Cover Image

Orthogonal Transforms in Neural Networks Amount to Effective Regularization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zając, Krzysztof, Sopot, Wojciech, Wachel, Paweł
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Neural and Evolutionary Computing Systems and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Scalable and Robust Physics-Informed Graph Neural Networks for Water Distribution Systems
by: Ashraf, Inaam, et al.
Published: (2025)

Power Flow Analysis Using Deep Neural Networks in Three-Phase Unbalanced Smart Distribution Grids
by: Tiwari, Deepak, et al.
Published: (2024)

Control-Theoretic Techniques for Online Adaptation of Deep Neural Networks in Dynamical Systems
by: Elkins, Jacob G., et al.
Published: (2024)

SCAR: State-Space Compression for Scalable AI-Based Network Management of Vehicular Services
by: Comsa, Ioan-Sorin, et al.
Published: (2025)

Safe PDE Boundary Control with Neural Operators
by: Hu, Hanjiang, et al.
Published: (2024)

Application of Zone Method based Physics-Informed Neural Networks in Reheating Furnaces
by: Dutta, Ujjal Kr, et al.
Published: (2023)

Designing Robust Software Sensors for Nonlinear Systems via Neural Networks and Adaptive Sliding Mode Control
by: Farkane, Ayoub, et al.
Published: (2025)

Real-Time Recurrent Reinforcement Learning
by: Lemmel, Julian, et al.
Published: (2023)

Curriculum-Learned Vanishing Stacked Residual PINNs for Hyperbolic PDE State Reconstruction
by: Eshkofti, Katayoun, et al.
Published: (2026)

Improving Performance of Spike-based Deep Q-Learning using Ternary Neurons
by: Ghoreishee, Aref, et al.
Published: (2025)

Learning the optimal state-feedback via supervised imitation learning
by: Tailor, Dharmesh, et al.
Published: (2019)

Improving Low-Fidelity Models of Li-ion Batteries via Hybrid Sparse Identification of Nonlinear Dynamics
by: da Silva, Samuel Filgueira, et al.
Published: (2024)

Engineering Hybrid Physics-Informed Neural Networks for Next-Generation Electricity Systems: A State-of-the-Art Review
by: Nyangon, Joseph
Published: (2026)

A Cloud-Edge Framework for Energy-Efficient Event-Driven Control: An Integration of Online Supervised Learning, Spiking Neural Networks and Local Plasticity Rules
by: Ahmadvand, Reza, et al.
Published: (2024)

Neural Control System for Continuous Glucose Monitoring and Maintenance
by: Wasi, Azmine Toushik
Published: (2024)

Optimality Principles and Neural Ordinary Differential Equations-based Process Modeling for Distributed Control
by: Wartmann, Michael R., et al.
Published: (2025)

An Efficient General-Purpose Optical Accelerator for Neural Networks
by: Fei, Sijie, et al.
Published: (2024)

A Pipelined Memristive Neural Network Analog-to-Digital Converter
by: Danial, Loai, et al.
Published: (2024)

Adaptive Control in Autonomous Driving via Real-Time Recurrent RL
by: Lemmel, Julian, et al.
Published: (2026)

Personalized Spiking Neural Networks with Ferroelectric Synapses for EEG Signal Processing
by: Garg, Nikhil, et al.
Published: (2025)

Computationally Efficient Optimisation of Elbow-Type Draft Tube Using Neural Network Surrogates
by: Sikirica, Ante, et al.
Published: (2024)

A Globally Convergent Algorithm for Neural Network Parameter Optimization Based on Difference-of-Convex Functions
by: Tschernutter, Daniel, et al.
Published: (2024)

Improving the Performance of Echo State Networks Through State Feedback
by: Ehlers, Peter J., et al.
Published: (2023)

Understand the Effectiveness of Shortcuts through the Lens of DCA
by: Sun, Youran, et al.
Published: (2024)

Spiking Neural Networks as a Controller for Emergent Swarm Agents
by: Zhu, Kevin, et al.
Published: (2024)

Controlling Chaotic Maps using Next-Generation Reservoir Computing
by: Kent, Robert M., et al.
Published: (2023)

Guidance Design for Escape Flight Vehicle Using Evolution Strategy Enhanced Deep Reinforcement Learning
by: Hu, Xiao, et al.
Published: (2024)

Combining Large Language Models and Gradient-Free Optimization for Automatic Control Policy Synthesis
by: Bosio, Carlo, et al.
Published: (2025)

Real-world validation of safe reinforcement learning, model predictive control and decision tree-based home energy management systems
by: Ruddick, Julian, et al.
Published: (2024)

Design and Implementation of Hardware Accelerators for Neural Processing Applications
by: Mayannavar, Shilpa, et al.
Published: (2024)

Effective Regularization Through Loss-Function Metalearning
by: Gonzalez, Santiago, et al.
Published: (2020)

Context-Based Echo State Networks with Prediction Confidence for Human-Robot Shared Control
by: Amirshirzad, Negin, et al.
Published: (2024)

Geometry-induced Regularization in Deep ReLU Neural Networks
by: Bona-Pellissier, Joachim, et al.
Published: (2024)

Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization
by: Luo, Fu, et al.
Published: (2023)

Sleep-Based Homeostatic Regularization for Stabilizing Spike-Timing-Dependent Plasticity in Recurrent Spiking Neural Networks
by: Massey, Andreas, et al.
Published: (2026)

Noise-Aware Bayesian Optimization Approach for Capacity Planning of the Distributed Energy Resources in an Active Distribution Network
by: Yang, Ruizhe, et al.
Published: (2024)

Embodied Neurocomputation: A Framework for Interfacing Biological Neural Cultures with Scaled Task-Driven Validation
by: Zhou, Johnson, et al.
Published: (2026)

Limiting Network Size within Finite Bounds for Optimization
by: Pinto, Linu, et al.
Published: (2019)

Digital Twin-Driven Pavement Health Monitoring and Maintenance Optimization Using Graph Neural Networks
by: Topu, Mohsin Mahmud, et al.
Published: (2025)

Stochastic Reservoir Computers
by: Ehlers, Peter J., et al.
Published: (2024)