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68 Publications

2020 | Conference Paper | IST-REx-ID: 7636
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, ACM, 2020, pp. 276–291.
View | DOI
 
2020 | Conference Paper | IST-REx-ID: 7803 | OA
Simple, deterministic, constant-round coloring in the congested clique
A. Czumaj, P. Davies, M. Parter, in:, Proceedings of the 2020 ACM Symposium on Principles of Distributed Computing, Association for Computing Machinery, 2020, pp. 309–318.
View | Files available | DOI | arXiv
 
2020 | Journal Article | IST-REx-ID: 7939 | OA
Fast approximate shortest paths in the congested clique
K. Censor-Hillel, M. Dory, J. Korhonen, D. Leitersdorf, Distributed Computing (2020).
View | Files available | DOI | Download Published Version (ext.) | arXiv
 
2020 | 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.
View | Files available | DOI | arXiv
 
2020 | 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.
View | Files available | 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, ICML 2020, 2020, pp. 5533–5543.
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2020 | Conference Paper | IST-REx-ID: 7802 | OA
Graph sparsification for derandomizing massively parallel computation with low space
A. Czumaj, P. Davies, M. Parter, in:, Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2020), Association for Computing Machinery, 2020, pp. 175–185.
View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2020 | Conference Paper | IST-REx-ID: 9632 | OA
WoodFisher: Efficient second-order approximation for neural network compression
S.P. Singh, D.-A. Alistarh, in:, Advances in Neural Information Processing Systems, Curran Associates, 2020, pp. 18098–18109.
View | Download Published Version (ext.) | arXiv
 
2020 | Conference Paper | IST-REx-ID: 9631 | OA
Scalable belief propagation via relaxed scheduling
V. Aksenov, D.-A. Alistarh, J. Korhonen, in:, Advances in Neural Information Processing Systems, Curran Associates, 2020, pp. 22361–22372.
View | Download Published Version (ext.) | arXiv
 
2019 | Conference Paper | IST-REx-ID: 7201 | OA
SparCML: High-performance sparse communication for machine learning
C. Renggli, S. Ashkboos, M. Aghagolzadeh, D.-A. Alistarh, T. Hoefler, in:, International Conference for High Performance Computing, Networking, Storage and Analysis, SC, ACM, 2019.
View | DOI | Download Preprint (ext.) | arXiv
 
2019 | 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, 2019, pp. 27–39.
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2019 | Journal Article | IST-REx-ID: 7214 | OA
Recovering rearranged cancer chromosomes from karyotype graphs
S. Aganezov, I. Zban, V. Aksenov, N. Alexeev, M.C. Schatz, BMC Bioinformatics 20 (2019).
View | Files available | DOI
 
2019 | Conference Paper | IST-REx-ID: 7228
Scalable FIFO channels for programming via communicating sequential processes
N. Koval, D.-A. Alistarh, R. Elizarov, in:, Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Nature, 2019, pp. 317–333.
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2019 | Conference Paper | IST-REx-ID: 7437 | OA
Distributed learning over unreliable networks
C. Yu, H. Tang, C. Renggli, S. Kassing, A. Singla, D.-A. Alistarh, C. Zhang, J. Liu, in:, 36th International Conference on Machine Learning, ICML 2019, IMLS, 2019, pp. 12481–12512.
View | Download Preprint (ext.) | arXiv
 
2019 | Conference Paper | IST-REx-ID: 7542 | OA
Powerset convolutional neural networks
C. Wendler, D.-A. Alistarh, M. Püschel, in:, Neural Information Processing Systems Foundation, 2019, pp. 927–938.
View | Download Published Version (ext.) | arXiv
 
2019 | Conference Paper | IST-REx-ID: 5947 | OA
A simple and practical concurrent non-blocking unbounded graph with linearizable reachability queries
B. Chatterjee, S. Peri, M. Sa, N. Singhal, in:, ACM International Conference Proceeding Series, ACM, 2019, pp. 168–177.
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2019 | 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 Press, 2019.
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2019 | 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 Press, 2019, pp. 145–154.
View | DOI | Download Preprint (ext.) | arXiv
 
2019 | 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 Press, 2019, pp. 986–996.
View | DOI | Download Preprint (ext.) | arXiv
 
2019 | Journal Article | IST-REx-ID: 6759 | OA
On grounded L-graphs and their relatives
V. Jelínek, M. Töpfer, Electronic Journal of Combinatorics 26 (2019).
View | Files available | arXiv
 

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