Optimization & Theory

RaScaNet: Learning Tiny Models by Raster-Scanning Images CVPR 2021 ReadOnce Transformers: Reusable Representations of Text for Transformers ACL 2021 Real-Time High-Resolution Background Matting CVPR 2021 ReconfigISP: Reconfigurable Camera Image Processing Pipeline ICCV 2021 Reconsidering the Past: Optimizing Hidden States in Language Models EMNLP 2021 RED : Looking for Redundancies for Data-FreeStructured Compression of Deep Neural Networks NeurIPS 2021 Reducing Neural Network Parameter Initialization Into an SMT Problem (Student Abstract) AAAI 2021 Refining BERT Embeddings for Document Hashing via Mutual Information Maximization EMNLP 2021 Regularising Fisher Information Improves Cross-lingual Generalisation EMNLP 2021 Regularization in ResNet with Stochastic Depth NeurIPS 2021 Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network AISTATS 2021 Regularizing Generative Adversarial Networks Under Limited Data CVPR 2021 Regularizing Neural Networks via Adversarial Model Perturbation CVPR 2021 Reinforcement Learning with Latent Flow NeurIPS 2021 Relating Adversarially Robust Generalization to Flat Minima ICCV 2021 Relative Flatness and Generalization NeurIPS 2021 Relevance-CAM: Your Model Already Knows Where To Look CVPR 2021 ReNAS: Relativistic Evaluation of Neural Architecture Search CVPR 2021 Representational aspects of depth and conditioning in normalizing flows ICML 2021 Representation Costs of Linear Neural Networks: Analysis and Design NeurIPS 2021 Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models NeurIPS 2021 RepVGG: Making VGG-Style ConvNets Great Again CVPR 2021 Reservoir Transformers ACL 2021 Residual Echo and Noise Cancellation with Feature Attention Module and Multi-Domain Loss Function Interspeech 2021 Residual Shuffle-Exchange Networks for Fast Processing of Long Sequences AAAI 2021