Architecture-Aware Minimization (A$^2$M): How to Find Flat Minima in Neural Architecture Search

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Gambella, Matteo, Pittorino, Fabrizio, Roveri, Manuel
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Disordered Systems and Neural Networks Computer Vision and Pattern Recognition 68T07
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

HERCULES: Hardware-Efficient, Robust, Continual Learning Neural Architecture Search
di: Gambella, Matteo, et al.
Pubblicazione: (2026)

NACHOS: Neural Architecture Search for Hardware Constrained Early Exit Neural Networks
di: Gambella, Matteo, et al.
Pubblicazione: (2024)

SEAL: Searching Expandable Architectures for Incremental Learning
di: Gambella, Matteo, et al.
Pubblicazione: (2025)

Training Multi-Layer Binary Neural Networks With Local Binary Error Signals
di: Colombo, Luca, et al.
Pubblicazione: (2024)

FlatNAS: optimizing Flatness in Neural Architecture Search for Out-of-Distribution Robustness
di: Gambella, Matteo, et al.
Pubblicazione: (2024)

SQUAD: Scalable Quorum Adaptive Decisions via ensemble of early exit neural networks
di: Gambella, Matteo, et al.
Pubblicazione: (2026)

Neural Vector Tomography for Reconstructing a Magnetization Vector Field
di: Butbaia, Giorgi, et al.
Pubblicazione: (2024)

BEP: A Binary Error Propagation Algorithm for Binary Neural Networks Training
di: Colombo, Luca, et al.
Pubblicazione: (2025)

Sequential Learning and Catastrophic Forgetting in Differentiable Resistor Networks
di: Ibrahim, Maniru
Pubblicazione: (2026)

Finding Some Impossibility of Flat-Folding of Given Origami Crease Pattern by Graphical Representation
di: Nakajima, Chihiro
Pubblicazione: (2025)

Planarian Neural Networks: Evolutionary Patterns from Basic Bilateria Shaping Modern Artificial Neural Network Architectures
di: Huang, Ziyuan, et al.
Pubblicazione: (2025)

Impact of dendritic non-linearities on the computational capabilities of neurons
di: Lauditi, Clarissa, et al.
Pubblicazione: (2024)

Can Geometric Quantum Machine Learning Lead to Advantage in Barcode Classification?
di: Umeano, Chukwudubem, et al.
Pubblicazione: (2024)

A Phase Transition in Diffusion Models Reveals the Hierarchical Nature of Data
di: Sclocchi, Antonio, et al.
Pubblicazione: (2024)

Hierarchical Associative Memory, Parallelized MLP-Mixer, and Symmetry Breaking
di: Karakida, Ryo, et al.
Pubblicazione: (2024)

iMixer: hierarchical Hopfield network implies an invertible, implicit and iterative MLP-Mixer
di: Ota, Toshihiro, et al.
Pubblicazione: (2023)

Memorization to Generalization: Emergence of Diffusion Models from Associative Memory
di: Pham, Bao, et al.
Pubblicazione: (2025)

Proximity-Based Evidence Retrieval for Uncertainty-Aware Neural Networks
di: Gharoun, Hassan, et al.
Pubblicazione: (2025)

Benefiting from Quantum? A Comparative Study of Q-Seg, Quantum-Inspired Techniques, and U-Net for Crack Segmentation
di: Srinivasan, Akshaya, et al.
Pubblicazione: (2024)

Exploring the Intersection between Neural Architecture Search and Continual Learning
di: Shahawy, Mohamed, et al.
Pubblicazione: (2022)

Spectral Architecture Search for Neural Network Models
di: Peri, Gianluca, et al.
Pubblicazione: (2025)

Fast Data Aware Neural Architecture Search via Supernet Accelerated Evaluation
di: Njor, Emil, et al.
Pubblicazione: (2025)

Towards Distributed Neural Architectures
di: Cowsik, Aditya, et al.
Pubblicazione: (2025)

Exploring Non-Steady-State Charge Transport Dynamics in Information Processing: Insights from Reservoir Computing
di: Li, Zheyang, et al.
Pubblicazione: (2023)

DYNAMAX: Dynamic computing for Transformers and Mamba based architectures
di: Nogales, Miguel, et al.
Pubblicazione: (2025)

Envisioning Future Deep Learning Theories: Some Basic Concepts and Characteristics
di: Su, Weijie J.
Pubblicazione: (2021)

Boosting Classification with Quantum-Inspired Augmentations
di: Tschöpe, Matthias, et al.
Pubblicazione: (2025)

Interplay of Flat-band and Anderson localizations in disordered moire superlattices
di: Liu, Qian, et al.
Pubblicazione: (2026)

The Rules-and-Facts Model for Simultaneous Generalization and Memorization in Neural Networks
di: Farné, Gabriele, et al.
Pubblicazione: (2026)

Do Hopfield Networks Dream of Stored Patterns? A Statistical-Mechanical Theory of Dreaming in Multidirectional Associative Memories
di: Barra, Adriano, et al.
Pubblicazione: (2026)

Solving Inverse Problems in Stochastic Self-Organizing Systems through Invariant Representations
di: Najarro, Elias, et al.
Pubblicazione: (2025)

A Federated Many-to-One Hopfield model for associative Neural Networks
di: Alessandrelli, Andrea, et al.
Pubblicazione: (2026)

Statistical mechanics of vector Hopfield network near and above saturation
di: Nicoletti, Flavio, et al.
Pubblicazione: (2025)

Neural network approximation of regularized density functionals
di: Csirik, Mihály A., et al.
Pubblicazione: (2025)

Scaling Laws and Representation Learning in Simple Hierarchical Languages: Transformers vs. Convolutional Architectures
di: Cagnetta, Francesco, et al.
Pubblicazione: (2025)

Minority Takeover in Majority Dynamics: Searching for Rare Initializations via the History Passing Algorithm
di: Jankola, Marek, et al.
Pubblicazione: (2025)

How to Train an Oscillator Ising Machine using Equilibrium Propagation
di: Gower, Alex
Pubblicazione: (2025)

How universal is the mean-field universality class for percolation in complex networks?
di: Cirigliano, Lorenzo
Pubblicazione: (2025)

Anomalous Random Neural Networks: a Special Renewal Process
di: Zhang, Hong, et al.
Pubblicazione: (2024)

Neural Network Quantum States analysis of the Shastry-Sutherland model
di: Mezera, Matěj, et al.
Pubblicazione: (2023)