Learning Paradigms

Optimizing Data Usage via Differentiable Rewards ICML 2020 Optimizing Millions of Hyperparameters by Implicit Differentiation AISTATS 2020 Orchard: Differentially Private Analytics at Scale OSDI 2020 People Do Not Just Plan,They Plan to Plan AAAI 2020 Practical Federated Gradient Boosting Decision Trees AAAI 2020 Predicting Performance for Natural Language Processing Tasks ACL 2020 Privacy Amplification via Random Check-Ins NeurIPS 2020 Privacy-Preserving News Recommendation Model Learning EMNLP 2020 Quantized Compressive Sampling of Stochastic Gradients for Efficient Communication in Distributed Deep Learning AAAI 2020 Query-efficient Meta Attack to Deep Neural Networks ICLR 2020 Regularized Fine-Grained Meta Face Anti-Spoofing AAAI 2020 Residual Neural Processes AAAI 2020 Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition From a Domain Adaptation Perspective CVPR 2020 Rethinking Performance Estimation in Neural Architecture Search CVPR 2020 ROAM: Recurrently Optimizing Tracking Model CVPR 2020 Robust Federated Learning via Collaborative Machine Teaching AAAI 2020 Robust Meta-learning for Mixed Linear Regression with Small Batches NeurIPS 2020 Scene-Adaptive Video Frame Interpolation via Meta-Learning CVPR 2020 Self-Paced Learning for Neural Machine Translation EMNLP 2020 Self-paced Multi-view Co-training JMLR 2020 Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks EMNLP 2020 Self-Supervised Tuning for Few-Shot Segmentation IJCAI 2020 Sol: Fast Distributed Computation Over Slow Networks NSDI 2020 Solving Hard AI Planning Instances Using Curriculum-Driven Deep Reinforcement Learning IJCAI 2020 Stochastic Loss Function AAAI 2020