Learning Paradigms

Fast and Efficient Locomotion via Learned Gait Transitions CoRL 2021 Fast And Slow Learning Of Recurrent Independent Mechanisms ICLR 2021 Faster Meta Update Strategy for Noise-Robust Deep Learning CVPR 2021 Fast Federated Learning in the Presence of Arbitrary Device Unavailability NeurIPS 2021 fastHan: A BERT-based Multi-Task Toolkit for Chinese NLP ACL 2021 Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification NeurIPS 2021 FATE: An Industrial Grade Platform for Collaborative Learning With Data Protection JMLR 2021 Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee NeurIPS 2021 FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning ICLR 2021 FedBN: Federated Learning on Non-IID Features via Local Batch Normalization ICLR 2021 FedDR – Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization NeurIPS 2021 Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models AAAI 2021 Federated-EM with heterogeneity mitigation and variance reduction NeurIPS 2021 Federated f-Differential Privacy AISTATS 2021 Federated Graph Classification over Non-IID Graphs NeurIPS 2021 Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing NeurIPS 2021 Federated Learning Based on Dynamic Regularization ICLR 2021 Federated Learning of User Verification Models Without Sharing Embeddings ICML 2021 Federated Learning via Posterior Averaging: A New Perspective and Practical Algorithms ICLR 2021 Federated Learning with Compression: Unified Analysis and Sharp Guarantees AISTATS 2021 Federated Learning with Dynamic Transformer for Text to Speech Interspeech 2021 Federated Learning with Fair Averaging IJCAI 2021 Federated Learning with Sparsification-Amplified Privacy and Adaptive Optimization IJCAI 2021 Federated Linear Contextual Bandits NeurIPS 2021 Federated Model Distillation with Noise-Free Differential Privacy IJCAI 2021