Copertina

Implementing Online Reinforcement Learning with Clustering Neural Networks

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Smith, James E.
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Neural and Evolutionary Computing 68T07 I.2
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Neuromorphic Online Clustering and Its Application to Spike Sorting
di: Smith, James E.
Pubblicazione: (2025)

Game-Theoretic Gradient Control for Robust Neural Network Training
di: Zaitseva, Maria, et al.
Pubblicazione: (2025)

Fractional Artificial Neural Networks for Growth Models
di: Najera-Tinoco, Juan Carlos, et al.
Pubblicazione: (2025)

Rapid training of Hamiltonian graph networks using random features
di: Rahma, Atamert, et al.
Pubblicazione: (2025)

Towards Understanding the Link Between Modularity and Performance in Neural Networks for Reinforcement Learning
di: Munn, Humphrey, et al.
Pubblicazione: (2022)

AiGAS-dEVL-RC: An Adaptive Growing Neural Gas Model for Recurrently Drifting Unsupervised Data Streams
di: Arostegi, Maria, et al.
Pubblicazione: (2025)

Alternate Loss Functions for Classification and Robust Regression Can Improve the Accuracy of Artificial Neural Networks
di: Noel, Mathew Mithra, et al.
Pubblicazione: (2023)

EvoPruneDeepTL: An Evolutionary Pruning Model for Transfer Learning based Deep Neural Networks
di: Poyatos, Javier, et al.
Pubblicazione: (2022)

The Deep Arbitrary Polynomial Chaos Neural Network or how Deep Artificial Neural Networks could benefit from Data-Driven Homogeneous Chaos Theory
di: Oladyshkin, Sergey, et al.
Pubblicazione: (2023)

On the Convergence and Stability of Upside-Down Reinforcement Learning, Goal-Conditioned Supervised Learning, and Online Decision Transformers
di: Štrupl, Miroslav, et al.
Pubblicazione: (2025)

ElegansNet: a brief scientific report and initial experiments
di: Bardozzo, Francesco, et al.
Pubblicazione: (2023)

Pointer Networks Trained Better via Evolutionary Algorithms
di: Zhong, Muyao, et al.
Pubblicazione: (2023)

Learning Morphisms with Gauss-Newton Approximation for Growing Networks
di: Lawton, Neal, et al.
Pubblicazione: (2024)

Task-Synchronized Recurrent Neural Networks
di: Lukoševičius, Mantas, et al.
Pubblicazione: (2022)

Pulse-Driven Neural Architecture: Learnable Oscillatory Dynamics for Robust Continuous-Time Sequence Processing
di: Sharma, Paras
Pubblicazione: (2026)

Combining AI Control Systems and Human Decision Support via Robustness and Criticality
di: Woods, Walt, et al.
Pubblicazione: (2024)

Adjusting Dynamics of Hopfield Neural Network via Time-variant Stimulus
di: Peng, Xuenan, et al.
Pubblicazione: (2024)

Reconstructing shared dynamics with a deep neural network
di: Benkő, Zsigmond, et al.
Pubblicazione: (2021)

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

Perforated Neural Networks for Keyword Spotting
di: Gopal, Vishy, et al.
Pubblicazione: (2026)

Loss shaping enhances exact gradient learning with Eventprop in spiking neural networks
di: Nowotny, Thomas, et al.
Pubblicazione: (2022)

Efficient Vectorized Backpropagation Algorithms for Training Feedforward Networks Composed of Quadratic Neurons
di: Noel, Mathew Mithra, et al.
Pubblicazione: (2023)

mlx-snn: Spiking Neural Networks on Apple Silicon via MLX
di: Qin, Jiahao
Pubblicazione: (2026)

Reservoir Computing with Evolved Critical Neural Cellular Automata
di: Pontes-Filho, Sidney, et al.
Pubblicazione: (2025)

Distal Interference: Exploring the Limits of Model-Based Continual Learning
di: van Deventer, Heinrich, et al.
Pubblicazione: (2024)

Composition of Relational Features with an Application to Explaining Black-Box Predictors
di: Srinivasan, Ashwin, et al.
Pubblicazione: (2022)

SCAPE: Searching Conceptual Architecture Prompts using Evolution
di: Lim, Soo Ling, et al.
Pubblicazione: (2024)

Algorithmic Analysis of Dense Associative Memory: Finite-Size Guarantees and Adversarial Robustness
di: Gaikwad, Madhava
Pubblicazione: (2026)

Modeling Local Search Metaheuristics Using Markov Decision Processes
di: Ruiz-Torrubiano, Rubén
Pubblicazione: (2024)

Physics-Driven AI Correction in Laser Absorption Sensing Quantification
di: Kang, Ruiyuan, et al.
Pubblicazione: (2024)

P1-KAN: an effective Kolmogorov-Arnold network with application to hydraulic valley optimization
di: Warin, Xavier
Pubblicazione: (2024)

One-Spike SNN: Single-Spike Phase Coding with Base Manipulation for ANN-to-SNN Conversion Loss Minimization
di: Hwang, Sangwoo, et al.
Pubblicazione: (2024)

A parametric activation function based on Wendland RBF
di: Darehmiraki, Majid
Pubblicazione: (2025)

The Coordinate System Problem in Persistent Structural Memory for Neural Architectures
di: Basu, Abhinaba
Pubblicazione: (2026)

Learning Neuron Dynamics within Deep Spiking Neural Networks
di: Jahns, Eric, et al.
Pubblicazione: (2025)

Energy-Efficient Neuromorphic Computing for Edge AI: A Framework with Adaptive Spiking Neural Networks and Hardware-Aware Optimization
di: Imanov, Olaf Yunus Laitinen, et al.
Pubblicazione: (2026)

Neural Networks Trained by Weight Permutation are Universal Approximators
di: Cai, Yongqiang, et al.
Pubblicazione: (2024)

Collocation-based Robust Physics Informed Neural Networks for time-dependent simulations of pollution propagation under thermal inversion conditions on Spitsbergen
di: Siwik, Leszek, et al.
Pubblicazione: (2026)

Model Input-Output Configuration Search with Embedded Feature Selection for Sensor Time-series and Image Classification
di: Hoang, Anh T., et al.
Pubblicazione: (2023)

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