Generating embeddings through doing L2-normalization to sgns embeddings trained by all data (train,dev,test).
- SQLNet: Generating Structured Queries from Natural Language without Reinforcement Learning
- Coarse-to-Fine Decoding for Neural Semantic Parsing*
- Simplification Using Paraphrases and Context-based Lexical Substitution
- Entity Matching on Web Tables: a Table Embeddings Approach for Blocking
- Table2Vec: Neural Word and Entity Embeddings for Table Population and Retrieval
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An Ensemble Method to Produce High-Quality Word Embeddings
combine conceptNetwith word2vec and glove; SVD
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Improving Distributional Similarity with Lessons Learned from Word Embeddings
combine predictive embedding models with count based models
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ColNet: Embedding the Semantics of Web Tables for Column Type Prediction
CNN and transfer learning to deal with words did not appear at KB
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Sentence Modeling via Multiple Word Embeddings and Multi-level Comparison for Semantic Textual Similarity
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Structural Embedding of Syntactic Trees for Machine Comprehension
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Supervised Learning of Universal Sentence Representations from Natural Language Inference Data
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Retrofitting Word Vectors to Semantic Lexicons
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ConceptNet 5.5: An Open Multilingual Graph of General Knowledge
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Deep contextualized word representations(ELMo)
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Training Relation Embeddings under Logical Constraints
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A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors
Discussion on different embeddings
Next to do: fix k8s container not found bug