Neural Network Optimization

Random Reshuffling with Variance Reduction: New Analysis and Better Rates UAI 2023 Rapid Network Adaptation: Learning to Adapt Neural Networks Using Test-Time Feedback ICCV 2023 Re2TAL: Rewiring Pretrained Video Backbones for Reversible Temporal Action Localization CVPR 2023 Reachability-based Trajectory Design with Neural Implicit Safety Constraints RSS 2023 Rebalancing Batch Normalization for Exemplar-Based Class-Incremental Learning CVPR 2023 Recurrence Without Recurrence: Stable Video Landmark Detection With Deep Equilibrium Models CVPR 2023 RecursiveDet: End-to-End Region-Based Recursive Object Detection ICCV 2023 Re-GAN: Data-Efficient GANs Training via Architectural Reconfiguration CVPR 2023 Regret Guarantees for Online Deep Control L4DC 2023 REPAIR: REnormalizing Permuted Activations for Interpolation Repair ICLR 2023 Reparameterization through Spatial Gradient Scaling ICLR 2023 Resetting the Optimizer in Deep RL: An Empirical Study NeurIPS 2023 ResMem: Learn what you can and memorize the rest NeurIPS 2023 ResoNet: Noise-Trained Physics-Informed MRI Off-Resonance Correction NeurIPS 2023 Restricted Strong Convexity of Deep Learning Models with Smooth Activations ICLR 2023 Results of WMT23 Metrics Shared Task: Metrics Might Be Guilty but References Are Not Innocent EMNLP 2023 Rethinking Graph Lottery Tickets: Graph Sparsity Matters ICLR 2023 Rethinking skip connection model as a learnable Markov chain ICLR 2023 Rethinking the Role of Scale for In-Context Learning: An Interpretability-based Case Study at 66 Billion Scale ACL 2023 Rethinking the Visual Cues in Audio-Visual Speaker Extraction Interspeech 2023 Revisiting Non-Autoregressive Translation at Scale ACL 2023 Revisiting Structured Dropout ACML 2023 Revisiting Token Dropping Strategy in Efficient BERT Pretraining ACL 2023 RLEKF: An Optimizer for Deep Potential with Ab Initio Accuracy AAAI 2023 RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch ICLR 2023