Image de couverture de livre

Enhancing Deep Neural Network Training Efficiency and Performance through Linear Prediction

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Ying, Hejie, Song, Mengmeng, Tang, Yaohong, Xiao, Shungen, Xiao, Zimin
Format:	Preprint
Publié:	2023
Sujets:	Machine Learning Computer Vision and Pattern Recognition
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Enhancing Accuracy and Parameter-Efficiency of Neural Representations for Network Parameterization
par: Choi, Hongjun, et autres
Publié: (2024)

Enhancing Semi-Supervised Multi-View Graph Convolutional Networks via Supervised Contrastive Learning and Self-Training
par: Xiao, Huaiyuan, et autres
Publié: (2025)

On the Efficiency of Convolutional Neural Networks
par: Lavin, Andrew
Publié: (2024)

Sharpness-Aware Minimization with Adaptive Regularization for Training Deep Neural Networks
par: Zou, Jinping, et autres
Publié: (2024)

Shrinking Your TimeStep: Towards Low-Latency Neuromorphic Object Recognition with Spiking Neural Network
par: Ding, Yongqi, et autres
Publié: (2024)

Visual Analysis of Prediction Uncertainty in Neural Networks for Deep Image Synthesis
par: Dutta, Soumya, et autres
Publié: (2024)

Seasonal Fire Prediction using Spatio-Temporal Deep Neural Networks
par: Michail, Dimitrios, et autres
Publié: (2024)

Advancing Neural Network Performance through Emergence-Promoting Initialization Scheme
par: Li, Johnny Jingze, et autres
Publié: (2024)

DPAdapter: Improving Differentially Private Deep Learning through Noise Tolerance Pre-training
par: Wang, Zihao, et autres
Publié: (2024)

Beyond Accuracy: Ensuring Correct Predictions With Correct Rationales
par: Li, Tang, et autres
Publié: (2024)

Enhancing Certifiable Semantic Robustness via Robust Pruning of Deep Neural Networks
par: Hu, Hanjiang, et autres
Publié: (2025)

ReActXGB: A Hybrid Binary Convolutional Neural Network Architecture for Improved Performance and Computational Efficiency
par: Chu, Po-Hsun, et autres
Publié: (2024)

Mask-informed Deep Contrastive Incomplete Multi-view Clustering
par: Li, Zhenglai, et autres
Publié: (2025)

Criticality Leveraged Adversarial Training (CLAT) for Boosted Performance via Parameter Efficiency
par: Gopal, Bhavna, et autres
Publié: (2024)

From Code to Prediction: Fine-Tuning LLMs for Neural Network Performance Classification in NNGPT
par: Hanouneh, Mahmoud, et autres
Publié: (2026)

LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging
par: Kim, Jinuk, et autres
Publié: (2024)

Bayesian Mesh Optimization for Graph Neural Networks to Enhance Engineering Performance Prediction
par: Park, Jangseop, et autres
Publié: (2024)

Dual Precision Deep Neural Network
par: Park, Jae Hyun, et autres
Publié: (2020)

EDA-DM: Enhanced Distribution Alignment for Post-Training Quantization of Diffusion Models
par: Liu, Xuewen, et autres
Publié: (2024)

Tailoring Adversarial Attacks on Deep Neural Networks for Targeted Class Manipulation Using DeepFool Algorithm
par: Labib, S. M. Fazle Rabby, et autres
Publié: (2023)

How to Train Your Metamorphic Deep Neural Network
par: Sommariva, Thomas, et autres
Publié: (2025)

Financial Fraud Identification and Interpretability Study for Listed Companies Based on Convolutional Neural Network
par: Li, Xiao
Publié: (2025)

Compositional Curvature Bounds for Deep Neural Networks
par: Entesari, Taha, et autres
Publié: (2024)

Tuning the Frequencies: Robust Training for Sinusoidal Neural Networks
par: Novello, Tiago, et autres
Publié: (2024)

DQA: An Efficient Method for Deep Quantization of Deep Neural Network Activations
par: Hu, Wenhao, et autres
Publié: (2024)

Complexity of Linear Regions in Self-supervised Deep ReLU Networks
par: Muthivhi, Mufhumudzi, et autres
Publié: (2026)

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data
par: Wisniewski, Mariusz, et autres
Publié: (2024)

An Explainable Fast Deep Neural Network for Emotion Recognition
par: Di Luzio, Francesco, et autres
Publié: (2024)

Calibrating Deep Neural Network using Euclidean Distance
par: Liang, Wenhao, et autres
Publié: (2024)

Revisiting the Evaluation of Deep Neural Networks for Pedestrian Detection
par: Feifel, Patrick, et autres
Publié: (2025)

CycleBNN: Cyclic Precision Training in Binary Neural Networks
par: Fontana, Federico, et autres
Publié: (2024)

Information Geometry of Evolution of Neural Network Parameters While Training
par: Thiruthummal, Abhiram Anand, et autres
Publié: (2024)

Are Sparse Neural Networks Better Hard Sample Learners?
par: Xiao, Qiao, et autres
Publié: (2024)

Iterative Misclassification Error Training (IMET): An Optimized Neural Network Training Technique for Image Classification
par: Singh, Ruhaan, et autres
Publié: (2025)

ReSpike: Residual Frames-based Hybrid Spiking Neural Networks for Efficient Action Recognition
par: Xiao, Shiting, et autres
Publié: (2024)

Cross-Organ Domain Adaptive Neural Network for Pancreatic Endoscopic Ultrasound Image Segmentation
par: Yan, ZhiChao, et autres
Publié: (2024)

The Impact of Background Removal on Performance of Neural Networks for Fashion Image Classification and Segmentation
par: Liang, Junhui, et autres
Publié: (2023)

U-Harmony: Enhancing Joint Training for Segmentation Models with Universal Harmonization
par: Ma, Weiwei, et autres
Publié: (2026)

Revitalizing Electoral Trust: Enhancing Transparency and Efficiency through Automated Voter Counting with Machine Learning
par: Faris, Mir, et autres
Publié: (2024)

Understanding Matrix Function Normalizations in Covariance Pooling through the Lens of Riemannian Geometry
par: Chen, Ziheng, et autres
Publié: (2024)