Optimization & Theory

Towards Extremely Compact RNNs for Video Recognition With Fully Decomposed Hierarchical Tucker Structure CVPR 2021 Towards Fast and Accurate Multi-Person Pose Estimation on Mobile Devices IJCAI 2021 Towards Sharper Generalization Bounds for Structured Prediction NeurIPS 2021 Towards Stable and Robust AdderNets NeurIPS 2021 Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration AAAI 2021 Towards Understanding Learning in Neural Networks with Linear Teachers ICML 2021 Towards Zero-Shot Knowledge Distillation for Natural Language Processing EMNLP 2021 Trainable Ranking Models to Evaluate the Semantic Accuracy of Data-to-Text Neural Generator EMNLP 2021 Training Adaptive Computation for Open-Domain Question Answering with Computational Constraints ACL 2021 Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds NeurIPS 2021 Training deep residual networks for uniform approximation guarantees L4DC 2021 Training Generative Adversarial Networks in One Stage CVPR 2021 Training Networks in Null Space of Feature Covariance for Continual Learning CVPR 2021 Training Neural Networks is ER-complete NeurIPS 2021 Training Neural Networks with Fixed Sparse Masks NeurIPS 2021 Training Over-parameterized Models with Non-decomposable Objectives NeurIPS 2021 Training Quantized Neural Networks to Global Optimality via Semidefinite Programming ICML 2021 Train simultaneously, generalize better: Stability of gradient-based minimax learners ICML 2021 Transformer Interpretability Beyond Attention Visualization CVPR 2021 Transient Non-stationarity and Generalisation in Deep Reinforcement Learning ICLR 2021 TranslateLocally: Blazing-fast translation running on the local CPU EMNLP 2021 TransTailor: Pruning the Pre-trained Model for Improved Transfer Learning AAAI 2021 Tree-Like Decision Distillation CVPR 2021 Troubleshooting Blind Image Quality Models in the Wild CVPR 2021 TRQ: Ternary Neural Networks With Residual Quantization AAAI 2021