Imagen de Portada

Restrictions on Physical Stochastic Reservoir Computers

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Polloreno, Anthony M.
Formato:	Preprint
Publicado:	2023
Materias:	Machine Learning Information Theory
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Innovation Capacity of Dynamical Learning Systems
por: Polloreno, Anthony M.
Publicado: (2026)

Geometry, Computation, and Optimality in Stochastic Optimization
por: Cheng, Chen, et al.
Publicado: (2019)

Online Prediction of Stochastic Sequences with High Probability Regret Bounds
por: Frey, Matthias, et al.
Publicado: (2026)

Generalized Lagrange Coded Computing: A Flexible Computation-Communication Tradeoff for Resilient, Secure, and Private Computation
por: Zhu, Jinbao, et al.
Publicado: (2022)

Tighter CMI-Based Generalization Bounds via Stochastic Projection and Quantization
por: Sefidgaran, Milad, et al.
Publicado: (2025)

Characterizing the Accuracy-Communication-Privacy Trade-off in Distributed Stochastic Convex Optimization
por: Salgia, Sudeep, et al.
Publicado: (2025)

An Information-Theoretic Framework for Out-of-Distribution Generalization with Applications to Stochastic Gradient Langevin Dynamics
por: Liu, Wenliang, et al.
Publicado: (2024)

Separable Computation of Information Measures
por: Xu, Xiangxiang, et al.
Publicado: (2025)

A Novel Deep Reinforcement Learning Method for Computation Offloading in Multi-User Mobile Edge Computing with Decentralization
por: Long, Nguyen Chi, et al.
Publicado: (2025)

Integrated Sensing, Communication, and Computation for Over-the-Air Federated Edge Learning
por: Wen, Dingzhu, et al.
Publicado: (2025)

Maximizing the Promptness of Metaverse Systems using Edge Computing by Deep Reinforcement Learning
por: Thi-Thanh, Tam Ninh, et al.
Publicado: (2025)

Computation-aware Energy-harvesting Federated Learning: Cyclic Scheduling with Selective Participation
por: Jeong, Eunjeong, et al.
Publicado: (2025)

ZENN: A Thermodynamics-Inspired Computational Framework for Heterogeneous Data-Driven Modeling
por: Wang, Shun, et al.
Publicado: (2025)

Robust Communication and Computation using Deep Learning via Joint Uncertainty Injection
por: Reifert, Robert-Jeron, et al.
Publicado: (2024)

Cost Minimization for Space-Air-Ground Integrated Multi-Access Edge Computing Systems
por: Qin, Weihong, et al.
Publicado: (2025)

Agentic AI-Based Joint Computing and Networking via Mixture of Experts and Large Language Models
por: Reifert, Robert-Jeron, et al.
Publicado: (2026)

Statistical-Computational Trade-offs in Tensor PCA and Related Problems via Communication Complexity
por: Dudeja, Rishabh, et al.
Publicado: (2022)

Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization
por: Shen, Wei, et al.
Publicado: (2023)

Unifying Summary Statistic Selection for Approximate Bayesian Computation
por: Hoffmann, Till, et al.
Publicado: (2022)

Community Detection in the Multi-View Stochastic Block Model
por: Zhang, Yexin, et al.
Publicado: (2024)

Model-free Reinforcement Learning of Semantic Communication by Stochastic Policy Gradient
por: Beck, Edgar, et al.
Publicado: (2023)

MESSY Estimation: Maximum-Entropy based Stochastic and Symbolic densitY Estimation
por: Tohme, Tony, et al.
Publicado: (2023)

On the Price of Differential Privacy for Spectral Clustering over Stochastic Block Models
por: Koskela, Antti, et al.
Publicado: (2025)

Stochastic Zeroth-Order Optimization under Strongly Convexity and Lipschitz Hessian: Minimax Sample Complexity
por: Yu, Qian, et al.
Publicado: (2024)

Computationally efficient reductions between some statistical models
por: Lou, Mengqi, et al.
Publicado: (2024)

Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application
por: Wang, Xiucheng, et al.
Publicado: (2025)

Integrated Sensing-Communication-Computation for Edge Artificial Intelligence
por: Wen, Dingzhu, et al.
Publicado: (2023)

On the Computational Entanglement of Distant Features in Adversarial Machine Learning
por: Lai, YenLung, et al.
Publicado: (2023)

Fast Mutual Information Computation for Large Binary Datasets
por: Falcao, Andre O.
Publicado: (2024)

Coding for Computation: Efficient Compression of Neural Networks for Reconfigurable Hardware
por: Rosenberger, Hans, et al.
Publicado: (2025)

The Generalization Error of Supervised Machine Learning Algorithms
por: Perlaza, Samir M., et al.
Publicado: (2024)

Optimal Information Combining for Multi-Agent Systems Using Adaptive Bias Learning
por: Alamouti, Siavash M., et al.
Publicado: (2025)

Spectral Clustering for Directed Graphs via Likelihood Estimation on Stochastic Block Models
por: Zhang, Ning, et al.
Publicado: (2024)

DRACO: Decentralized Asynchronous Federated Learning over Row-Stochastic Wireless Networks
por: Jeong, Eunjeong, et al.
Publicado: (2024)

Statistical-Geometric Degeneracy in UAV Search: A Physics-Aware Asymmetric Filtering Approach
por: Ren, Zhiyuan, et al.
Publicado: (2026)

A unified framework for learning with nonlinear model classes from arbitrary linear samples
por: Adcock, Ben, et al.
Publicado: (2023)

A Convergence Analysis of Approximate Message Passing with Non-Separable Functions and Applications to Multi-Class Classification
por: Çakmak, Burak, et al.
Publicado: (2024)

Asymptotic Behavior of Multi--Task Learning: Implicit Regularization and Double Descent Effects
por: Alrashdi, Ayed M., et al.
Publicado: (2026)

Decentralized Machine Learning with Centralized Performance Guarantees via Gibbs Algorithms
por: Bermudez, Yaiza, et al.
Publicado: (2026)

Minimum Entropy Coupling with Bottleneck
por: Ebrahimi, M. Reza, et al.
Publicado: (2024)