few-shot learning

Adaptive Cross-Modal Few-shot Learning NeurIPS 2019 Adaptive Gradient-Based Meta-Learning Methods NeurIPS 2019 Adaptive Posterior Learning: few-shot learning with a surprise-based memory module ICLR 2019 A Dual Attention Network with Semantic Embedding for Few-Shot Learning AAAI 2019 AffinityNet: Semi-Supervised Few-Shot Learning for Disease Type Prediction AAAI 2019 A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation NeurIPS 2019 A Meta-Learning Approach for Custom Model Training AAAI 2019 AMP: Adaptive Masked Proxies for Few-Shot Segmentation ICCV 2019 Attention-Based Multi-Context Guiding for Few-Shot Semantic Segmentation AAAI 2019 Bad Form: Comparing Context-Based and Form-Based Few-Shot Learning in Distributional Semantic Models EMNLP 2019 Big Generalizations with Small Data: Exploring the Role of Training Samples in Learning Adjectives of Size EMNLP 2019 Boosting Few-Shot Visual Learning With Self-Supervision ICCV 2019 CANet: Class-Agnostic Segmentation Networks With Iterative Refinement and Attentive Few-Shot Learning CVPR 2019 Collect and Select: Semantic Alignment Metric Learning for Few-Shot Learning ICCV 2019 Coloring With Limited Data: Few-Shot Colorization via Memory Augmented Networks CVPR 2019 Combining Unsupervised Pre-training and Annotator Rationales to Improve Low-shot Text Classification EMNLP 2019 Compositional Generalization for Primitive Substitutions EMNLP 2019 Cross Attention Network for Few-shot Classification NeurIPS 2019 Data-Efficient Goal-Oriented Conversation with Dialogue Knowledge Transfer Networks EMNLP 2019 Deep Meta Learning for Real-Time Target-Aware Visual Tracking ICCV 2019 Deep Metric Learning to Rank CVPR 2019 Dense Classification and Implanting for Few-Shot Learning CVPR 2019 Distribution Consistency Based Covariance Metric Networks for Few-Shot Learning AAAI 2019 Diversity With Cooperation: Ensemble Methods for Few-Shot Classification ICCV 2019 Domain Adaptive Dialog Generation via Meta Learning ACL 2019