A Machine Learning Framework for Weighted Least Squares GNSS Positioning based on Activation Functions
Fuente:
arXiv
Guardado en:
| Autores principales: | Lee, Pin-Hsun, Leib, Harry |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
DRL-Based Beam Positioning for LEO Satellite Constellations with Weighted Least Squares
por: Chou, Po-Heng, et al.
Publicado: (2025)
por: Chou, Po-Heng, et al.
Publicado: (2025)
Partitioned Least Squares
por: Esposito, Roberto, et al.
Publicado: (2020)
por: Esposito, Roberto, et al.
Publicado: (2020)
Importance Weighting Correction of Regularized Least-Squares for Target Shift
por: Gogolashvili, Davit
Publicado: (2022)
por: Gogolashvili, Davit
Publicado: (2022)
KernelSHAP-IQ: Weighted Least-Square Optimization for Shapley Interactions
por: Fumagalli, Fabian, et al.
Publicado: (2024)
por: Fumagalli, Fabian, et al.
Publicado: (2024)
Transformers Don't In-Context Learn Least Squares Regression
por: Hill, Joshua, et al.
Publicado: (2025)
por: Hill, Joshua, et al.
Publicado: (2025)
Kernel Recursive Least Squares Dictionary Learning Algorithm
por: Alipoor, Ghasem, et al.
Publicado: (2025)
por: Alipoor, Ghasem, et al.
Publicado: (2025)
PLeaS -- Merging Models with Permutations and Least Squares
por: Nasery, Anshul, et al.
Publicado: (2024)
por: Nasery, Anshul, et al.
Publicado: (2024)
Outlier-robust Autocovariance Least Square Estimation via Iteratively Reweighted Least Square
por: Li, Jiahong, et al.
Publicado: (2026)
por: Li, Jiahong, et al.
Publicado: (2026)
AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models
por: Kveton, Branislav, et al.
Publicado: (2026)
por: Kveton, Branislav, et al.
Publicado: (2026)
A Hybrid Federated Kernel Regularized Least Squares Algorithm
por: Damiani, Celeste, et al.
Publicado: (2024)
por: Damiani, Celeste, et al.
Publicado: (2024)
Robust PCA Based on Adaptive Weighted Least Squares and Low-Rank Matrix Factorization
por: Li, Kexin, et al.
Publicado: (2024)
por: Li, Kexin, et al.
Publicado: (2024)
On Least Square Estimation in Softmax Gating Mixture of Experts
por: Nguyen, Huy, et al.
Publicado: (2024)
por: Nguyen, Huy, et al.
Publicado: (2024)
Communication-Efficient l_0 Penalized Least Square
por: Gong, Chenqi, et al.
Publicado: (2025)
por: Gong, Chenqi, et al.
Publicado: (2025)
Online Multi-Task Learning with Recursive Least Squares and Recursive Kernel Methods
por: Lencione, Gabriel R., et al.
Publicado: (2023)
por: Lencione, Gabriel R., et al.
Publicado: (2023)
Ordinary Least Squares as an Attention Mechanism
por: Coulombe, Philippe Goulet
Publicado: (2025)
por: Coulombe, Philippe Goulet
Publicado: (2025)
Core-elements Subsampling for Alternating Least Squares
por: Xue, Dunyao, et al.
Publicado: (2025)
por: Xue, Dunyao, et al.
Publicado: (2025)
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning
por: Di, Qiwei, et al.
Publicado: (2023)
por: Di, Qiwei, et al.
Publicado: (2023)
Towards Learning High-Precision Least Squares Algorithms with Sequence Models
por: Liu, Jerry, et al.
Publicado: (2025)
por: Liu, Jerry, et al.
Publicado: (2025)
Improving Implicit Regularization of SGD with Preconditioning for Least Square Problems
por: Su, Junwei, et al.
Publicado: (2024)
por: Su, Junwei, et al.
Publicado: (2024)
$(ε, δ)$-Differentially Private Partial Least Squares Regression
por: Nikzad-Langerodi, Ramin, et al.
Publicado: (2024)
por: Nikzad-Langerodi, Ramin, et al.
Publicado: (2024)
Generalization for Least Squares Regression With Simple Spiked Covariances
por: Li, Jiping, et al.
Publicado: (2024)
por: Li, Jiping, et al.
Publicado: (2024)
Convex Regression in Multidimensions: Suboptimality of Least Squares Estimators
por: Kur, Gil, et al.
