:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Sundaram, Ganesh, Ulmen, Jonas, Haider, Amjad, Görges, Daniel
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	https://arxiv.org/abs/2507.14882
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Enhanced Pruning Strategy for Multi-Component Neural Architectures Using Component-Aware Graph Analysis
di: Sundaram, Ganesh, et al.
Pubblicazione: (2025)

COMponent-Aware Pruning for Accelerated Control Tasks in Latent Space Models
di: Sundaram, Ganesh, et al.
Pubblicazione: (2025)

Component-Aware Pruning Framework for Neural Network Controllers via Gradient-Based Importance Estimation
di: Sundaram, Ganesh, et al.
Pubblicazione: (2026)

Learning State-Space Models of Dynamic Systems from Arbitrary Data using Joint Embedding Predictive Architectures
di: Ulmen, Jonas, et al.
Pubblicazione: (2025)

State Derivative Normalization for Continuous-Time Deep Neural Networks
di: Weigand, Jonas, et al.
Pubblicazione: (2024)

A Latent Space Framework for Modeling Transient Engine Emissions Using Joint Embedding Predictive Architectures
di: Sundaram, Ganesh, et al.
Pubblicazione: (2026)

Flow-Aware GNN for Transmission Network Reconfiguration via Substation Breaker Optimization
di: Meng, Dekang, et al.
Pubblicazione: (2025)

Exchangeability in Neural Network and its Application to Dynamic Pruning
di: Pu, et al.
Pubblicazione: (2025)

Resource-Aware Neural Network Pruning Using Graph-based Reinforcement Learning
di: Balemans, Dieter, et al.
Pubblicazione: (2025)

C-SWAP: Explainability-Aware Structured Pruning for Efficient Neural Networks Compression
di: Bauvin, Baptiste, et al.
Pubblicazione: (2025)

MPruner: Optimizing Neural Network Size with CKA-Based Mutual Information Pruning
di: Hu, Seungbeom, et al.
Pubblicazione: (2024)

Prune 'n Predict: Optimizing LLM Decision-making with Conformal Prediction
di: Vishwakarma, Harit, et al.
Pubblicazione: (2024)

SPAP: Structured Pruning via Alternating Optimization and Penalty Methods
di: Hu, Hanyu, et al.
Pubblicazione: (2025)

Orthogonal Soft Pruning for Efficient Class Unlearning
di: Gong, Qinghui, et al.
Pubblicazione: (2025)

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

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

SPEAR: Structured Pruning for Spiking Neural Networks via Synaptic Operation Estimation and Reinforcement Learning
di: Xie, Hui, et al.
Pubblicazione: (2025)

Max-Affine Spline Insights Into Deep Network Pruning
di: You, Haoran, et al.
Pubblicazione: (2021)

Layerwise LQR for Geometry-Aware Optimization of Deep Networks
di: Dufort-Labbé, Simon, et al.
Pubblicazione: (2026)

The Graphon Limit Hypothesis: Understanding Neural Network Pruning via Infinite Width Analysis
di: Pham, Hoang, et al.
Pubblicazione: (2025)

GPrune-LLM: Generalization-Aware Structured Pruning for Large Language Models
di: Liu, Xiaoyun, et al.
Pubblicazione: (2026)

Compressing Deep Reinforcement Learning Networks with a Dynamic Structured Pruning Method for Autonomous Driving
di: Su, Wensheng, et al.
Pubblicazione: (2024)

Wanda++: Pruning Large Language Models via Regional Gradients
di: Yang, Yifan, et al.
Pubblicazione: (2025)

Principal Components for Neural Network Initialization
di: Phan, Nhan, et al.
Pubblicazione: (2025)

Hierarchical Zero-Order Optimization for Deep Neural Networks
di: Cao, Sansheng, et al.
Pubblicazione: (2026)

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

Locality-Aware Redundancy Pruning for LLM Depth Compression
di: Yun, Vincent-Daniel, et al.
Pubblicazione: (2026)

Graph Neural Networks with Feature and Structure Aware Random Walk
di: Zhuo, Wei, et al.
Pubblicazione: (2021)

Climate Aware Deep Neural Networks (CADNN) for Wind Power Simulation
di: Forootani, Ali, et al.
Pubblicazione: (2024)

Adaptive Pruning for Large Language Models with Structural Importance Awareness
di: Zheng, Haotian, et al.
Pubblicazione: (2024)

Pruning-based Data Selection and Network Fusion for Efficient Deep Learning
di: Kousar, Humaira, et al.
Pubblicazione: (2025)

Spectral Theory for Edge Pruning in Asynchronous Recurrent Graph Neural Networks
di: Bessone, Nicolas
Pubblicazione: (2025)

Budgeted Broadcast: An Activity-Dependent Pruning Rule for Neural Network Efficiency
di: Meirovitch, Yaron, et al.
Pubblicazione: (2025)

Hierarchical Attention-based Graph Neural Network with Relevance-driven Pruning
di: Kum, Seungwoo
Pubblicazione: (2026)

The Neural Pruning Law Hypothesis
di: Barbulescu, Eugen, et al.
Pubblicazione: (2025)

ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing
di: Tew, Hwa Hui, et al.
Pubblicazione: (2025)

Sensitivity-Aware Mixed-Precision Quantization and Width Optimization of Deep Neural Networks Through Cluster-Based Tree-Structured Parzen Estimation
di: Azizi, Seyedarmin, et al.
Pubblicazione: (2023)

An Efficient Sparse Fine-Tuning with Low Quantization Error via Neural Network Pruning
di: Li, Cen-Jhih, et al.
Pubblicazione: (2025)

Detection of Odor Presence via Deep Neural Networks
di: Hassanloo, Matin, et al.
Pubblicazione: (2025)

Diversity-Aware Adaptive Collocation for Physics-Informed Neural Networks via Sparse QUBO Optimization and Hybrid Coresets
di: Salloum, Hadi, et al.
Pubblicazione: (2026)