Ergun Biçici
Natural Language Processing · 2013–2017
A researcher in the Science corpus: 9 papers; trusts 121 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Natural Language Processing — 78 citations into it; #4,054 of 5,688 by trust here, #4,601 by citations
- Artificial Intelligence — 69 citations into it; #11,389 of 35,345 by trust here, #19,439 by citations
- Evaluation & Benchmarks — 44 citations into it; #766 of 3,147 by trust here, #2,442 by citations
- Molecular Biology — 16 citations into it
- Computer Vision and Pattern Recognition — 11 citations into it
- Information Systems — 10 citations into it
- Algorithms & Complexity — 7 citations into it
- Statistics and Probability — 7 citations into it
Whom Ergun Biçici trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Michael Collins
- Philipp Koehn
- Isabelle M Guyon
- Andreas Stolcke
- Andy Way
- Pierre Geurts
- Alex Smola
- Y. Seginer
- Chris Callison-Burch
- Jason Aaron Edward Weston
Who trusts Ergun Biçici overall
- Andy Way
- Miquel Esplà-Gomis
- Chris Hokamp
- Lucia Specia
- Kashif Shah
- Ondrej Bojar
- Qun Liu
- Felipe Sánchez-Martínez
- Iacer Calixto
- Carolina Scarton
Papers from Ergun Biçici's perspective
Ordered by how strongly the researchers Ergun Biçici trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
Their papers
- Predicting Translation Performance with Referential Translation Machines (2017) — 8 citations
- Referential Translation Machines for Predicting Translation Performance (2016) — 5 citations
- Referential translation machines for predicting semantic similarity (2015) — 16 citations
- RTM at SemEval-2017 Task 1: Referential Translation Machines for Predicting Semantic Similarity (2017) — 6 citations
- ParFDA for Instance Selection for Statistical Machine Translation (2016) — 8 citations
- Referential Translation Machines for Predicting Translation Quality and Related Statistics (2015) — 13 citations
- Parallel FDA5 for Fast Deployment of Accurate Statistical Machine Translation Systems (2014) — 17 citations
- Referential Translation Machines for Predicting Translation Quality (2014) — 25 citations
- Referential Translation Machines for Quality Estimation (2013) — 44 citations