Outputs (5)

Asynchronous Decentralized SGD with Quantized and Local Updates (2021)
Presentation / Conference Contribution
Nadiradze, G., Sabour, A., Davies, P., Li, S., & Alistarh, D. (2021, December). Asynchronous Decentralized SGD with Quantized and Local Updates. Presented at Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS 2021), Online

Decentralized optimization is emerging as a viable alternative for scalable distributed machine learning, but also introduces new challenges in terms of synchronization costs. To this end, several communication-reduction techniques, such as non-block... Read More about Asynchronous Decentralized SGD with Quantized and Local Updates.

New Bounds For Distributed Mean Estimation and Variance Reduction (2021)
Presentation / Conference Contribution
Davies, P., Gurunathan, V., Moshrefi, N., Ashkboos, S., & Alistarh, D. (2021, May). New Bounds For Distributed Mean Estimation and Variance Reduction. Presented at 9th International Conference on Learning Representations (ICLR), Vienna, Austria

We consider the problem of distributed mean estimation (DME), in which n machines are each given a local d-dimensional vector x v ∈ R d , and must cooperate to estimate the mean of their inputs µ = 1 n n v=1 x v , while minimizing total communication... Read More about New Bounds For Distributed Mean Estimation and Variance Reduction.

Graph Sparsification for Derandomizing Massively Parallel Computation with Low Space (2021)
Journal Article
Czumaj, A., Davies, P., & Parter, M. (2021). Graph Sparsification for Derandomizing Massively Parallel Computation with Low Space. ACM Transactions on Algorithms, 17(2), 1-27. https://doi.org/10.1145/3451992

Simple, Deterministic, Constant-Round Coloring in Congested Clique and MPC (2021)
Journal Article
Czumaj, A., Davies, P., & Parter, M. (2021). Simple, Deterministic, Constant-Round Coloring in Congested Clique and MPC. SIAM Journal on Computing, 50(5), 1603-1626. https://doi.org/10.1137/20m1366502

Exploiting Spontaneous Transmissions for Broadcasting and Leader Election in Radio Networks (2021)
Journal Article
Czumaj, A., & Davies, P. (2021). Exploiting Spontaneous Transmissions for Broadcasting and Leader Election in Radio Networks. Journal of the ACM, 68(2), 1-22. https://doi.org/10.1145/3446383

We study two fundamental communication primitives: broadcasting and leader election in the classical model of multi-hop radio networks with unknown topology and without collision detection mechanisms. It has been known for almost 20 years that in und... Read More about Exploiting Spontaneous Transmissions for Broadcasting and Leader Election in Radio Networks.