Results 51 to 60 of about 21,847 (188)

Polytopes of Minimum Positive Semidefinite Rank

, 2013
The positive semidefinite (psd) rank of a polytope is the smallest $k$ for which the cone of $k \times k$ real symmetric psd matrices admits an affine slice that projects onto the polytope.
Gouveia, João, Robinson, Richard Z., Thomas, Rekha R.   +2 more
core   +1 more source

Joint Estimation and Bandwidth Selection in Partially Parametric Models

Journal of Applied Econometrics, EarlyView.
ABSTRACT We propose a single‐step approach to estimating a model with both a known nonlinear parametric component and an unknown nonparametric component. We study the large sample behavior of a simultaneous optimization routine that estimates both the parameter vector of the parametric component and the bandwidth vector used to smooth the unknown ...
Daniel J. Henderson, Nadine McCloud, Christopher F. Parmeter   +2 more
wiley   +1 more source

Predicting Infrared Optical Properties of Materials Using Machine Learning Interatomic Potentials

Materials Genome Engineering Advances, EarlyView.
This work proposes a new fast computing framework for infrared reflectance spectra, MTP‐FIRE, based on machine learning potential, which can achieve the same accuracy as the existing first‐principles calculation, but can be two orders of magnitude faster on average.
Lianduan Zeng, Xiao Zhou, Xinxi Lu, Li Huang, Lan Yang, Lihao Wang, Gang Liu, Zhongyang Wang, Tongxiang Fan   +8 more
wiley   +1 more source

Dropping Symmetry for Fast Symmetric Nonnegative Matrix Factorization

, 2018
Accepted in NIPS ...
Zhu, Zhihui, Li, Xiao, Liu, Kai, Li, Qiuwei   +3 more
openaire   +2 more sources

Informed Dictionary‐Guided Monte Carlo Inversion for Robust and Reproducible Multidimensional MRI

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To develop a robust and efficient multidimensional MRI (MD‐MRI) data processing framework for accurately estimating joint frequency‐dependent diffusion‐relaxation distributions, while overcoming computational limitations and noise instability inherent to Monte Carlo (MC) inversion.
Joon Sik Park, Eppu Manninen, Yihong Yang, Dan Benjamini   +3 more
wiley   +1 more source

Loss Behavior in Supervised Learning With Entangled States

Advanced Quantum Technologies, EarlyView.
Entanglement in training samples supports quantum supervised learning algorithm in obtaining solutions of low generalization error. Using analytical as well as numerical methods, this work shows that the positive effect of entanglement on model after training has negative consequences for the trainability of the model itself, while showing the ...
Alexander Mandl, Johanna Barzen, Marvin Bechtold, Frank Leymann, Lavinia Stiliadou   +4 more
wiley   +1 more source

Accelerating Nonnegative Matrix Factorization Algorithms using Extrapolation

, 2018
In this paper, we propose a general framework to accelerate significantly the algorithms for nonnegative matrix factorization (NMF). This framework is inspired from the extrapolation scheme used to accelerate gradient methods in convex optimization and ...
Ang, Andersen Man Shun, Gillis, Nicolas
core   +1 more source

Data‐Based Refinement of Parametric Uncertainty Descriptions

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT We consider dynamical systems with a linear fractional representation involving parametric uncertainties which are either constant or varying with time. Given a finite‐horizon input‐state or input‐output trajectory of such a system, we propose a numerical scheme which iteratively improves the available knowledge about the involved constant ...
Tobias Holicki, Carsten W. Scherer
wiley   +1 more source

Robust Control Design and Analysis Based on Lifting Linearization of Nonlinear Systems Under Uncertain Initial Conditions

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This paper presents a robust control synthesis and analysis framework for nonlinear systems with uncertain initial conditions. First, a deep learning‐based lifting approach is proposed to approximate nonlinear dynamical systems with linear parameter‐varying (LPV) state‐space models in higher‐dimensional spaces while simultaneously ...
Sourav Sinha, Mazen Farhood
wiley   +1 more source

Output Feedback Design for Parameter Varying Systems Subject to Persistent Disturbances and Control Rate Constraints

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This paper develops a framework for designing output feedback controllers for constrained linear parameter‐varying systems that experience persistent disturbances. We specifically propose an incremental parameter‐varying output feedback control law to address control rate constraints, as well as state and control amplitude constraints.
Jackson G. Ernesto, Eugênio B. Castelan, Walter Lucia   +2 more
wiley   +1 more source