James Cipar

Artificial Intelligence · 2013–2014

A researcher in the Science corpus: 3 papers; trusts 3 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 15 citations into it
• Computer Networks and Communications — 14 citations into it
• Hardware and Architecture — 7 citations into it

Whom James Cipar trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Haifeng Yu
2. Yucheng Low
3. Amr Ahmed
4. Joseph E. Gonzalez
5. Russell Power
6. Amin Vahdat
7. Fabrizio Petrini
8. Aapo Kyrola
9. Friedemann Mattern
10. Mohamed Aly

Who trusts James Cipar overall

1. Henggang Cui
2. Cong Xie
3. Wei Dai
4. Aaron Harlap
5. Eric P. Xing
6. Aurick Qiao
7. Oluwasanmi Koyejo
8. G. R. Ganger
9. Qirong Ho
10. Ilya Trofimov

Papers from James Cipar's perspective

Ordered by how strongly the researchers James Cipar trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Large Scale Distributed Deep Networks
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Learning Multiple Layers of Features from Tiny Images
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent

Their papers

• Exploiting Bounded Staleness to Speed Up Big Data Analytics (2014) — 171 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