Results 71 to 80 of about 22,203 (182)

The role of identification in data‐driven policy iteration: A system theoretic study

International Journal of Robust and Nonlinear Control, EarlyView.
Abstract The goal of this article is to study fundamental mechanisms behind so‐called indirect and direct data‐driven control for unknown systems. Specifically, we consider policy iteration applied to the linear quadratic regulator problem. Two iterative procedures, where data collected from the system are repeatedly used to compute new estimates of ...
Bowen Song, Andrea Iannelli
wiley   +1 more source

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

Responsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen, Siwei Yang, Xiangqian Cui, Ziheng Liu, Hang Wang, Yongqiang Li, Peng He, Miao Wang, Guqiao Ding   +8 more
wiley   +1 more source

Modeling the Thermal Properties of Hydrogen‐Based Direct Reduced Iron Using Computational Thermodynamics and Machine Learning

steel research international, EarlyView.
Hydrogen‐based direct reduced iron (H‐DRI) melts differently from scrap and carbon‐bearing DRI. This work combines differential scanning calorimetry experiments, FactSage thermodynamics, and simple composition‐based regression to predict solidus, liquidus, heat capacity, and enthalpy for H‐DRI.
Ankur Agnihotri, Petri Sulasalmi, Pasquale Cavaliere, Ville‐Valtteri Visuri   +3 more
wiley   +1 more source

Enhancing generalized spectral clustering with embedding Laplacian graph regularization

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang, Jian Yang, Bob Zhang, Yang Tang, Wenli Du, Bihan Wen   +5 more
wiley   +1 more source

Bayesian inference for dynamic Q matrices and attribute trajectories in hidden Markov diagnostic classification models

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Hidden Markov diagnostic classification models capture how students' cognitive attributes evolve over time. This paper introduces a Bayesian Markov chain Monte Carlo algorithm for diagnostic classification models that jointly estimates time‐varying Q matrices, latent attributes, item parameters, attribute class proportions and transition ...
Chen‐Wei Liu
wiley   +1 more source

Computing Skinning Weights via Convex Duality

Computer Graphics Forum, EarlyView.
We present an alternate optimization method to compute bounded biharmonic skinning weights. Our method relies on a dual formulation, which can be optimized with a nonnegative linear least squares setup. Abstract We study the problem of optimising for skinning weights through the lens of convex duality.
J. Solomon, O. Stein
wiley   +1 more source

Survey on differential estimators for 3d point clouds

Computer Graphics Forum, EarlyView.
Abstract Recent advancements in 3D scanning technologies, including LiDAR and photogrammetry, have enabled the precise digital replication of real‐world objects. These methods are widely used in fields such as GIS, robotics, and cultural heritage. However, the point clouds generated by such scans are often noisy and unstructured, posing challenges for ...
Léo Arnal–Anger, Thibault Lejemble, David Coeurjolly, Loïc Barthe, Nicolas Mellado   +4 more
wiley   +1 more source

Hierarchical Optimization of the As‐Rigid‐As‐Possible Energy

Computer Graphics Forum, EarlyView.
Abstract The As‐Rigid‐As‐Possible (ARAP) energy [SA07] has become a versatile ingredient in various geometry processing and machine learning methods. The classic method for its minimization is a block coordinate descent, alternating between local rotation estimation and a global linear solve, which converges slowly for large problem instances.
Hendrik Meyer, Bernd Bickel, Marc Alexa
wiley   +1 more source

A Note on Local Polynomial Regression for Time Series in Banach Spaces

Journal of Time Series Analysis, EarlyView.
ABSTRACT This work extends local polynomial regression to Banach space‐valued time series for estimating smoothly varying means and their derivatives in non‐stationary data. The asymptotic properties of both the standard and bias‐reduced Jackknife estimators are analyzed under mild moment conditions, establishing their convergence rates.
Florian Heinrichs
wiley   +1 more source

The Natural Components of a Regular Linear System

Oxford Bulletin of Economics and Statistics, EarlyView.
ABSTRACT The analysis of a finite‐dimensional regular linear system may be simplified by separating the system into its natural components. The natural components are smaller linear systems on separate subspaces whose dimensions sum to the dimension of the original linear system.
Brendan K. Beare, Phil Howlett
wiley   +1 more source