Publicado: (2020)
por: Kur, Gil, et al.
Publicado: (2020)
APFL: Analytic Personalized Federated Learning via Dual-Stream Least Squares
por: Fan, Kejia, et al.
Publicado: (2025)
por: Fan, Kejia, et al.
Publicado: (2025)
Concurrent Learning with Aggregated States via Randomized Least Squares Value Iteration
por: Chen, Yan, et al.
Publicado: (2025)
por: Chen, Yan, et al.
Publicado: (2025)
A Representer Theorem for Hawkes Processes via Penalized Least Squares Minimization
por: Kim, Hideaki, et al.
Publicado: (2025)
por: Kim, Hideaki, et al.
Publicado: (2025)
Functional Partial Least-Squares: Adaptive Estimation and Inference
por: Babii, Andrii, et al.
Publicado: (2024)
por: Babii, Andrii, et al.
Publicado: (2024)
Randomized Least Squares Value Iteration itself is Joint Differentially Private
por: Lu, Haiyang, et al.
Publicado: (2026)
por: Lu, Haiyang, et al.
Publicado: (2026)
High-Dimensional Partial Least Squares: Spectral Analysis and Fundamental Limitations
por: Léger, Victor, et al.
Publicado: (2025)
por: Léger, Victor, et al.
Publicado: (2025)
Generalized Least Squares Kernelized Tensor Factorization
por: Lei, Mengying, et al.
Publicado: (2024)
por: Lei, Mengying, et al.
Publicado: (2024)
Algebraic and Statistical Properties of the Ordinary Least Squares Interpolator
por: Shen, Dennis, et al.
Publicado: (2023)
por: Shen, Dennis, et al.
Publicado: (2023)
Shape Constraints in Symbolic Regression using Penalized Least Squares
por: Martinek, Viktor, et al.
Publicado: (2024)
por: Martinek, Viktor, et al.
Publicado: (2024)
Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares
por: Brown, Gavin, et al.
Publicado: (2024)
por: Brown, Gavin, et al.
Publicado: (2024)
Tensor-Based Foundations of Ordinary Least Squares and Neural Network Regression Models
por: Algarte, Roberto Dias
Publicado: (2024)
por: Algarte, Roberto Dias
Publicado: (2024)
Enhancing Robustness and Efficiency of Least Square Twin SVM via Granular Computing
por: Tanveer, M., et al.
Publicado: (2024)
por: Tanveer, M., et al.
Publicado: (2024)
Least Squares Training of Quadratic Convolutional Neural Networks with Applications to System Theory
por: Van Egmond, Zachary Yetman, et al.
Publicado: (2024)
por: Van Egmond, Zachary Yetman, et al.
Publicado: (2024)
Stochastic Differential Equations models for Least-Squares Stochastic Gradient Descent
por: Schertzer, Adrien, et al.
Publicado: (2024)
por: Schertzer, Adrien, et al.
Publicado: (2024)
Ordinary Least Squares is a Special Case of Transformer
por: Tan, Xiaojun, et al.
Publicado: (2026)
por: Tan, Xiaojun, et al.
Publicado: (2026)
On Regularization via Early Stopping for Least Squares Regression
por: Sonthalia, Rishi, et al.
Publicado: (2024)
por: Sonthalia, Rishi, et al.
Publicado: (2024)
$\ell_1$-Regularized Generalized Least Squares
por: Nobari, Kaveh S., et al.
Publicado: (2024)
por: Nobari, Kaveh S., et al.
Publicado: (2024)
ORFit: One-Pass Learning via Bridging Orthogonal Gradient Descent and Recursive Least-Squares
por: Min, Youngjae, et al.
Publicado: (2022)
por: Min, Youngjae, et al.
Publicado: (2022)
Ejemplares similares
-
DRL-Based Beam Positioning for LEO Satellite Constellations with Weighted Least Squares
por: Chou, Po-Heng, et al.
Publicado: (2025) -
Partitioned Least Squares
por: Esposito, Roberto, et al.
Publicado: (2020) -
Importance Weighting Correction of Regularized Least-Squares for Target Shift
por: Gogolashvili, Davit
Publicado: (2022) -
KernelSHAP-IQ: Weighted Least-Square Optimization for Shapley Interactions
por: Fumagalli, Fabian, et al.
Publicado: (2024) -
Transformers Don't In-Context Learn Least Squares Regression
por: Hill, Joshua, et al.
Publicado: (2025)