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Few-Shot Learning

2,562 papers

Papers per year

3
167
401
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Papers

Meta-Learning with Implicit Gradients NIPS 2019
Fast and Flexible Multi-Task Classification using Conditional Neural Adaptive Processes NIPS 2019
SMILe: Scalable Meta Inverse Reinforcement Learning through Context-Conditional Policies NIPS 2019
A Generalized Algorithm for Multi-Objective Reinforcement Learning and Policy Adaptation NIPS 2019
Meta-Curvature NIPS 2019
Learning to Learn By Self-Critique NIPS 2019
Reconciling meta-learning and continual learning with online mixtures of tasks NIPS 2019
Efficient Meta Learning via Minibatch Proximal Update NIPS 2019
Visual Concept-Metaconcept Learning NIPS 2019
Learning to Self-Train for Semi-Supervised Few-Shot Classification NIPS 2019
Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model NIPS 2019
Adaptive Cross-Modal Few-shot Learning NIPS 2019
Cost Effective Active Search NIPS 2019
Incremental Few-Shot Learning with Attention Attractor Networks NIPS 2019
Unsupervised Meta-Learning for Few-Shot Image Classification NIPS 2019
Experience-Embedded Visual Foresight CORL 2019
Learning to Generalize Kinematic Models to Novel Objects CORL 2019
PGANs: Personalized Generative Adversarial Networks for ECG Synthesis to Improve Patient-Specific Deep ECG Classification AAAI 2019
Weakly-Supervised Simultaneous Evidence Identification and Segmentation for Automated Glaucoma Diagnosis AAAI 2019
Image Block Augmentation for One-Shot Learning AAAI 2019
Unsupervised Transfer Learning for Spoken Language Understanding in Intelligent Agents AAAI 2019
Consensus Adversarial Domain Adaptation AAAI 2019
Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification AAAI 2019
Semi-Parametric Sampling for Stochastic Bandits with Many Arms AAAI 2019
Attention-Based Multi-Context Guiding for Few-Shot Semantic Segmentation AAAI 2019