Popular Co-Authors
Ergun Bicici (4)
Enis Sert (3)
Suresh Manandhar (2)
Volkan Cirik (2)
Kevin Knight (2)
Roxana Girju (1)
Johan Hall (1)
Sandra Kübler (1)
Ryan McDonald (1)
Venues
CONLL (8)
WS (7)
*SEMEVAL (7)
EMNLP (4)
COLING (4)
HLT (3)
ACL (2)
WMT (2)
Deniz Yuret
2018
Tree-Stack LSTM in Transition Based Dependency Parsing
[K18-2012]:
{Ö}mer Kırnap
|
Erenay Dayanık
|
Deniz Yuret
SParse: Ko{ç} University Graph-Based Parsing System for the CoNLL 2018 Shared Task
[K18-2022]:
Berkay {Ö}nder
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Can G{ü}meli
|
Deniz Yuret
2017
Parsing with Context Embeddings
[K17-3008]:
Ömer Kırnap
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Berkay Furkan Önder
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Deniz Yuret
2016
Learning grammatical categories using paradigmatic representations: Substitute words for language acquisition
[C16-1068]:
Mehmet Ali Yatbaz
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Volkan Cirik
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Aylin Küntay
|
Deniz Yuret
CharNER: Character-Level Named Entity Recognition
[C16-1087]:
Onur Kuru
|
Ozan Arkan Can
|
Deniz Yuret
Transfer Learning for Low-Resource Neural Machine Translation
[D16-1163]:
Barret Zoph
|
Deniz Yuret
|
Jonathan May
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Kevin Knight
Why Neural Translations are the Right Length
[D16-1248]:
Xing Shi
|
Kevin Knight
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Deniz Yuret
Natural Language Communication with Robots
[N16-1089]:
Yonatan Bisk
|
Deniz Yuret
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Daniel Marcu
2014
Unsupervised Instance-Based Part of Speech Induction Using Probable Substitutes
[C14-1217]:
Deniz Yuret
|
Mehmet Ali Yatbaz
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Enis Sert
Probabilistic Modeling of Joint-context in Distributional Similarity
[W14-1619]:
Oren Melamud
|
Ido Dagan
|
Jacob Goldberger
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Idan Szpektor
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Deniz Yuret
2013
Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013)
[S13-2000]:
Suresh Manandhar
|
Deniz Yuret
AI-KU: Using Substitute Vectors and Co-Occurrence Modeling For Word Sense Induction and Disambiguation
[S13-2050]:
Osman Baskaya
|
Enis Sert
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Volkan Cirik
|
Deniz Yuret
2012
Learning Syntactic Categories Using Paradigmatic Representations of Word Context
[D12-1086]:
Mehmet Ali Yatbaz
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Enis Sert
|
Deniz Yuret
*SEM 2012: The First Joint Conference on Lexical and Computational Semantics – Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012)
[S12-1000]:
Eneko Agirre
|
Johan Bos
|
Mona iab
|
Suresh Manandhar
|
Yuval Marton
|
Deniz Yuret
2011
Instance Selection for Machine Translation using Feature Decay Algorithms
[W11-2131]:
Ergun Bicici
|
Deniz Yuret
RegMT System for Machine Translation, System Combination, and Evaluation
[W11-2137]:
Ergun Bicici
|
Deniz Yuret
2010
Unsupervised Part of Speech Tagging Using Unambiguous Substitutes from a Statistical Language Model
[C10-2159]:
Mehmet Ali Yatbaz
|
Deniz Yuret
The Noisy Channel Model for Unsupervised Word Sense Disambiguation
[J10-1004]:
Deniz Yuret
|
Mehmet Ali Yatbaz
SemEval-2010 Task 12: Parser Evaluation Using Textual Entailments
[S10-1009]:
Deniz Yuret
|
Aydin Han
|
Zehra Turgut
L1 Regularized Regression for Reranking and System Combination in Machine Translation
[W10-1741]:
Ergun Bicici
|
Deniz Yuret
2009
Modeling Morphologically Rich Languages Using Split Words and Unstructured Dependencies
[P09-2087]:
Deniz Yuret
|
Ergun Bicici
2008
Smoothing a Tera-word Language Model
[P08-2036]:
Deniz Yuret
Discriminative vs. Generative Approaches in Semantic Role Labeling
[W08-2131]:
Deniz Yuret
|
Mehmet Ali Yatbaz
|
Ahmet Engin Ural
2007
The CoNLL 2007 Shared Task on Dependency Parsing
[D07-1096]:
Joakim Nivre
|
Johan Hall
|
Sandra Kübler
|
Ryan McDonald
|
Jens Nilsson
|
Sebastian Riedel
|
Deniz Yuret
SemEval-2007 Task 04: Classification of Semantic Relations between Nominals
[S07-1003]:
Roxana Girju
|
Preslav Nakov
|
Vivi Nastase
|
Stan Szpakowicz
|
Peter Turney
|
Deniz Yuret
KU: Word Sense Disambiguation by Substitution
[S07-1044]:
Deniz Yuret
2006
Learning Morphological Disambiguation Rules for Turkish
[N06-1042]:
Deniz Yuret
|
Ferhan Ture
Dependency Parsing as a Classication Problem
[W06-2938]:
Deniz Yuret
2004
Some experiments with a Naive Bayes WSD system
[W04-0864]:
Deniz Yuret
