← Optimization & Theory
Deep Learning › Optimization & Theory ›

Neural Network Optimization

902 directly classified papers

Papers per year

Papers

Bayes-optimal learning of an extensive-width neural network from quadratically many samples NIPS 2024
ADR-X: ANN-Assisted Wireless Link Rate Adaptation for Compute-Constrained Embedded Gaming Devices NSDI 2024
CE-NAS: An End-to-End Carbon-Efficient Neural Architecture Search Framework NIPS 2024
Faster Diffusion: Rethinking the Role of the Encoder for Diffusion Model Inference NIPS 2024
Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees NIPS 2024
Continual Forgetting for Pre-trained Vision Models CVPR 2024
OneBit: Towards Extremely Low-bit Large Language Models NIPS 2024
Improving Training Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architecture CVPR 2024
DIMAT: Decentralized Iterative Merging-And-Training for Deep Learning Models CVPR 2024
Neural Collapse To Multiple Centers For Imbalanced Data NIPS 2024
The Impact of Geometric Complexity on Neural Collapse in Transfer Learning NIPS 2024
Attention-Driven Training-Free Efficiency Enhancement of Diffusion Models CVPR 2024
From Activation to Initialization: Scaling Insights for Optimizing Neural Fields CVPR 2024
SGD vs GD: Rank Deficiency in Linear Networks NIPS 2024
Neural Redshift: Random Networks are not Random Functions CVPR 2024
Multi-criteria Token Fusion with One-step-ahead Attention for Efficient Vision Transformers CVPR 2024
Tuning Stable Rank Shrinkage: Aiming at the Overlooked Structural Risk in Fine-tuning CVPR 2024
Zero-TPrune: Zero-Shot Token Pruning through Leveraging of the Attention Graph in Pre-Trained Transformers CVPR 2024
PACE: Marrying generalization in PArameter-efficient fine-tuning with Consistency rEgularization NIPS 2024
Analyzing and Improving the Training Dynamics of Diffusion Models CVPR 2024
Progressive Divide-and-Conquer via Subsampling Decomposition for Accelerated MRI CVPR 2024
Batch Normalization Alleviates the Spectral Bias in Coordinate Networks CVPR 2024
MLP Can Be A Good Transformer Learner CVPR 2024
Instance-Aware Group Quantization for Vision Transformers CVPR 2024
PACE: Pacing Operator Learning to Accurate Optical Field Simulation for Complicated Photonic Devices NIPS 2024