Embedding Learning

Exponential Family Embeddings NeurIPS 2016 Fast Collaborative Filtering from Implicit Feedback with Provable Guarantees ACML 2016 Fast Training of Triplet-Based Deep Binary Embedding Networks CVPR 2016 Finite Sample Prediction and Recovery Bounds for Ordinal Embedding NeurIPS 2016 GAKE: Graph Aware Knowledge Embedding COLING 2016 Geometric Mean Metric Learning ICML 2016 Geometry Aware Mappings for High Dimensional Sparse Factors AISTATS 2016 Hybrid Orthogonal Projection and Estimation (HOPE): A New Framework to Learn Neural Networks JMLR 2016 Improving Distributed Word Representation and Topic Model by Word-Topic Mixture Model ACML 2016 Improving Statistical Machine Translation with Selectional Preferences COLING 2016 Improving Translation Selection with Supersenses COLING 2016 Inducing Bilingual Lexica From Non-Parallel Data With Earth Mover’s Distance Regularization COLING 2016 Integrating Topic Modeling with Word Embeddings by Mixtures of vMFs COLING 2016 Joint Embedding of Hierarchical Categories and Entities for Concept Categorization and Dataless Classification COLING 2016 Jointly Modeling Embedding and Translation to Bridge Video and Language CVPR 2016 Knowledge-Driven Event Embedding for Stock Prediction COLING 2016 Label Embedding for Zero-shot Fine-grained Named Entity Typing COLING 2016 Language classification from bilingual word embedding graphs COLING 2016 Latent Embeddings for Zero-Shot Classification CVPR 2016 Latent Topic Embedding COLING 2016 Learning Deep Embeddings with Histogram Loss NeurIPS 2016 Learning Deep Representations of Fine-Grained Visual Descriptions CVPR 2016 Learning Deep Structure-Preserving Image-Text Embeddings CVPR 2016 Learning Distance Metrics for Multi-Label Classification ACML 2016 Learning Kernels with Random Features NeurIPS 2016