in:, Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2020, pp. 45–61.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2020 | Published | Conference Paper | IST-REx-ID: 8724 | OA
On the sample complexity of adversarial multi-source PAC learning
N.H. Konstantinov, E. Frantar, D.-A. Alistarh, C. Lampert, in:, Proceedings of the 37th International Conference on Machine Learning, ML Research Press, 2020, pp. 5416–5425.
[Published Version] View | Files available | arXiv
 
2020 | Published | Conference Paper | IST-REx-ID: 8725 | OA
The splay-list: A distribution-adaptive concurrent skip-list
V. Aksenov, D.-A. Alistarh, A. Drozdova, A. Mohtashami, in:, 34th International Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020, p. 3:1-3:18.
[Published Version] View | Files available | DOI | arXiv
 
2020 | Published | Conference Paper | IST-REx-ID: 9631 | OA
Scalable belief propagation via relaxed scheduling
V. Aksenov, D.-A. Alistarh, J. Korhonen, in:, Neural Information Processing Systems Foundation, 2020, pp. 22361–22372.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2020 | Published | Conference Paper | IST-REx-ID: 9632 | OA
WoodFisher: Efficient second-order approximation for neural network compression
S.P. Singh, D.-A. Alistarh, in:, Neural Information Processing Systems Foundation, 2020, pp. 18098–18109.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2020 | Published | Conference Paper | IST-REx-ID: 7213 | OA
A persistent homology perspective to the link prediction problem
S. Bhatia, B. Chatterjee, D. Nathani, M. Kaul, in:, Complex Networks and Their Applications VIII, Springer Nature, 2020, pp. 27–39.
[Submitted Version] View | Files available | DOI | WoS
 
2020 | Published | Journal Article | IST-REx-ID: 7224 | OA
Habitat fragmentation and species diversity in competitive communities
J. Rybicki, N. Abrego, O. Ovaskainen, Ecology Letters 23 (2020) 506–517.
[Published Version] View | Files available | DOI | WoS | PubMed | Europe PMC
 
2020 | Published | Conference Paper | IST-REx-ID: 7272 | OA
Getting to the root of concurrent binary search tree performance
M. Arbel-Raviv, T.A. Brown, A. Morrison, in:, Proceedings of the 2018 USENIX Annual Technical Conference, USENIX Association, 2020, pp. 295–306.
[Published Version] View | Download Published Version (ext.)
 
earlier version | 2020 | Published | Conference Paper | IST-REx-ID: 15074 | OA
Brief announcement: Efficient load-balancing through distributed token dropping
S. Brandt, B. Keller, J. Rybicki, J. Suomela, J. Uitto, in:, 34th International Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020.
[Published Version] View | Files available | DOI | arXiv
 
2020 | Conference Paper | IST-REx-ID: 9415 | OA
Inducing and exploiting activation sparsity for fast neural network inference
M. Kurtz, J. Kopinsky, R. Gelashvili, A. Matveev, J. Carr, M. Goin, W. Leiserson, S. Moore, B. Nell, N. Shavit, D.-A. Alistarh, in:, 37th International Conference on Machine Learning, 2020, pp. 5533–5543.
[Published Version] View | Files available
 
2020 | Published | Conference Paper | IST-REx-ID: 7636 | OA
Non-blocking interpolation search trees with doubly-logarithmic running time
T.A. Brown, A. Prokopec, D.-A. Alistarh, in:, Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Association for Computing Machinery, 2020, pp. 276–291.
[Published Version] View | DOI | Download Published Version (ext.) | WoS
 
2020 | Published | Conference Paper | IST-REx-ID: 9198 | OA
Landscape connectivity and dropout stability of SGD solutions for over-parameterized neural networks
A. Shevchenko, M. Mondelli, in:, Proceedings of the 37th International Conference on Machine Learning, ML Research Press, 2020, pp. 8773–8784.
[Published Version] View | Files available | arXiv
 
2019 | Published | Conference Poster | IST-REx-ID: 6485
Lock-free channels for programming via communicating sequential processes
N. Koval, D.-A. Alistarh, R. Elizarov, Lock-Free Channels for Programming via Communicating Sequential Processes, ACM, 2019.
View | DOI | WoS
 
2019 | Published | Conference Paper | IST-REx-ID: 6673 | OA
Efficiency guarantees for parallel incremental algorithms under relaxed schedulers
D.-A. Alistarh, G. Nadiradze, N. Koval, in:, 31st ACM Symposium on Parallelism in Algorithms and Architectures, ACM, 2019, pp. 145–154.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
earlier version | 2019 | Published | Conference Paper | IST-REx-ID: 6676 | OA
Why extension-based proofs fail
D.-A. Alistarh, J. Aspnes, F. Ellen, R. Gelashvili, L. Zhu, in:, Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, ACM, 2019, pp. 986–996.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2019 | Published | Journal Article | IST-REx-ID: 6759 | OA
On grounded L-graphs and their relatives
V. Jelínek, M. Töpfer, Electronic Journal of Combinatorics 26 (2019).
[Published Version] View | Files available | DOI | arXiv
 
2019 | Published | Conference Paper | IST-REx-ID: 6931 | OA
Byzantine approximate agreement on graphs
T. Nowak, J. Rybicki, in:, 33rd International Symposium on Distributed Computing, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2019, p. 29:1--29:17.
[Published Version] View | Files available | DOI | arXiv
 
earlier version | 2019 | Published | Conference Paper | IST-REx-ID: 6933 | OA
Fast approximate shortest paths in the congested clique
K. Censor-Hillel, M. Dory, J. Korhonen, D. Leitersdorf, in:, Proceedings of the 2019 ACM Symposium on Principles of Distributed Computin, ACM, 2019, pp. 74–83.
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 
2019 | Published | Conference Paper | IST-REx-ID: 6935 | OA
Does preprocessing help under congestion?
K.-T. Foerster, J. Korhonen, J. Rybicki, S. Schmid, in:, Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing, ACM, 2019, pp. 259–261.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2019 | Published | Journal Article | IST-REx-ID: 6936 | OA
What can observational data reveal about metacommunity processes?
O. Ovaskainen, J. Rybicki, N. Abrego, Ecography 42 (2019) 1877–1886.
[Published Version] View | Files available | DOI | WoS
 

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