Garth A. Gibson
Computer Networks and Communications · 2000–2019
A researcher in the Science corpus: 16 papers; trusts 16 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Computer Networks and Communications — 48 citations into it; #8,970 of 9,886 by trust here, #1,475 by citations
- Artificial Intelligence — 42 citations into it
- Optimization & Training — 33 citations into it
- Computer Vision and Pattern Recognition — 30 citations into it
- Information Systems — 27 citations into it
- Hardware and Architecture — 23 citations into it
- ML Systems & Hardware — 17 citations into it; #192 of 575 by trust here, #163 by citations
- Computational Mechanics — 16 citations into it
Whom Garth A. Gibson trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yucheng Low
- Joseph E. Gonzalez
- Amr Ahmed
- T. Griffiths
- Qirong Ho
- Martin A. Zinkevich
- Rainer Gemulla
- James Cipar
- Muthu Dayalan
Who trusts Garth A. Gibson overall
- Hao Zhang
- Henggang Cui
- Cong Xie
- Eric P. Xing
- Kurt B. Ferreira
- Wei Dai
- Gang Chen
- Kiwan Maeng
- Aaron Harlap
- Xiao Fang
Papers from Garth A. Gibson's perspective
Ordered by how strongly the researchers Garth A. Gibson trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet Large Scale Visual Recognition Challenge
- Large Scale Distributed Deep Networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
- MapReduce: simplified data processing on large clusters
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Building high-level features using large scale unsupervised learning
Their papers
- On Model Parallelization and Scheduling Strategies for Distributed Machine Learning (2014) — 129 citations
- SysML: The New Frontier of Machine Learning Systems (2019) — 23 citations
- Addressing the straggler problem for iterative convergent parallel ML (2016) — 148 citations
- Exploiting iterative-ness for parallel ML computations (2014) — 40 citations
- Exploiting Bounded Staleness to Speed Up Big Data Analytics (2014) — 171 citations
- High-Performance Distributed ML at Scale through Parameter Server Consistency Models (2014) — 123 citations
- Update of the handbook on external costs of transport: final report for the European Commission: DG-MOVE (2014) — 276 citations
- More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server (2013) — 813 citations
- Solving the Straggler Problem with Bounded Staleness (2013) — 149 citations
- PLFS: a checkpoint filesystem for parallel applications (2009) — 337 citations
- Safe and effective fine-grained TCP retransmissions for datacenter communication (2009) — 499 citations
- Measurement and Analysis of TCP Throughput Collapse in Cluster-based Storage Systems (2008) — 295 citations
- Scalable Performance of the Panasas Parallel File System (2008) — 418 citations
- Understanding failures in petascale computers (2007) — 489 citations
- A Large-Scale Study of Failures in High-Performance Computing Systems (2006) — 1,086 citations
- Network attached storage architecture (2000) — 317 citations