| 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 | 1145 | 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 | 418 | 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 | 344 | 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 | 263* | 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 | 178 | 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 | 138 | 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 | 126 | 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 | 100 | 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 | 99 | 2018 |
| 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 | 98 | 2019 |
| 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 | 98 | 2019 |
| 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 | 97 | 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 | 91 | 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 | 90 | 2021 |
| 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 | 86 | 2018 |
| 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 | 73 | 2021 |
| 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 | 55 | 2020 |
| {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 | 54 | 2020 |
| 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 | 51 | 2016 |
| 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 | 48 | 2019 |
Yi ZhouResearch Staff Member, IBM ResearchCorreu electrònic verificat a ibm.com
