Results 51 to 60 of about 848,965 (236)
Interpreting uninterpretable predictors: kernel methods, Shtarkov solutions, and random forests
Statistical Theory and Related Fields, 2022 Many of the best predictors for complex problems are typically regarded as hard to interpret physically. These include kernel methods, Shtarkov solutions, and random forests.
T. M. Le, Bertrand Clarke
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A One-Sample Test for Normality with Kernel Methods [PDF]
, 2015 We propose a new one-sample test for normality in a Reproducing Kernel Hilbert Space (RKHS). Namely, we test the null-hypothesis of belonging to a given family of Gaussian distributions.
Celisse, Alain, Kellner, Jérémie
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Harnessing Fungal Biowelding for Constructing Mycelium‐Engineered Materials
Advanced Engineering Materials, EarlyView.Mycelium‐bound composites (MBCs) offer low‐carbon alternatives for construction, yet interfacial bonding remains a critical challenge. This review examines fungal biowelding as a biocompatible adhesive, elucidating mycelium‐mediated interfacial mechanisms and their role in material assembly. Strategies to optimize biowelding are discussed, highlighting
Xue Brenda Bai +2 more
wiley +1 more source
A Fast Neural Network Learning Algorithm with Approximate Singular Value Decomposition
International Journal of Applied Mathematics and Computer Science, 2019 The learning of neural networks is becoming more and more important. Researchers have constructed dozens of learning algorithms, but it is still necessary to develop faster, more flexible, or more accurate learning algorithms.
Jankowski Norbert, Linowiecki Rafał
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Supervised Kernel Principal Component Analysis by Most Expressive Feature Reordering
Journal of Telecommunications and Information Technology, 2015 The presented paper is concerned with feature space derivation through feature selection. The selection is performed on results of kernel Principal Component Analysis (kPCA) of input data samples.
Krzysztof Ślot +3 more
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, 2014 Dyadic prediction methods operate on pairs of objects (dyads), aiming to infer labels for out-of-sample dyads. We consider the full and almost full cold start problem in dyadic prediction, a setting that occurs when both objects in an out-of-sample dyad ...
A. Ben-Hur +22 more
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Advanced Engineering Materials, EarlyView.A numerical model resulting from irreversible thermodynamics for describing transport processes is introduced, focusing on thermodynamic activity gradients as the actual driving force for diffusion. Implemented in CUDA C++ and using CalPhaD methods for determining the necessary activity data, the model accurately simulates interdiffusion in aluminum ...
Ulrich Holländer +3 more
wiley +1 more source
Kernel methods for detecting coherent structures in dynamical data
, 2019 We illustrate relationships between classical kernel-based dimensionality reduction techniques and eigendecompositions of empirical estimates of reproducing kernel Hilbert space (RKHS) operators associated with dynamical systems.
Husic, Brooke E. +3 more
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Advanced Engineering Materials, EarlyView.Low‐cycle fatigue damage in Mn–Mo–Ni reactor pressure vessel steel is examined using a combined electron backscatter diffraction and positron annihilation lifetime spectroscopy approach. The study correlates texture evolution, dislocation substructure development, and vacancy‐type defect formation across uniform, necked, and fracture regions, providing
Apu Sarkar +2 more
wiley +1 more source
Approximate‐Guided Representation Learning in Vision Transformer
CAAI Transactions on Intelligence TechnologyIn recent years, the transformer model has demonstrated excellent performance in computer vision (CV) applications. The key lies in its guided representation attention mechanism, which uses dot‐product to depict complex feature relationships, and ...
Kaili Wang +4 more
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