Pages that link to "Item:Q462325"
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The following pages link to Kernel methods in system identification, machine learning and function estimation: a survey (Q462325):
Displaying 50 items.
- Data-driven switching modeling for MPC using regression trees and random forests (Q2178240) (← links)
- High precision variational Bayesian inference of sparse linear networks (Q2188259) (← links)
- Efficient spatio-temporal Gaussian regression via Kalman filtering (Q2188275) (← links)
- On the mathematical foundations of stable RKHSs (Q2188280) (← links)
- Recursive estimation for sparse Gaussian process regression (Q2203074) (← links)
- Nonlinear system identification for multivariable control via discrete-time Chen-Fliess series (Q2207213) (← links)
- Facing undermodelling in sign-perturbed-sums system identification (Q2242890) (← links)
- Bayesian positive system identification: truncated Gaussian prior and hyperparameter estimation (Q2242966) (← links)
- Gaussian process regression for the estimation of generalized frequency response functions (Q2280760) (← links)
- On convexification of system identification criteria (Q2289048) (← links)
- Control-based algorithms for high dimensional online learning (Q2297419) (← links)
- Sparse RKHS estimation via globally convex optimization and its application in LPV-IO identification (Q2307599) (← links)
- Distribution-free uncertainty quantification for kernel methods by gradient perturbations (Q2320596) (← links)
- Nonlinear system identification via data augmentation (Q2327384) (← links)
- Leading impulse response identification via the elastic net criterion (Q2407167) (← links)
- Regularized nonparametric Volterra kernel estimation (Q2409165) (← links)
- Maximum entropy vector kernels for MIMO system identification (Q2409365) (← links)
- System models or learning machines? (Q2518629) (← links)
- Kernel methods for subspace identification of multivariable LPV and bilinear systems (Q2576109) (← links)
- Control-oriented regularization for linear system identification (Q2664260) (← links)
- MIMO ILC using complex-kernel regression and application to precision SEA robots (Q2664276) (← links)
- Learning linear modules in a dynamic network using regularized kernel-based methods (Q2665089) (← links)
- Learning nonlinear state-space models using autoencoders (Q2665158) (← links)
- Kernel-based methods for Volterra series identification (Q2665176) (← links)
- On semiseparable kernels and efficient implementation for regularized system identification and function estimation (Q2665635) (← links)
- Deterministic error bounds for kernel-based learning techniques under bounded noise (Q2665700) (← links)
- The existence and uniqueness of solutions for kernel-based system identification (Q2682286) (← links)
- Learning dynamical systems using local stability priors (Q2696118) (← links)
- Kernel-based methods for parameter estimation in multidimensional systems (Q2851166) (← links)
- Kernel Absolute Summability Is Sufficient but Not Necessary for RKHS Stability (Q3300839) (← links)
- Kernels for Linear Time Invariant System Identification (Q3451766) (← links)
- Generalized System Identification with Stable Spline Kernels (Q4553782) (← links)
- Model selection for dynamical systems via sparse regression and information criteria (Q4644829) (← links)
- Linearly Constrained Linear Quadratic Regulator from the Viewpoint of Kernel Methods (Q5009773) (← links)
- Identification of flame transfer functions in the presence of intrinsic thermoacoustic feedback and noise (Q5032152) (← links)
- On the almost sure central limit theorem for ARX processes in adaptive tracking (Q5128869) (← links)
- Two-phase selective decentralization to improve reinforcement learning systems with MDP (Q5145441) (← links)
- A shift in paradigm for system identification (Q5216416) (← links)
- Sparse identification of nonlinear dynamics for model predictive control in the low-data limit (Q5243602) (← links)
- A Scaled Gradient Projection Method for Bayesian Learning in Dynamical Systems (Q5254793) (← links)
- Maximum Entropy Kernels for System Identification (Q5282397) (← links)
- Non-Linear Interactions and Exchange Rate Prediction: Empirical Evidence Using Support Vector Regression (Q5378531) (← links)
- Recovery of Surfaces and Functions in High Dimensions: Sampling Theory and Links to Neural Networks (Q5860295) (← links)
- Kernel-based identification of asymptotically stable continuous-time linear dynamical systems (Q5863750) (← links)
- Kernel-Based Models for System Analysis (Q6047030) (← links)
- Nonlinear system identification in Sobolev spaces (Q6106395) (← links)
- A regularised fast recursive algorithm for fraction model identification of nonlinear dynamic systems (Q6109495) (← links)
- On the regularization and optimization in quantum detector tomography (Q6110007) (← links)
- Stable spline identification of linear systems under missing data (Q6119719) (← links)
- When cannot regularization improve the least squares estimate in the kernel-based regularized system identification (Q6152563) (← links)
