Arvind Krishnamurthy
Artificial Intelligence · USENIX Symposium on Operating Systems Design and Implementation · 2006–2020
A researcher in the Science corpus: 14 papers; trusts 179 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 113 citations into it
- Computer Vision and Pattern Recognition — 101 citations into it; #19,499 of 21,575 by trust here, #7,027 by citations
- Computer Networks and Communications — 97 citations into it; #8,873 of 9,886 by trust here, #1,173 by citations
- Hardware and Architecture — 51 citations into it
- ML Systems & Hardware — 40 citations into it
- Optimization & Training — 39 citations into it; #2,245 of 2,601 by trust here, #1,195 by citations
- Efficiency & Compression — 36 citations into it; #1,004 of 1,264 by trust here, #532 by citations
- Information Systems — 33 citations into it
Whom Arvind Krishnamurthy trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Dongyu Qiu
- Yoshua Bengio
- Beth Cohen
- Karen Simonyan
- Yann LeCun
- Ilya Sutskever
- Andrew Zisserman
Who trusts Arvind Krishnamurthy overall
Papers from Arvind Krishnamurthy's perspective
Ordered by how strongly the researchers Arvind Krishnamurthy trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Going deeper with convolutions
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- TVM: An Automated End-to-End Optimizing Compiler for Deep Learning (2018) — 357 citations
- PLink: Discovering and Exploiting Locality for Accelerated Distributed Training on the public Cloud (2020) — 57 citations
- Nexus: a GPU cluster engine for accelerating DNN-based video analysis (2019) — 335 citations
- Scaling Distributed Machine Learning with In-Network Aggregation (2019) — 553 citations
- Learning to Optimize Tensor Programs (2018) — 501 citations
- TVM: An Automated End-to-End Optimizing Compiler for Deep Learning (2018)
- IncBricks: Toward In-Network Computation with an In-Network Cache (2017) — 176 citations
- MCDNN: An Approximation-Based Execution Framework for Deep Stream Processing Under Resource Constraints (2016) — 413 citations
- Arrakis (2014) — 307 citations
- FairCloud: sharing the network in cloud computing (2012) — 436 citations
- P4p: provider portal for applications (2008) — 780 citations
- Do incentives build robustness in bit torrent (2007) — 407 citations
- Towards IP geolocation using delay and topology measurements (2006) — 403 citations
- iPlane: an information plane for distributed services (2006) — 674 citations