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.

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.

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.

Memory tagging: Minimalist synchronization for scalable concurrent data structures
D.-A. Alistarh, T.A. Brown, N. Singhal, in:, Annual ACM Symposium on Parallelism in Algorithms and Architectures, Association for Computing Machinery, 2020, pp. 37–49.

Testing concurrency on the JVM with Lincheck
N. Koval, M. Sokolova, A. Fedorov, D.-A. Alistarh, D. Tsitelov, in:, Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP, Association for Computing Machinery, 2020, pp. 423–424.

Brief Announcement: Why Extension-Based Proofs Fail
D.-A. Alistarh, J. Aspnes, F. Ellen, R. Gelashvili, L. Zhu, in:, Proceedings of the 39th Symposium on Principles of Distributed Computing, Association for Computing Machinery, 2020, pp. 54–56.

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.

Adaptive gradient quantization for data-parallel SGD
F. Faghri, I. Tabrizian, I. Markov, D.-A. Alistarh, D. Roy, A. Ramezani-Kebrya, in:, Advances in Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2020.

Dynamic averaging load balancing on cycles
D.-A. Alistarh, G. Nadiradze, A. Sabour, in:, 47th International Colloquium on Automata, Languages, and Programming, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020.

On grounded L-graphs and their relatives
V. Jelínek, M. Töpfer, Electronic Journal of Combinatorics 26 (2019).

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.

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.

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.

What can observational data reveal about metacommunity processes?
O. Ovaskainen, J. Rybicki, N. Abrego, Ecography 42 (2019) 1877–1886.

Self-stabilising Byzantine clock synchronisation is almost as easy as consensus
C. Lenzen, J. Rybicki, Journal of the ACM 66 (2019).

Gradient compression for communication-limited convex optimization
S. Khirirat, M. Johansson, D.-A. Alistarh, in:, 2018 IEEE Conference on Decision and Control, IEEE, 2019.

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.

Recovering rearranged cancer chromosomes from karyotype graphs
S. Aganezov, I. Zban, V. Aksenov, N. Alexeev, M.C. Schatz, BMC Bioinformatics 20 (2019).

Scalable FIFO channels for programming via communicating sequential processes
N. Koval, D.-A. Alistarh, R. Elizarov, in:, 25th Anniversary of Euro-Par, Springer Nature, 2019, pp. 317–333.

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.