Results 91 to 100 of about 478,588 (342)
Dimensionality Reduction for Handwritten Digit Recognition [PDF]
Human perception of dimensions is usually limited to two or three degrees. Any further increase in the number of dimensions usually leads to the difficulty in visual imagination for any person.
Ankita Das+2 more
doaj +1 more source
Foundations of Coupled Nonlinear Dimensionality Reduction
In this paper we introduce and analyze the learning scenario of \emph{coupled nonlinear dimensionality reduction}, which combines two major steps of machine learning pipeline: projection onto a manifold and subsequent supervised learning. First, we present new generalization bounds for this scenario and, second, we introduce an algorithm that follows ...
Mohri, Mehryar+2 more
openaire +2 more sources
Elasticity of Diametrically Compressed Microfabricated Woodpile Lattices
Modulus–porosity relationship is derived for woodpile lattices with struts under diametrical compression. The formula presented here that Young's modulus is proportional to the square of the volume fraction E˜ρ2$E \sim \left(\rho\right)^{2}$ is shown to be consistent with computations and laboratory experiments on 3D‐printed samples.
Faezeh Shalchy, Atul Bhaskar
wiley +1 more source
Conditional Symmetry and Reductions for the Two-Dimensional Nonlinear Wave Equation. I. General Case [PDF]
We present classification of Q-conditional symmetries for the two-dimensional nonlinear wave equations and the reductions corresponding to these nonlinear symmetries. Classification of inequivalent reductions is discussed.
arxiv
Survey: Geometric Foundations of Data Reduction [PDF]
This survey is written in summer, 2016. The purpose of this survey is to briefly introduce nonlinear dimensionality reduction (NLDR) in data reduction. The first two NLDR were respectively published in Science in 2000 in which they solve the similar reduction problem of high-dimensional data endowed with the intrinsic nonlinear structure. The intrinsic
arxiv
A Novel Digitalization Approach for Smart Materials – Ontology‐Based Access to Data and Models
In order to access heterogeneous material data and model‐based knowledge, the established ontology‐based data access (OBDA) is extended to include material models. This novel ontology‐based data and model access (OBDMA) enables the computation of new responses beyond stored data.
Jürgen Maas+15 more
wiley +1 more source
Forward-backward equations for nonlinear propagation in axially-invariant optical systems
We present a novel general framework to deal with forward and backward components of the electromagnetic field in axially-invariant nonlinear optical systems, which include those having any type of linear or nonlinear transverse inhomogeneities.
A. Ferrando+7 more
core +1 more source
AISI 304L stainless steel powder is mixed with silicon nitride (Si3N4) powder and processed by PBF‐LB/M, allowing partial retention of Si3N4. The numerical approach effectively predicts the Si3N4 powder homogeneity and N content distribution on the powder bed. Recent studies have focused on the alloying of nitrogen (N) in high‐alloy stainless steels by
Yuanbin Deng+7 more
wiley +1 more source
Kinodynamic FMT* with Dimensionality Reduction Heuristics and Neural Network Controllers [PDF]
This paper proposes a new sampling-based kinodynamic motion planning algorithm, called FMT*PFF, for nonlinear systems. It exploits the novel idea of dimensionality reduction using partial-final-state-free (PFF) optimal controllers.With the proposed dimensionality reduction heuristic, the search space is restricted within a subspace, thus faster ...
arxiv
To improve smoke detection accuracy, we combine local binary pattern (LBP) like features, kernel principal component analysis (KPCA), and Gaussian process regression (GPR) to propose a novel data processing pipeline for smoke detection.
Feiniu Yuan+4 more
doaj +1 more source