Few-Shot Learning

Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima NeurIPS 2021 Partial Is Better Than All: Revisiting Fine-tuning Strategy for Few-shot Learning AAAI 2021 PNPDet: Efficient Few-Shot Detection Without Forgetting via Plug-and-Play Sub-Networks WACV 2021 POODLE: Improving Few-shot Learning via Penalizing Out-of-Distribution Samples NeurIPS 2021 Predictive Complexity Priors AISTATS 2021 Progressive Network Grafting for Few-Shot Knowledge Distillation AAAI 2021 ProtoInfoMax: Prototypical Networks with Mutual Information Maximization for Out-of-Domain Detection EMNLP 2021 Prototype Completion With Primitive Knowledge for Few-Shot Learning CVPR 2021 PTN: A Poisson Transfer Network for Semi-supervised Few-shot Learning AAAI 2021 Query Adaptive Few-Shot Object Detection With Heterogeneous Graph Convolutional Networks ICCV 2021 RADDLE: An Evaluation Benchmark and Analysis Platform for Robust Task-oriented Dialog Systems ACL 2021 Raven's Progressive Matrices Completion with Latent Gaussian Process Priors AAAI 2021 Realistic evaluation of transductive few-shot learning NeurIPS 2021 Rectifying the Shortcut Learning of Background for Few-Shot Learning NeurIPS 2021 Regularising Knowledge Transfer by Meta Functional Learning IJCAI 2021 Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization NeurIPS 2021 Relational Embedding for Few-Shot Classification ICCV 2021 Relational Learning to Capture the Dynamics and Sparsity of Knowledge Graphs AAAI 2021 Relative and Absolute Location Embedding for Few-Shot Node Classification on Graph AAAI 2021 Repurposing GANs for One-Shot Semantic Part Segmentation CVPR 2021 Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning ICLR 2021 Re-ranking for image retrieval and transductive few-shot classification NeurIPS 2021 Rethinking Class Relations: Absolute-Relative Supervised and Unsupervised Few-Shot Learning CVPR 2021 Revisiting Self-training for Few-shot Learning of Language Model EMNLP 2021 Revisit Multimodal Meta-Learning through the Lens of Multi-Task Learning NeurIPS 2021