:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Guenter, Valentin Frank Ingmar, Sideris, Athanasios
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2406.04549
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Online Training and Pruning of Deep Reinforcement Learning Networks
by: Guenter, Valentin Frank Ingmar, et al.
Published: (2025)

Complexity-Aware Training of Deep Neural Networks for Optimal Structure Discovery
by: Guenter, Valentin Frank Ingmar, et al.
Published: (2024)

Sparse Explanations of Neural Networks Using Pruned Layer-Wise Relevance Propagation
by: Sarmiento, Paulo Yanez, et al.
Published: (2024)

LayerMerge: Neural Network Depth Compression through Layer Pruning and Merging
by: Kim, Jinuk, et al.
Published: (2024)

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

Training-Free Restoration of Pruned Neural Networks
by: Lee, Keonho, et al.
Published: (2025)

AdaBet: Gradient-free Layer Selection for Efficient Training of Deep Neural Networks
by: Tenison, Irene, et al.
Published: (2025)

Post-Training Neural Network Pruning using Graph Curvature
by: Tan, Shuhang, et al.
Published: (2026)

ICE-Pruning: An Iterative Cost-Efficient Pruning Pipeline for Deep Neural Networks
by: Hu, Wenhao, et al.
Published: (2025)

Pruning Deep Convolutional Neural Network Using Conditional Mutual Information
by: Vu-Van, Tien, et al.
Published: (2024)

Spectral Pruning for Recurrent Neural Networks
by: Furuya, Takashi, et al.
Published: (2021)

LNPT: Label-free Network Pruning and Training
by: Xiao, Jinying, et al.
Published: (2024)

Joint Pruning and Channel-wise Mixed-Precision Quantization for Efficient Deep Neural Networks
by: Motetti, Beatrice Alessandra, et al.
Published: (2024)

On-Device Training of Fully Quantized Deep Neural Networks on Cortex-M Microcontrollers
by: Deutel, Mark, et al.
Published: (2024)

Pruning Deep Neural Networks via a Combination of the Marchenko-Pastur Distribution and Regularization
by: Berlyand, Leonid, et al.
Published: (2025)

LION-DG: Layer-Informed Initialization with Deep Gradient Protocols for Accelerated Neural Network Training
by: Kim, Hyunjun
Published: (2026)

On the Hardness of Training Deep Neural Networks Discretely
by: Doron-Arad, Ilan
Published: (2024)

Explore and Establish Synergistic Effects Between Weight Pruning and Coreset Selection in Neural Network Training
by: Wan, Weilin, et al.
Published: (2025)

IDAP++: Advancing Divergence-Based Pruning via Filter-Level and Layer-Level Optimization
by: Samarin, Aleksei, et al.
Published: (2025)

Privacy-Preserving 3-Layer Neural Network Training
by: Chiang, John
Published: (2023)

Layer-Adaptive State Pruning for Deep State Space Models
by: Gwak, Minseon, et al.
Published: (2024)

Mutual Information Preserving Neural Network Pruning
by: Westphal, Charles, et al.
Published: (2024)

Pruning and Quantization Impact on Graph Neural Networks
by: Khedri, Khatoon, et al.
Published: (2025)

Node Perturbation Can Effectively Train Multi-Layer Neural Networks
by: Dalm, Sander, et al.
Published: (2023)

Training Deep Morphological Neural Networks as Universal Approximators
by: Fotopoulos, Konstantinos, et al.
Published: (2025)

Layer Embedding Deep Fusion Graph Neural Network
by: Xu, Taihua, et al.
Published: (2026)

Adaptive Pruning of Deep Neural Networks for Resource-Aware Embedded Intrusion Detection on the Edge
by: Broggi, Alexandre, et al.
Published: (2025)

Robust Neural Pruning with Gradient Sampling Optimization for Residual Neural Networks
by: Yun, Juyoung
Published: (2023)

Enhancing Certifiable Semantic Robustness via Robust Pruning of Deep Neural Networks
by: Hu, Hanjiang, et al.
Published: (2025)

FGFP: A Fractional Gaussian Filter and Pruning for Deep Neural Networks Compression
by: Tu, Kuan-Ting, et al.
Published: (2025)

A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations
by: Cheng, Hongrong, et al.
Published: (2023)

Exact Gauss-Newton Optimization for Training Deep Neural Networks
by: Korbit, Mikalai, et al.
Published: (2024)

Mathematical Modeling and Convergence Analysis of Deep Neural Networks with Dense Layer Connectivities in Deep Learning
by: Huang, Jinshu, et al.
Published: (2025)

Symbol Correctness in Deep Neural Networks Containing Symbolic Layers
by: Bembenek, Aaron, et al.
Published: (2024)

Automatic Joint Structured Pruning and Quantization for Efficient Neural Network Training and Compression
by: Qu, Xiaoyi, et al.
Published: (2025)

Shapley Pruning for Neural Network Compression
by: Adamczewski, Kamil, et al.
Published: (2024)

Convex Formulations for Training Two-Layer ReLU Neural Networks
by: Prakhya, Karthik, et al.
Published: (2024)

PruneSymNet: A Symbolic Neural Network and Pruning Algorithm for Symbolic Regression
by: Wu, Min, et al.
Published: (2024)

FALCON: FLOP-Aware Combinatorial Optimization for Neural Network Pruning
by: Meng, Xiang, et al.
Published: (2024)

Exploring Vision Neural Network Pruning via Screening Methodology
by: Wang, Mingyuan, et al.
Published: (2025)