neural network training

Module-wise Training of Neural Networks via the Minimizing Movement Scheme NeurIPS 2023 Momentum Provably Improves Error Feedback! NeurIPS 2023 Neural Implicit Surface Evolution ICCV 2023 New Complexity-Theoretic Frontiers of Tractability for Neural Network Training NeurIPS 2023 On the Convergence of Stochastic Gradient Descent with Bandwidth-based Step Size JMLR 2023 Provable Data Subset Selection For Efficient Neural Networks Training ICML 2023 Robust Training for AC-OPF (Student Abstract) AAAI 2023 Self-Supervised Primal-Dual Learning for Constrained Optimization AAAI 2023 Sequential Gradient Coding For Straggler Mitigation ICLR 2023 Sequential Subset Matching for Dataset Distillation NeurIPS 2023 Simplifying Neural Network Training Under Class Imbalance NeurIPS 2023 SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks at the Edge ICML 2023 Stable Nonconvex-Nonconcave Training via Linear Interpolation NeurIPS 2023 Supervised Homography Learning with Realistic Dataset Generation ICCV 2023 Symbolic Discovery of Optimization Algorithms NeurIPS 2023 Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training NeurIPS 2023 The Transient Nature of Emergent In-Context Learning in Transformers NeurIPS 2023 Training Deep Surrogate Models with Large Scale Online Learning ICML 2023 Training Fully Connected Neural Networks is $\exists\mathbb{R}$-Complete NeurIPS 2023 Training Neural Networks is NP-Hard in Fixed Dimension NeurIPS 2023 Training Transformers with 4-bit Integers NeurIPS 2023 When to Learn What: Model-Adaptive Data Augmentation Curriculum ICCV 2023 You Only Condense Once: Two Rules for Pruning Condensed Datasets NeurIPS 2023 A Class of Short-term Recurrence Anderson Mixing Methods and Their Applications ICLR 2022 Active Boundary Loss for Semantic Segmentation AAAI 2022