Learning Paradigms

Learning Robust State Abstractions for Hidden-Parameter Block MDPs ICLR 2021 Learning Task-Distribution Reward Shaping with Meta-Learning AAAI 2021 Learning to Adapt via Latent Domains for Adaptive Semantic Segmentation NeurIPS 2021 Learning to Attack Real-World Models for Person Re-identification via Virtual-Guided Meta-Learning AAAI 2021 Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification CVPR 2021 Learning to Generate Noise for Multi-Attack Robustness ICML 2021 Learning To Hallucinate Examples From Extrinsic and Intrinsic Supervision ICCV 2021 Learning to Learn Dense Gaussian Processes for Few-Shot Learning NeurIPS 2021 Learning to Learn End-to-End Goal-Oriented Dialog From Related Dialog Tasks EMNLP 2021 Learning-to-learn non-convex piecewise-Lipschitz functions NeurIPS 2021 Learning to Learn Semantic Factors in Heterogeneous Image Classification NAACL 2021 Learning to Learn to be Right for the Right Reasons NAACL 2021 Learning to Purify Noisy Labels via Meta Soft Label Corrector AAAI 2021 Learning to Selectively Learn for Weakly-supervised Paraphrase Generation EMNLP 2021 Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation NeurIPS 2021 Linear Convergence in Federated Learning: Tackling Client Heterogeneity and Sparse Gradients NeurIPS 2021 Linear Regression over Networks with Communication Guarantees L4DC 2021 Local SGD: Unified Theory and New Efficient Methods AISTATS 2021 Lossless Compression of Efficient Private Local Randomizers ICML 2021 LRSC: Learning Representations for Subspace Clustering AAAI 2021 MARINA: Faster Non-Convex Distributed Learning with Compression ICML 2021 Memory Efficient Meta-Learning with Large Images NeurIPS 2021 MetaAlign: Coordinating Domain Alignment and Classification for Unsupervised Domain Adaptation CVPR 2021 MetaAugment: Sample-Aware Data Augmentation Policy Learning AAAI 2021 Meta Batch-Instance Normalization for Generalizable Person Re-Identification CVPR 2021