DSD$^2$: Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free?
Fuente:
arXiv
Saved in:
| Main Authors: | Quétu, Victor, Tartaglione, Enzo |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
The Simpler The Better: An Entropy-Based Importance Metric To Reduce Neural Networks' Depth
by: Quétu, Victor, et al.
Published: (2024)
by: Quétu, Victor, et al.
Published: (2024)
Layer Collapse Can be Induced by Unstructured Pruning
by: Liao, Zhu, et al.
Published: (2024)
by: Liao, Zhu, et al.
Published: (2024)
Till the Layers Collapse: Compressing a Deep Neural Network through the Lenses of Batch Normalization Layers
by: Liao, Zhu, et al.
Published: (2024)
by: Liao, Zhu, et al.
Published: (2024)
LaCoOT: Layer Collapse through Optimal Transport
by: Quétu, Victor, et al.
Published: (2024)
by: Quétu, Victor, et al.
Published: (2024)
Memory-Optimized Once-For-All Network
by: Girard, Maxime, et al.
Published: (2024)
by: Girard, Maxime, et al.
Published: (2024)
Efficient Adaptation of Deep Neural Networks for Semantic Segmentation in Space Applications
by: Olivi, Leonardo, et al.
Published: (2025)
by: Olivi, Leonardo, et al.
Published: (2025)
Manipulating Sparse Double Descent
by: Zhang, Ya Shi
Published: (2024)
by: Zhang, Ya Shi
Published: (2024)
The Double Descent Behavior in Two Layer Neural Network for Binary Classification
by: Abeykoon, Chathurika S, et al.
Published: (2025)
by: Abeykoon, Chathurika S, et al.
Published: (2025)
Efficient Resource-Constrained Training of Transformers via Subspace Optimization
by: Nguyen, Le-Trung, et al.
Published: (2025)
by: Nguyen, Le-Trung, et al.
Published: (2025)
WaterMAS: Sharpness-Aware Maximization for Neural Network Watermarking
by: Trias, Carl De Sousa, et al.
Published: (2024)
by: Trias, Carl De Sousa, et al.
Published: (2024)
Activation Map Compression through Tensor Decomposition for Deep Learning
by: Nguyen, Le-Trung, et al.
Published: (2024)
by: Nguyen, Le-Trung, et al.
Published: (2024)
Hoeffding Concept Bottleneck Models with Applications to Overhead Images
by: Bénard, Clément, et al.
Published: (2026)
by: Bénard, Clément, et al.
Published: (2026)
On the Lipschitz Constant of Deep Networks and Double Descent
by: Gamba, Matteo, et al.
Published: (2023)
by: Gamba, Matteo, et al.
Published: (2023)
Analog Physical Systems Can Exhibit Double Descent
by: Dillavou, Sam, et al.
Published: (2025)
by: Dillavou, Sam, et al.
Published: (2025)
GABIC: Graph-based Attention Block for Image Compression
by: Spadaro, Gabriele, et al.
Published: (2024)
by: Spadaro, Gabriele, et al.
Published: (2024)
How Sparse Can We Prune A Deep Network: A Fundamental Limit Perspective
by: Zhang, Qiaozhe, et al.
Published: (2023)
by: Zhang, Qiaozhe, et al.
Published: (2023)
Unsupervised Learning of Unbiased Visual Representations
by: Barbano, Carlo Alberto, et al.
Published: (2022)
by: Barbano, Carlo Alberto, et al.
Published: (2022)
Two Sparse Matrices are Better than One: Sparsifying Neural Networks with Double Sparse Factorization
by: Boža, Vladimír, et al.
Published: (2024)
by: Boža, Vladimír, et al.
Published: (2024)
Feature-Aware (Hyper)graph Generation via Next-Scale Prediction
by: Gailhard, Dorian, et al.
Published: (2025)
by: Gailhard, Dorian, et al.
Published: (2025)
Memory Constrained Dynamic Subnetwork Update for Transfer Learning
by: Quélennec, Aël, et al.
Published: (2025)
by: Quélennec, Aël, et al.
Published: (2025)
HYGENE: A Diffusion-based Hypergraph Generation Method
by: Gailhard, Dorian, et al.
Published: (2024)
by: Gailhard, Dorian, et al.
