Aditya Akella
Computer Networks and Communications · 2006–2021
A researcher in the Science corpus: 12 papers; trusts 21 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Computer Networks and Communications — 102 citations into it; #8,762 of 9,886 by trust here, #984 by citations
- Information Systems — 53 citations into it; #7,731 of 8,771 by trust here, #1,964 by citations
- Artificial Intelligence — 46 citations into it
- Computer Vision and Pattern Recognition — 36 citations into it
- Hardware and Architecture — 19 citations into it
- Electrical and Electronic Engineering — 17 citations into it
- ML Systems & Hardware — 13 citations into it
Whom Aditya Akella trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Srikanth Kandula
- Mohammad Al-Fares
- Albert G. Greenberg
- Theophilus A. Benson
- Sudipta Sengupta
- Bernard Fortz
- Muthu Dayalan
Who trusts Aditya Akella overall
Papers from Aditya Akella's perspective
Ordered by how strongly the researchers Aditya Akella trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- VL2: a scalable and flexible data center network (Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication)
- Attention is All you Need (Neural Information Processing Systems)
- A scalable, commodity data center network architecture (Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Et al
- BCube: a high performance, server-centric network architecture for modular data centers (Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication)
- Understanding data center traffic characteristics (Workshop on Research on Enterprise Networking)
Their papers
- Understanding data center traffic characteristics (2009) — 718 citations
- ATP: In-network Aggregation for Multi-tenant Learning (2021) — 335 citations
- The Design and Operation of CloudLab (2019) — 672 citations
- Themis: Fair and Efficient GPU Cluster Scheduling for Machine Learning Workloads (2019) — 249 citations
- Presto: Edge-based Load Balancing for Fast Datacenter Networks (2015) — 364 citations
- Low Latency Geo-distributed Data Analytics (2015) — 388 citations
- Multi-resource packing for cluster schedulers (2014) — 673 citations
- OpenNF (2014) — 509 citations
- Developing a predictive model of quality of experience for internet video (2013) — 446 citations
- MicroTE: fine grained traffic engineering for data centers (2011) — 697 citations
- Network traffic characteristics of data centers in the wild (2010) — 2,458 citations
- SANE: A Protection Architecture for Enterprise Networks (2006) — 296 citations