Copertina

The Simpler The Better: An Entropy-Based Importance Metric To Reduce Neural Networks' Depth

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Quétu, Victor, Liao, Zhu, Tartaglione, Enzo
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

DSD$^2$: Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free?
di: Quétu, Victor, et al.
Pubblicazione: (2023)

Layer Collapse Can be Induced by Unstructured Pruning
di: Liao, Zhu, et al.
Pubblicazione: (2024)

Till the Layers Collapse: Compressing a Deep Neural Network through the Lenses of Batch Normalization Layers
di: Liao, Zhu, et al.
Pubblicazione: (2024)

LaCoOT: Layer Collapse through Optimal Transport
di: Quétu, Victor, et al.
Pubblicazione: (2024)

Memory-Optimized Once-For-All Network
di: Girard, Maxime, et al.
Pubblicazione: (2024)

Efficient Adaptation of Deep Neural Networks for Semantic Segmentation in Space Applications
di: Olivi, Leonardo, et al.
Pubblicazione: (2025)

Efficient Resource-Constrained Training of Transformers via Subspace Optimization
di: Nguyen, Le-Trung, et al.
Pubblicazione: (2025)

WaterMAS: Sharpness-Aware Maximization for Neural Network Watermarking
di: Trias, Carl De Sousa, et al.
Pubblicazione: (2024)

The Importance of Model Inspection for Better Understanding Performance Characteristics of Graph Neural Networks
di: Shehata, Nairouz, et al.
Pubblicazione: (2024)

Hoeffding Concept Bottleneck Models with Applications to Overhead Images
di: Bénard, Clément, et al.
Pubblicazione: (2026)

Combinatorial Approximations for Cluster Deletion: Simpler, Faster, and Better
di: Balmaseda, Vicente, et al.
Pubblicazione: (2024)

TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series
di: Ashok, Arjun, et al.
Pubblicazione: (2023)

Unsupervised Learning of Unbiased Visual Representations
di: Barbano, Carlo Alberto, et al.
Pubblicazione: (2022)

HYGENE: A Diffusion-based Hypergraph Generation Method
di: Gailhard, Dorian, et al.
Pubblicazione: (2024)

Feature-Aware (Hyper)graph Generation via Next-Scale Prediction
di: Gailhard, Dorian, et al.
Pubblicazione: (2025)

Memory Constrained Dynamic Subnetwork Update for Transfer Learning
di: Quélennec, Aël, et al.
Pubblicazione: (2025)

SimDiff: Simpler Yet Better Diffusion Model for Time Series Point Forecasting
di: Ding, Hang, et al.
Pubblicazione: (2025)

Reducing Storage of Pretrained Neural Networks by Rate-Constrained Quantization and Entropy Coding
di: Conzelmann, Alexander, et al.
Pubblicazione: (2025)

Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device Learning
di: Nguyen, Le-Trung, et al.
Pubblicazione: (2025)

Neural Velocity for hyperparameter tuning
di: Dalmasso, Gianluca, et al.
Pubblicazione: (2025)

The silence of the weights: a structural pruning strategy for attention-based audio signal architectures with second order metrics
di: Diecidue, Andrea, et al.
Pubblicazione: (2025)

Better and Simpler Lower Bounds for Differentially Private Statistical Estimation
di: Narayanan, Shyam
Pubblicazione: (2023)

Supervised Metric Regularization Through Alternating Optimization for Multi-Regime Physics-Informed Neural Networks
di: Spotorno, Enzo Nicolas, et al.
Pubblicazione: (2026)

Study of Training Dynamics for Memory-Constrained Fine-Tuning
di: Quélennec, Aël, et al.
Pubblicazione: (2025)

Beyond Task Vectors: Selective Task Arithmetic Based on Importance Metrics
di: Bowen, Tian, et al.
Pubblicazione: (2024)

Weighted Ensemble Models Are Strong Continual Learners
di: Marouf, Imad Eddine, et al.
Pubblicazione: (2023)

Multi-Turn Jailbreaks Are Simpler Than They Seem
di: Yang, Xiaoxue, et al.
Pubblicazione: (2025)

How I Met Your Bias: Investigating Bias Amplification in Diffusion Models
di: Roos, Nathan, et al.
Pubblicazione: (2025)

Packed-Ensembles for Efficient Uncertainty Estimation
di: Laurent, Olivier, et al.
Pubblicazione: (2022)

Orthogonal Gradient Boosting for Simpler Additive Rule Ensembles
di: Yang, Fan, et al.
Pubblicazione: (2024)

Optimal Depth of Neural Networks
di: Qi, Qian
Pubblicazione: (2025)

Improved Depth Estimation of Bayesian Neural Networks
di: van Erp, Bart, et al.
Pubblicazione: (2024)

Activation Map Compression through Tensor Decomposition for Deep Learning
di: Nguyen, Le-Trung, et al.
Pubblicazione: (2024)

A Simpler Alternative to Variational Regularized Counterfactual Risk Minimization
di: Bakker, Hua Chang, et al.
Pubblicazione: (2024)

OccamNets: Mitigating Dataset Bias by Favoring Simpler Hypotheses
di: Shrestha, Robik, et al.
Pubblicazione: (2022)

Deep Grokking: Would Deep Neural Networks Generalize Better?
di: Fan, Simin, et al.
Pubblicazione: (2024)

Neural Networks for Generating Better Local Optima in Topology Optimization
di: Herrmann, Leon, et al.
Pubblicazione: (2024)

ESPO: Entropy Importance Sampling Policy Optimization
di: Sheng, Yuepeng, et al.
Pubblicazione: (2025)

Entropy Meets Importance: A Unified Head Importance-Entropy Score for Stable and Efficient Transformer Pruning
di: Choi, Minsik, et al.
Pubblicazione: (2025)

Neural Networks Use Distance Metrics
di: Oursland, Alan
Pubblicazione: (2024)