Published: (2024)
Least Squares Regression Can Exhibit Under-Parameterized Double Descent
by: Li, Xinyue, et al.
Published: (2023)
by: Li, Xinyue, et al.
Published: (2023)
Bayesian Double Descent
by: Polson, Nick, et al.
Published: (2025)
by: Polson, Nick, et al.
Published: (2025)
Beyond Low-rank Decomposition: A Shortcut Approach for Efficient On-Device Learning
by: Nguyen, Le-Trung, et al.
Published: (2025)
by: Nguyen, Le-Trung, et al.
Published: (2025)
Neural Velocity for hyperparameter tuning
by: Dalmasso, Gianluca, et al.
Published: (2025)
by: Dalmasso, Gianluca, et al.
Published: (2025)
The silence of the weights: a structural pruning strategy for attention-based audio signal architectures with second order metrics
by: Diecidue, Andrea, et al.
Published: (2025)
by: Diecidue, Andrea, et al.
Published: (2025)
Study of Training Dynamics for Memory-Constrained Fine-Tuning
by: Quélennec, Aël, et al.
Published: (2025)
by: Quélennec, Aël, et al.
Published: (2025)
Dropout Drops Double Descent
by: Yang, Tian-Le, et al.
Published: (2023)
by: Yang, Tian-Le, et al.
Published: (2023)
Weighted Ensemble Models Are Strong Continual Learners
by: Marouf, Imad Eddine, et al.
Published: (2023)
by: Marouf, Imad Eddine, et al.
Published: (2023)
Double Descent and Other Interpolation Phenomena in GANs
by: Luzi, Lorenzo, et al.
Published: (2021)
by: Luzi, Lorenzo, et al.
Published: (2021)
Stochastic Gradient Descent for Two-layer Neural Networks
by: Cao, Dinghao, et al.
Published: (2024)
by: Cao, Dinghao, et al.
Published: (2024)
Variational Stochastic Gradient Descent for Deep Neural Networks
by: Chen, Haotian, et al.
Published: (2024)
by: Chen, Haotian, et al.
Published: (2024)
Denoising Diffusion Probabilistic Model for Point Cloud Compression at Low Bit-Rates
by: Spadaro, Gabriele, et al.
Published: (2025)
by: Spadaro, Gabriele, et al.
Published: (2025)
Hybrid Coordinate Descent for Efficient Neural Network Learning Using Line Search and Gradient Descent
by: Hsiao, Yen-Che, et al.
Published: (2024)
by: Hsiao, Yen-Che, et al.
Published: (2024)
Can We Understand Plasticity Through Neural Collapse?
by: Bonifazi, Guglielmo, et al.
Published: (2024)
by: Bonifazi, Guglielmo, et al.
Published: (2024)
Rethinking Impersonation and Dodging Attacks on Face Recognition Systems
by: Zhou, Fengfan, et al.
Published: (2024)
by: Zhou, Fengfan, et al.
Published: (2024)
How I Met Your Bias: Investigating Bias Amplification in Diffusion Models
by: Roos, Nathan, et al.
Published: (2025)
by: Roos, Nathan, et al.
Published: (2025)
Sparse Covariance Neural Networks
by: Cavallo, Andrea, et al.
Published: (2024)
by: Cavallo, Andrea, et al.
Published: (2024)
Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks
by: Wang, Puyu, et al.
Published: (2023)
by: Wang, Puyu, et al.
Published: (2023)
Generalization Bounds of Stochastic Gradient Descent in Homogeneous Neural Networks
by: Ma, Wenquan, et al.
Published: (2026)
by: Ma, Wenquan, et al.
Published: (2026)
Similar Items
-
The Simpler The Better: An Entropy-Based Importance Metric To Reduce Neural Networks' Depth
by: Quétu, Victor, et al.
Published: (2024) -
Layer Collapse Can be Induced by Unstructured Pruning
by: Liao, Zhu, et al.
Published: (2024) -
Till the Layers Collapse: Compressing a Deep Neural Network through the Lenses of Batch Normalization Layers
by: Liao, Zhu, et al.
Published: (2024) -
LaCoOT: Layer Collapse through Optimal Transport
by: Quétu, Victor, et al.
Published: (2024) -
Memory-Optimized Once-For-All Network
by: Girard, Maxime, et al.
Published: (2024)