Training Multi-Layer Binary Neural Networks With Local Binary Error Signals
Fuente:
arXiv
Saved in:
| Main Authors: | Colombo, Luca, Pittorino, Fabrizio, Roveri, Manuel |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
BEP: A Binary Error Propagation Algorithm for Binary Neural Networks Training
by: Colombo, Luca, et al.
Published: (2025)
by: Colombo, Luca, et al.
Published: (2025)
Architecture-Aware Minimization (A$^2$M): How to Find Flat Minima in Neural Architecture Search
by: Gambella, Matteo, et al.
Published: (2025)
by: Gambella, Matteo, et al.
Published: (2025)
NITRO-D: Native Integer-only Training of Deep Convolutional Neural Networks
by: Pirillo, Alberto, et al.
Published: (2024)
by: Pirillo, Alberto, et al.
Published: (2024)
Advancing the Biological Plausibility and Efficacy of Hebbian Convolutional Neural Networks
by: Nimmo, Julian Jimenez, et al.
Published: (2025)
by: Nimmo, Julian Jimenez, et al.
Published: (2025)
Variational Autoregressive Networks with probability priors
by: Białas, Piotr, et al.
Published: (2026)
by: Białas, Piotr, et al.
Published: (2026)
Neural Vector Tomography for Reconstructing a Magnetization Vector Field
by: Butbaia, Giorgi, et al.
Published: (2024)
by: Butbaia, Giorgi, et al.
Published: (2024)
Graph Expansion in Pruned Recurrent Neural Network Layers Preserve Performance
by: Kalra, Suryam Arnav, et al.
Published: (2024)
by: Kalra, Suryam Arnav, et al.
Published: (2024)
Binary Apollonian networks
by: Souza, Eduardo M. K., et al.
Published: (2022)
by: Souza, Eduardo M. K., et al.
Published: (2022)
Learn&Drop: Fast Learning of CNNs based on Layer Dropping
by: Cruciata, Giorgio, et al.
Published: (2026)
by: Cruciata, Giorgio, et al.
Published: (2026)
What changes after deployment? A survey on On-device Learning in TinyML
by: Pavan, Massimo, et al.
Published: (2026)
by: Pavan, Massimo, et al.
Published: (2026)
Graph Neural Networks Based Deep Learning for Predicting Structural and Electronic Properties
by: Selvaraj, Selva Chandrasekaran
Published: (2024)
by: Selvaraj, Selva Chandrasekaran
Published: (2024)
Pulling Back the Curtain on Deep Networks
by: Satkiewicz, Maciej, et al.
Published: (2025)
by: Satkiewicz, Maciej, et al.
Published: (2025)
Multi-objective Binary Coordinate Search for Feature Selection
by: Miyandoab, Sevil Zanjani, et al.
Published: (2024)
by: Miyandoab, Sevil Zanjani, et al.
Published: (2024)
HERCULES: Hardware-Efficient, Robust, Continual Learning Neural Architecture Search
by: Gambella, Matteo, et al.
Published: (2026)
by: Gambella, Matteo, et al.
Published: (2026)
Impact of dendritic non-linearities on the computational capabilities of neurons
by: Lauditi, Clarissa, et al.
Published: (2024)
by: Lauditi, Clarissa, et al.
Published: (2024)
On the Atypical Solutions of the Symmetric Binary Perceptron
by: Barbier, Damien, et al.
Published: (2023)
by: Barbier, Damien, et al.
Published: (2023)
Self-Distillation Learning Based on Temporal-Spatial Consistency for Spiking Neural Networks
by: Zuo, Lin, et al.
Published: (2024)
by: Zuo, Lin, et al.
Published: (2024)
Alternating Gradient Flow Utility: A Unified Metric for Structural Pruning and Dynamic Routing in Deep Networks
by: Qian, Tianhao, et al.
Published: (2026)
by: Qian, Tianhao, et al.
Published: (2026)
Can Geometric Quantum Machine Learning Lead to Advantage in Barcode Classification?
by: Umeano, Chukwudubem, et al.
Published: (2024)
by: Umeano, Chukwudubem, et al.
Published: (2024)
A Phase Transition in Diffusion Models Reveals the Hierarchical Nature of Data
by: Sclocchi, Antonio, et al.
Published: (2024)
by: Sclocchi, Antonio, et al.
Published: (2024)
The Interconnection Tensor Rank and the Neural Network Storage Capacity
by: Kryzhanovsky, Boris V.
Published: (2025)
by: Kryzhanovsky, Boris V.
Published: (2025)
Auxiliary Physics-Informed Neural Networks for Forward, Inverse, and Coupled Radiative Transfer Problems
by: Riganti, Roberto, et al.
