Shivaram Venkataraman
Computer Networks and Communications · 2011–2019
A researcher in the Science corpus: 12 papers; trusts 62 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Networks and Communications — 81 citations into it
- Information Systems — 78 citations into it
- Artificial Intelligence — 68 citations into it
- Computer Vision and Pattern Recognition — 59 citations into it
- ML Systems & Hardware — 34 citations into it
- Hardware and Architecture — 30 citations into it
- Optimization & Training — 26 citations into it
- Evaluation & Benchmarks — 19 citations into it
Whom Shivaram Venkataraman trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Kaiming He
- Muthu Dayalan
- Chih-Jen Lin
- Geoffrey E. Hinton
- Abhishek Verma
- Bradley Efron
- David G. Lowe
- Yoshua Bengio
- B. Recht
Who trusts Shivaram Venkataraman overall
- XiaoJian Wu
- Yanghua Peng
- Junchen Jiang
- Jun Yang
- A. L. Narasimha Reddy
- Sanjay Krishnan
- Wencong Xiao
- Ganesh Ananthanarayanan
- D. Narayanan
- Yixin Bao
Papers from Shivaram Venkataraman's perspective
Ordered by how strongly the researchers Shivaram Venkataraman 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- Learning Multiple Layers of Features from Tiny Images
Their papers
- MLlib: Machine Learning in Apache Spark (2015) — 1,861 citations
- Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads (2019) — 471 citations
- Themis: Fair and Efficient GPU Cluster Scheduling for Machine Learning Workloads (2019) — 249 citations
- SysML: The New Frontier of Machine Learning Systems (2019) — 23 citations
- MLSys: The New Frontier of Machine Learning Systems (2019) — 25 citations
- Multi-tenant GPU Clusters for Deep Learning Workloads: Analysis and Implications (2018) — 71 citations
- Occupy the cloud: distributed computing for the 99% (2017) — 526 citations
- CherryPick: Adaptively Unearthing the Best Cloud Configurations for Big Data Analytics (2017) — 523 citations
- KeystoneML: Optimizing Pipelines for Large-Scale Advanced Analytics (2016) — 161 citations
- Apache Spark (2016) — 1,660 citations
- Ernest: Efficient Performance Prediction for Large-Scale Advanced Analytics (2016) — 520 citations
- Consistent and Durable Data Structures for Non-Volatile Byte-Addressable Memory (2011) — 411 citations