about
Efficient Estimation of Word Representations in Vector SpaceVery Deep Convolutional Networks for Text ClassificationContext encoders as a simple but powerful extension of word2vecCharacter-level Convolutional Networks for Text ClassificationTweester at SemEval-2017 Task 4: Fusion of Semantic-Affective and pairwise classification models for sentiment analysis in TwitterPart-of-Speech Tagging for Twitter with Adversarial Neural NetworksPrayas at EmoInt 2017: An Ensemble of Deep Neural Architectures for Emotion Intensity Prediction in TweetsIntrinsic Evaluation of Word Vectors Fails to Predict Extrinsic PerformanceAdvances in Pre-Training Distributed Word RepresentationsNotes on Noise Contrastive Estimation and Negative SamplingCommunity Evaluation and Exchange of Word Vectors at wordvectors.orgBetter Word Representations with Recursive Neural Networks for MorphologyIt Depends: Dependency Parser Comparison Using A Web-based Evaluation ToolImproving historical spelling normalization with bi-directional LSTMs and multi-task learningMultilingual Visual Sentiment Concept MatchingProjet Pensées ProfondesAn Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence ModelingLearning Grounded Meaning Representations with AutoencodersNew Word Analogy Corpus for Exploring Embeddings of Czech WordsStructuring Neural Networks for More Explainable PredictionsNeural Cross-Lingual Transfer and Limited Annotated Data for Named Entity Recognition in DanishRichpedia: A Comprehensive Multi-modal Knowledge Graph
P2860
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P2860
description
2011 թուականի Մարտին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի մարտին հրատարակված գիտական հոդված
@hy
Collobert et al. 2011
@en
artículu científicu espublizáu en 2011
@ast
im März 2011 veröffentlichter wissenschaftlicher Artikel
@de
vedecký článok (publikovaný 2011/03/02)
@sk
vědecký článek publikovaný v roce 2011
@cs
wetenschappelijk artikel (gepubliceerd op 2011/03/02)
@nl
наукова стаття, опублікована в березні 2011
@uk
مقالة علمية (نشرت في 2-3-2011)
@ar
name
Natural Language Processing (almost) from Scratch
@ast
Natural Language Processing (almost) from Scratch
@da
Natural Language Processing (almost) from Scratch
@de
Natural Language Processing (almost) from Scratch
@en
Natural Language Processing (almost) from Scratch
@fo
Natural Language Processing (almost) from Scratch
@fr
Natural Language Processing (almost) from Scratch
@is
Natural Language Processing (almost) from Scratch
@kl
Natural Language Processing (almost) from Scratch
@nb
Natural Language Processing (almost) from Scratch
@nl
type
label
Natural Language Processing (almost) from Scratch
@ast
Natural Language Processing (almost) from Scratch
@da
Natural Language Processing (almost) from Scratch
@de
Natural Language Processing (almost) from Scratch
@en
Natural Language Processing (almost) from Scratch
@fo
Natural Language Processing (almost) from Scratch
@fr
Natural Language Processing (almost) from Scratch
@is
Natural Language Processing (almost) from Scratch
@kl
Natural Language Processing (almost) from Scratch
@nb
Natural Language Processing (almost) from Scratch
@nl
prefLabel
Natural Language Processing (almost) from Scratch
@ast
Natural Language Processing (almost) from Scratch
@da
Natural Language Processing (almost) from Scratch
@de
Natural Language Processing (almost) from Scratch
@en
Natural Language Processing (almost) from Scratch
@fo
Natural Language Processing (almost) from Scratch
@fr
Natural Language Processing (almost) from Scratch
@is
Natural Language Processing (almost) from Scratch
@kl
Natural Language Processing (almost) from Scratch
@nb
Natural Language Processing (almost) from Scratch
@nl
P50
P921
P1476
Natural Language Processing (almost) from Scratch
@en
P2093
Michael Karlen
Pavel Kuksa
P304
P407
P577
2011-03-02T00:00:00Z