Paul A. Tucker

Optimization & Training · 2005–2016

A researcher in the Science corpus: 5 papers; trusts 1 researcher and is trusted by 26 researchers here, as inferred from the citation graph.

Subfields

• Optimization & Training — 32 citations into it; #926 of 2,601 by trust here, #33 by citations

Whom Paul A. Tucker trusts overall

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

1. L. Eon Bottou

Who trusts Paul A. Tucker overall

1. Tara N. Sainath
2. Li Deng

Papers from Paul A. Tucker's perspective

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

1. Long Short-Term Memory
2. Learning Multiple Layers of Features from Tiny Images
3. ImageNet: A large-scale hierarchical image database
4. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
5. ImageNet Large Scale Visual Recognition Challenge
6. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
7. Building high-level features using large scale unsupervised learning
8. Efficient BackProp
9. A Neural Probabilistic Language Model
10. Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent

Their papers

• TensorFlow: A system for large-scale machine learning (2016) — 19,838 citations
• Auto-rickshaw: an automated crystal structure determination platform as an efficient tool for the validation of an X-ray diffraction experiment. (2005) — 399 citations
• On the routine use of soft X-rays in macromolecular crystallography. Part IV. Efficient determination of anomalous substructures in biomacromolecules using longer X-ray wavelengths. (2007) — 77 citations
• TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems (2016) — 11,798 citations
• Large Scale Distributed Deep Networks (2012) — 4,179 citations