Konstantinov NH, Frantar E, Alistarh D-A, Lampert C. On the sample complexity of adversarial multi-source PAC learning. In: Proceedings of the 37th International Conference on Machine Learning. Vol 119. ML Research Press; 2020:5416-5425.

Bhatia S, Chatterjee B, Nathani D, Kaul M. A persistent homology perspective to the link prediction problem. In: Complex Networks and Their Applications VIII. Vol 881. Springer Nature; 2020:27-39. doi:10.1007/978-3-030-36687-2_3

Czumaj A, Davies P, Parter M. Graph sparsification for derandomizing massively parallel computation with low space. In: Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2020). Association for Computing Machinery; 2020:175-185. doi:10.1145/3350755.3400282

Brown TA, Prokopec A, Alistarh D-A. Non-blocking interpolation search trees with doubly-logarithmic running time. In: Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming. Association for Computing Machinery; 2020:276-291. doi:10.1145/3332466.3374542

Alistarh D-A, Brown TA, Singhal N. Memory tagging: Minimalist synchronization for scalable concurrent data structures. In: Annual ACM Symposium on Parallelism in Algorithms and Architectures. Association for Computing Machinery; 2020:37-49. doi:10.1145/3350755.3400213

Koval N, Sokolova M, Fedorov A, Alistarh D-A, Tsitelov D. Testing concurrency on the JVM with Lincheck. In: Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP. Association for Computing Machinery; 2020:423-424. doi:10.1145/3332466.3374503

Alistarh D-A, Aspnes J, Ellen F, Gelashvili R, Zhu L. Brief Announcement: Why Extension-Based Proofs Fail. In: Proceedings of the 39th Symposium on Principles of Distributed Computing. Association for Computing Machinery; 2020:54-56. doi:10.1145/3382734.3405743

Brandt S, Keller B, Rybicki J, Suomela J, Uitto J. Brief announcement: Efficient load-balancing through distributed token dropping. In: 34th International Symposium on Distributed Computing. Vol 179. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2020. doi:10.4230/LIPIcs.DISC.2020.40

Faghri F, Tabrizian I, Markov I, Alistarh D-A, Roy D, Ramezani-Kebrya A. Adaptive gradient quantization for data-parallel SGD. In: Advances in Neural Information Processing Systems. Vol 33. Neural Information Processing Systems Foundation; 2020.

Alistarh D-A, Nadiradze G, Sabour A. Dynamic averaging load balancing on cycles. In: 47th International Colloquium on Automata, Languages, and Programming. Vol 168. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2020. doi:10.4230/LIPIcs.ICALP.2020.7

Jelínek V, Töpfer M. On grounded L-graphs and their relatives. Electronic Journal of Combinatorics. 2019;26(3). doi:10.37236/8096

Nowak T, Rybicki J. Byzantine approximate agreement on graphs. In: 33rd International Symposium on Distributed Computing. Vol 146. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2019:29:1--29:17. doi:10.4230/LIPICS.DISC.2019.29

Chatterjee B, Peri S, Sa M, Singhal N. A simple and practical concurrent non-blocking unbounded graph with linearizable reachability queries. In: ACM International Conference Proceeding Series. ACM; 2019:168-177. doi:10.1145/3288599.3288617

Koval N, Alistarh D-A, Elizarov R. Lock-Free Channels for Programming via Communicating Sequential Processes. ACM Press; 2019:417-418. doi:10.1145/3293883.3297000

Ovaskainen O, Rybicki J, Abrego N. What can observational data reveal about metacommunity processes? Ecography. 2019;42(11):1877-1886. doi:10.1111/ecog.04444

Lenzen C, Rybicki J. Self-stabilising Byzantine clock synchronisation is almost as easy as consensus. Journal of the ACM. 2019;66(5). doi:10.1145/3339471

Khirirat S, Johansson M, Alistarh D-A. Gradient compression for communication-limited convex optimization. In: 2018 IEEE Conference on Decision and Control. IEEE; 2019. doi:10.1109/cdc.2018.8619625

Renggli C, Ashkboos S, Aghagolzadeh M, Alistarh D-A, Hoefler T. SparCML: High-performance sparse communication for machine learning. In: International Conference for High Performance Computing, Networking, Storage and Analysis, SC. ACM; 2019. doi:10.1145/3295500.3356222

Aganezov S, Zban I, Aksenov V, Alexeev N, Schatz MC. Recovering rearranged cancer chromosomes from karyotype graphs. BMC Bioinformatics. 2019;20. doi:10.1186/s12859-019-3208-4

Koval N, Alistarh D-A, Elizarov R. Scalable FIFO channels for programming via communicating sequential processes. In: 25th Anniversary of Euro-Par. Vol 11725. Springer Nature; 2019:317-333. doi:10.1007/978-3-030-29400-7_23