neural network optimization

MKOR: Momentum-Enabled Kronecker-Factor-Based Optimizer Using Rank-1 Updates NeurIPS 2023 Mnemosyne: Learning to Train Transformers with Transformers NeurIPS 2023 Mode Connectivity in Auction Design NeurIPS 2023 ModelKeeper: Accelerating DNN Training via Automated Training Warmup NSDI 2023 MSCFFN: A New FFN with Multi-Space Cross to Accelerate Transformer EMNLP 2023 MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks ICML 2023 Multi-Level Logit Distillation CVPR 2023 Network Expansion for Practical Training Acceleration CVPR 2023 Neural Architecture Search for Wide Spectrum Adversarial Robustness AAAI 2023 Neural Weight Search for Scalable Task Incremental Learning WACV 2023 On Enhancing Fine-Tuning for Pre-trained Language Models EMNLP 2023 One Wide Feedforward Is All You Need EMNLP 2023 On the Initialization of Graph Neural Networks ICML 2023 On the Neural Tangent Kernel Analysis of Randomly Pruned Neural Networks AISTATS 2023 On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective NeurIPS 2023 On the Training Instability of Shuffling SGD with Batch Normalization ICML 2023 Optimistic Meta-Gradients NeurIPS 2023 OSP2B: One-Stage Point-to-Box Network for 3D Siamese Tracking IJCAI 2023 OTOv2: Automatic, Generic, User-Friendly ICLR 2023 Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation NeurIPS 2023 Over-parameterized Model Optimization with Polyak-{\L}ojasiewicz Condition ICLR 2023 PA&DA: Jointly Sampling Path and Data for Consistent NAS CVPR 2023 PAD-Net: An Efficient Framework for Dynamic Networks ACL 2023 Partition Speeds Up Learning Implicit Neural Representations Based on Exponential-Increase Hypothesis ICCV 2023 Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks NeurIPS 2023