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Neural Network Optimization

902 directly classified papers

Papers per year

Papers

Dissecting the Effects of SGD Noise in Distinct Regimes of Deep Learning ICML 2023
Binarizing Sparse Convolutional Networks for Efficient Point Cloud Analysis CVPR 2023
CAME: Confidence-guided Adaptive Memory Efficient Optimization ACL 2023
On the Initialization of Graph Neural Networks ICML 2023
Revisiting Reverse Distillation for Anomaly Detection CVPR 2023
Understanding Gradient Regularization in Deep Learning: Efficient Finite-Difference Computation and Implicit Bias ICML 2023
Shakes on a Plane: Unsupervised Depth Estimation From Unstabilized Photography CVPR 2023
Conformal Inference is (almost) Free for Neural Networks Trained with Early Stopping ICML 2023
MDL-NAS: A Joint Multi-Domain Learning Framework for Vision Transformer CVPR 2023
Dropout Reduces Underfitting ICML 2023
NIPQ: Noise Proxy-Based Integrated Pseudo-Quantization CVPR 2023
Revisiting Token Dropping Strategy in Efficient BERT Pretraining ACL 2023
Polynomial Implicit Neural Representations for Large Diverse Datasets CVPR 2023
A Length-Extrapolatable Transformer ACL 2023
Symbolic Discovery of Optimization Algorithms NIPS 2023
Understanding Imbalanced Semantic Segmentation Through Neural Collapse CVPR 2023
Maximal Initial Learning Rates in Deep ReLU Networks ICML 2023
Self-Evolution Learning for Discriminative Language Model Pretraining ACL 2023
Bias in Pruned Vision Models: In-Depth Analysis and Countermeasures CVPR 2023
Learning to Boost Training by Periodic Nowcasting Near Future Weights ICML 2023
Initialization Noise in Image Gradients and Saliency Maps CVPR 2023
An SDE for Modeling SAM: Theory and Insights ICML 2023
On the Expressivity Role of LayerNorm in Transformers’ Attention ACL 2023
TRAMS: Training-free Memory Selection for Long-range Language Modeling EMNLP 2023
EfficientViT: Memory Efficient Vision Transformer With Cascaded Group Attention CVPR 2023