R. Rosenfeld
Natural Language Processing · with Chen · 1993–2005
A researcher in the Science corpus: 9 papers; trusts 48 researchers and is trusted by 233 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 65 citations into it; #340 of 5,688 by trust here, #1,286 by citations
- Speech & Audio — 18 citations into it; #223 of 1,076 by trust here, #600 by citations
- Artificial Intelligence — 17 citations into it; #2,082 of 35,345 by trust here, #7,858 by citations
- Evaluation & Benchmarks — 15 citations into it
- Computer Vision and Pattern Recognition — 14 citations into it
- Information Theory — 13 citations into it
- Probabilistic & Bayesian Methods — 13 citations into it
- Representation & Self-Supervised Learning — 11 citations into it
Whom R. Rosenfeld trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Irving John Good
- Frederick Jelinek
- Reinhard Kneser
- Adam L. Berger
- Peter F. Brown
- N. Sloane
- James K. Baker
- V. D. Pietra
- Steve Hranilovic
- Roland Kuhn
Who trusts R. Rosenfeld overall
- Jerome R. Bellegarda
- Joshua Goodman
- Alessandro Vinciarelli
- Yoshua Bengio
- Andreas Stolcke
- Holger Schwenk
- Yee Whye Teh
- Hanna M. Wallach
- Noam Shazeer
- Bamshad Mobasher
Papers from R. Rosenfeld's perspective
Ordered by how strongly the researchers R. Rosenfeld 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)
- Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- Two decades of statistical language modeling: where do we go from here? (2000) — 850 citations
- Whole-sentence exponential language models: a vehicle for linguistic-statistical integration (2001) — 110 citations
- A survey of smoothing techniques for ME models (2000) — 246 citations
- Semi-supervised learning with graphs (2005) — 715 citations
- Generating remote control interfaces for complex appliances (2002) — 336 citations
- Statistical language modeling using the CMU-cambridge toolkit (1997)
- A maximum entropy approach to adaptive statistical language modelling (1996)
- Adaptive Statistical Language Modeling; A Maximum Entropy Approach (1994)
- Trigger-based language models: a maximum entropy approach (1993)