Published: (2023)
by: Riganti, Roberto, et al.
Published: (2023)
Hierarchical Associative Memory, Parallelized MLP-Mixer, and Symmetry Breaking
by: Karakida, Ryo, et al.
Published: (2024)
by: Karakida, Ryo, et al.
Published: (2024)
iMixer: hierarchical Hopfield network implies an invertible, implicit and iterative MLP-Mixer
by: Ota, Toshihiro, et al.
Published: (2023)
by: Ota, Toshihiro, et al.
Published: (2023)
Advancing Attribution-Based Neural Network Explainability through Relative Absolute Magnitude Layer-Wise Relevance Propagation and Multi-Component Evaluation
by: Vukadin, Davor, et al.
Published: (2024)
by: Vukadin, Davor, et al.
Published: (2024)
Memorization to Generalization: Emergence of Diffusion Models from Associative Memory
by: Pham, Bao, et al.
Published: (2025)
by: Pham, Bao, et al.
Published: (2025)
NERFIFY: A Multi-Agent Framework for Turning NeRF Papers into Code
by: Jain, Seemandhar, et al.
Published: (2026)
by: Jain, Seemandhar, et al.
Published: (2026)
Benefiting from Quantum? A Comparative Study of Q-Seg, Quantum-Inspired Techniques, and U-Net for Crack Segmentation
by: Srinivasan, Akshaya, et al.
Published: (2024)
by: Srinivasan, Akshaya, et al.
Published: (2024)
The Rules-and-Facts Model for Simultaneous Generalization and Memorization in Neural Networks
by: Farné, Gabriele, et al.
Published: (2026)
by: Farné, Gabriele, et al.
Published: (2026)
Automated Multi-Class Crop Pathology Classification via Convolutional Neural Networks: A Deep Learning Approach for Real-Time Precision Agriculture
by: Suri, Sourish, et al.
Published: (2025)
by: Suri, Sourish, et al.
Published: (2025)
Controlling Recurrent Neural Networks by Conceptors
by: Jaeger, Herbert
Published: (2014)
by: Jaeger, Herbert
Published: (2014)
Do Hopfield Networks Dream of Stored Patterns? A Statistical-Mechanical Theory of Dreaming in Multidirectional Associative Memories
by: Barra, Adriano, et al.
Published: (2026)
by: Barra, Adriano, et al.
Published: (2026)
A Federated Many-to-One Hopfield model for associative Neural Networks
by: Alessandrelli, Andrea, et al.
Published: (2026)
by: Alessandrelli, Andrea, et al.
Published: (2026)
TIFeD: a Tiny Integer-based Federated learning algorithm with Direct feedback alignment
by: Colombo, Luca, et al.
Published: (2024)
by: Colombo, Luca, et al.
Published: (2024)
Unsupervised Learning to Recognize Quantum Phases of Matter
by: Khosrojerdi, Mehran, et al.
Published: (2025)
by: Khosrojerdi, Mehran, et al.
Published: (2025)
Efficient and Flexible Neural Network Training through Layer-wise Feedback Propagation
by: Weber, Leander, et al.
Published: (2023)
by: Weber, Leander, et al.
Published: (2023)
AgenticPruner: MAC-Constrained Neural Network Compression via LLM-Driven Strategy Search
by: Esmat, Shahrzad, et al.
Published: (2026)
by: Esmat, Shahrzad, et al.
Published: (2026)
Effect of Local Topological Changes on Resistance in Tunably-Disordered Networks
by: Wang, Chenxi, et al.
Published: (2026)
by: Wang, Chenxi, et al.
Published: (2026)
Statistical Localization of Electromagnetic Signals in Disordered Time-Varying Cavity
by: Zhou, Bo, et al.
Published: (2024)
by: Zhou, Bo, et al.
Published: (2024)
Envisioning Future Deep Learning Theories: Some Basic Concepts and Characteristics
by: Su, Weijie J.
Published: (2021)
by: Su, Weijie J.
Published: (2021)
Similar Items
-
BEP: A Binary Error Propagation Algorithm for Binary Neural Networks Training
by: Colombo, Luca, et al.
Published: (2025) -
Architecture-Aware Minimization (A$^2$M): How to Find Flat Minima in Neural Architecture Search
by: Gambella, Matteo, et al.
Published: (2025) -
NITRO-D: Native Integer-only Training of Deep Convolutional Neural Networks
by: Pirillo, Alberto, et al.
Published: (2024) -
Advancing the Biological Plausibility and Efficacy of Hebbian Convolutional Neural Networks
by: Nimmo, Julian Jimenez, et al.
Published: (2025) -
Variational Autoregressive Networks with probability priors
by: Białas, Piotr, et al.
Published: (2026)