Ali Anwar
Cited by
Cited by
A Hybrid Approach to Privacy-Preserving Federated Learning
S Truex, N Baracaldo, A Anwar, T Steinke, H Ludwig, R Zhang, Y Zhou
The 12th ACM Workshop on Artificial Intelligence and Security (AISec 2019), 2019
Hybridalpha: An efficient approach for privacy-preserving federated learning
R Xu, N Baracaldo, Y Zhou, A Anwar, H Ludwig
Proceedings of the 12th ACM workshop on artificial intelligence and security …, 2019
TiFL: A Tier-based Federated Learning System
Z Chai, A Ali, S Zawad, S Truex, A Anwar, N Baracaldo, Y Zhou, H Ludwig, ...
ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC), 2020
FedAT: A high-performance and communication-efficient federated learning system with asynchronous tiers
Z Chai, Y Chen, A Anwar, L Zhao, Y Cheng, H Rangwala
Proceedings of the International Conference for High Performance Computing …, 2021
Ibm federated learning: an enterprise framework white paper v0. 1
H Ludwig, N Baracaldo, G Thomas, Y Zhou, A Anwar, S Rajamoni, Y Ong, ...
arXiv preprint arXiv:2007.10987, 2020
Wukong: A scalable and locality-enhanced framework for serverless parallel computing
B Carver, J Zhang, A Wang, A Anwar, P Wu, Y Cheng
Proceedings of the 11th ACM symposium on cloud computing, 1-15, 2020
{InfiniCache}: exploiting ephemeral serverless functions to build a {cost-effective} memory cache
A Wang, J Zhang, X Ma, A Anwar, L Rupprecht, D Skourtis, V Tarasov, ...
18th USENIX conference on file and storage technologies (FAST 20), 267-281, 2020
hatS: A heterogeneity-aware tiered storage for Hadoop
KR Krish, A Anwar, AR Butt
Cluster, Cloud and Grid Computing (CCGrid), 2014 14th IEEE/ACM International …, 2014
Improving docker registry design based on production workload analysis
A Anwar, M Mohamed, V Tarasov, M Littley, L Rupprecht, Y Cheng, ...
16th USENIX Conference on File and Storage Technologies (FAST), 265-278, 2018
Towards Taming the Resource and Data Heterogeneity in Federated Learning
Z Chai, H Fayyaz, Z Fayyaz, A Anwar, Y Zhou, N Baracaldo, H Ludwig, ...
2019 USENIX Conference on Operational Machine Learning, 2019
Dynamic metering adjustment for service management of computing platform
A Anwar, A Kochut, A Sailer, CO Schulz, A Segal
US Patent 10,467,036, 2019
Scalable metering for cloud service management based on cost-awareness
A Anwar, SA Baset, AP Kochut, H Lei, A Sailer, A Segal
US Patent 10,171,371, 2019
Characterizing co-located datacenter workloads: An alibaba case study
Y Cheng, Z Chai, A Anwar
Proceedings of the 9th asia-pacific workshop on systems, 1-3, 2018
Towards federated graph learning for collaborative financial crimes detection
T Suzumura, Y Zhou, N Baracaldo, G Ye, K Houck, R Kawahara, A Anwar, ...
arXiv preprint arXiv:1909.12946, 2019
Fedv: Privacy-preserving federated learning over vertically partitioned data
R Xu, N Baracaldo, Y Zhou, A Anwar, J Joshi, H Ludwig
Proceedings of the 14th ACM workshop on artificial intelligence and security …, 2021
Curse or redemption? how data heterogeneity affects the robustness of federated learning
S Zawad, A Ali, PY Chen, A Anwar, Y Zhou, N Baracaldo, Y Tian, F Yan
Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), 2021
Mos: Workload-aware elasticity for cloud object stores
A Anwar, Y Cheng, A Gupta, AR Butt
Proceedings of the 25th ACM International Symposium on High-Performance …, 2016
{DupHunter}: Flexible {High-Performance} Deduplication for Docker Registries
N Zhao, H Albahar, S Abraham, K Chen, V Tarasov, D Skourtis, ...
2020 USENIX Annual Technical Conference (USENIX ATC 20), 769-783, 2020
Large-scale analysis of docker images and performance implications for container storage systems
N Zhao, V Tarasov, H Albahar, A Anwar, L Rupprecht, D Skourtis, AK Paul, ...
IEEE Transactions on Parallel and Distributed Systems 32 (4), 918-930, 2020
Large-Scale Analysis of the Docker Hub Dataset
N Zhao, V Tarasov, H Albahar, A Anwar, L Rupprecht, D Skourtis, ...
IEEE International Conference on Cluster Computing, 2019
The system can't perform the operation now. Try again later.
Articles 1–20