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Embedding Learning

3,795 papers

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Papers

Stock Embeddings Acquired from News Articles and Price History, and an Application to Portfolio Optimization ACL 2020 Stolen Probability: A Structural Weakness of Neural Language Models ACL 2020 Story Embedding: Learning Distributed Representations of Stories based on Character Networks (Extended Abstract) IJCAI 2020 Structural Language Models of Code ICML 2020 Surfacing Privacy Settings Using Semantic Matching EMNLP 2020 Symbolic Querying of Vector Spaces: Probabilistic Databases Meets Relational Embeddings UAI 2020 Task-oriented Domain-specific Meta-Embedding for Text Classification EMNLP 2020 Temporal Network Embedding with High-Order Nonlinear Information AAAI 2020 Tensor Train Decomposition on TensorFlow (T3F) JMLR 2020 TeRo: A Time-aware Knowledge Graph Embedding via Temporal Rotation COLING 2020 Text-based Person Search via Attribute-aided Matching WACV 2020 The Secret is in the Spectra: Predicting Cross-lingual Task Performance with Spectral Similarity Measures EMNLP 2020 The TalTech Systems for the Short-Duration Speaker Verification Challenge 2020 Interspeech 2020 The XMUSPEECH System for the AP19-OLR Challenge Interspeech 2020 Tiny Word Embeddings Using Globally Informed Reconstruction COLING 2020 Topic Modeling on Document Networks with Adjacent-Encoder AAAI 2020 Towards Backward-Compatible Representation Learning CVPR 2020 Towards Better Context-aware Lexical Semantics:Adjusting Contextualized Representations through Static Anchors EMNLP 2020 Towards Fine-Grained Temporal Network Representation via Time-Reinforced Random Walk AAAI 2020 Towards Universal Representation Learning for Deep Face Recognition CVPR 2020 Translating Collocations: The Need for Task-driven Word Associations COLING 2020 TransRHS: A Representation Learning Method for Knowledge Graphs with Relation Hierarchical Structure IJCAI 2020 Treebank Embedding Vectors for Out-of-Domain Dependency Parsing ACL 2020 Tree! I am no Tree! I am a low dimensional Hyperbolic Embedding NeurIPS 2020 Understanding the Semantic Content of Sparse Word Embeddings Using a Commonsense Knowledge Base AAAI 2020