:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Dabounou, Jaouad
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2409.02410
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Adaptive Feedforward Gradient Estimation in Neural ODEs
by: Dabounou, Jaouad
Published: (2024)

Enhancing Neural Network Interpretability Through Conductance-Based Information Plane Analysis
by: Dabounou, Jaouad, et al.
Published: (2024)

Estimation of discrete distributions in relative entropy, and the deviations of the missing mass
by: Mourtada, Jaouad
Published: (2025)

Enhancing Pre-Trained Model-Based Class-Incremental Learning through Neural Collapse
by: He, Kun, et al.
Published: (2025)

Progressive Monitoring of Generative Model Training Evolution
by: Prasad, Vidya, et al.
Published: (2024)

Enhancing Signed Graph Neural Networks through Curriculum-Based Training
by: Zhang, Zeyu, et al.
Published: (2023)

Quantifying Emergence in Neural Networks: Insights from Pruning and Training Dynamics
by: AlShinaifi, Faisal, et al.
Published: (2024)

An Adaptive and Stability-Promoting Layerwise Training Approach for Sparse Deep Neural Network Architecture
by: Krishnanunni, C G, et al.
Published: (2022)

HiPreNets: High-Precision Neural Networks through Progressive Training
by: Mulle, Ethan, et al.
Published: (2025)

Automatic Stability and Recovery for Neural Network Training
by: Or, Barak
Published: (2026)

Finite-sample performance of the maximum likelihood estimator in logistic regression
by: Chardon, Hugo, et al.
Published: (2024)

Stability and Generalization of Quantum Neural Networks
by: Yang, Jiaqi, et al.
Published: (2025)

Enhancing Stability of Physics-Informed Neural Network Training Through Saddle-Point Reformulation
by: Bylinkin, Dmitry, et al.
Published: (2025)

Class Adaptive Conformal Training
by: Marani, Badr-Eddine, et al.
Published: (2026)

Skill-Targeted Adaptive Training
by: He, Yinghui, et al.
Published: (2025)

Universal coding, intrinsic volumes, and metric complexity
by: Mourtada, Jaouad
Published: (2023)

Adaptive Progressive Attention Graph Neural Network for EEG Emotion Recognition
by: Feng, Tianzhi, et al.
Published: (2025)

Adaptive Momentum and Nonlinear Damping for Neural Network Training
by: Karoni, Aikaterini, et al.
Published: (2026)

Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning
by: Huang, Zheng, et al.
Published: (2024)

Enhancing Stability in Training Conditional Generative Adversarial Networks via Selective Data Matching
by: Kong, Kyeongbo, et al.
Published: (2021)

Layerwise Progressive Freezing Enables STE-Free Training of Deep Binary Neural Networks
by: Smith, Evan Gibson, et al.
Published: (2026)

Investigating Target Class Influence on Neural Network Compressibility for Energy-Autonomous Avian Monitoring
by: Brolich, Nina, et al.
Published: (2026)

Enhancing Deep Neural Network Training Efficiency and Performance through Linear Prediction
by: Ying, Hejie, et al.
Published: (2023)

Randomized Neural Network with Adaptive Forward Regularization for Online Task-free Class Incremental Learning
by: Wang, Junda, et al.
Published: (2025)

An Adaptive Method Stabilizing Activations for Enhanced Generalization
by: Seung, Hyunseok, et al.
Published: (2025)

Advancing Neural Network Performance through Emergence-Promoting Initialization Scheme
by: Li, Johnny Jingze, et al.
Published: (2024)

Dynamic DropConnect: Enhancing Neural Network Robustness through Adaptive Edge Dropping Strategies
by: Yang, Yuan-Chih, et al.
Published: (2025)

Enhancing the Expressivity of Temporal Graph Networks through Source-Target Identification
by: Tjandra, Benedict Aaron, et al.
Published: (2024)

Information Geometry of Evolution of Neural Network Parameters While Training
by: Thiruthummal, Abhiram Anand, et al.
Published: (2024)

Dual Prototypes for Adaptive Pre-Trained Model in Class-Incremental Learning
by: Xu, Zhiming, et al.
Published: (2024)

Learn2Mix: Training Neural Networks Using Adaptive Data Integration
by: Venkatasubramanian, Shyam, et al.
Published: (2024)

Step by Step: Adaptive Gradient Descent for Training L-Lipschitz Neural Networks
by: Sung, Kyle, et al.
Published: (2025)

Understanding the Evolution of the Neural Tangent Kernel at the Edge of Stability
by: Jiang, Kaiqi, et al.
Published: (2025)

Correct-By-Construction: Certified Individual Fairness through Neural Network Training
by: Zhang, Ruihan, et al.
Published: (2025)

Explaining Grokking and Information Bottleneck through Neural Collapse Emergence
by: Sakamoto, Keitaro, et al.
Published: (2025)

The Nyström method for convex loss functions
by: Della Vecchia, Andrea, et al.
Published: (2020)

Enhancing Stability for Large Language Models Training in Constrained Bandwidth Networks
by: Dai, Yun, et al.
Published: (2024)

Enhancing Robustness of Graph Neural Networks through p-Laplacian
by: Sirohi, Anuj Kumar, et al.
Published: (2024)

Enhancing Robustness of Graph Neural Networks through p-Laplacian
by: Sirohi, Anuj Kumar, et al.
Published: (2025)

Growing Neural Networks: Dynamic Evolution through Gradient Descent
by: Radhakrishnan, Anil, et al.
Published: (2025)