Results 121 to 130 of about 3,554 (301)

Multiple Kernel Spectral Regression for Dimensionality Reduction

Journal of Applied Mathematics, 2013
Traditional manifold learning algorithms, such as locally linear embedding, Isomap, and Laplacian eigenmap, only provide the embedding results of the training samples.
Bing Liu, Shixiong Xia, Yong Zhou
doaj   +1 more source

Privacy-Preserving Classification of Vertically Partitioned Data via Random Kernels

, 2007
We propose a novel privacy-preserving support vector machine (SVM) classifier for a data matrix A whose input feature columns are divided into groups belonging to different entities.
Mangasarian, Olvi, Fung, Glenn, Wild, Edward   +2 more
core  

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Multi‐Omics Insights Into the Mechanisms of Early Muscle Fiber Difference and Transformation Between Lean‐Type and Chinese Indigenous Pigs

Advanced Science, EarlyView.
Multi‐omics analyses uncover breed‐specific cis‐regulatory landscapes and higher‐order chromatin architectural differences that underlie early postnatal muscle fiber divergence in pigs. A super‐enhancer upstream of PPP3CB recruits MEF2C to activate PPP3CB transcription, while the PPP3CB–MEF2C positive feedback loop promotes oxidative muscle fiber ...
Shuailong Zheng, Hainan Wu, Min Liu, Kunpeng Wu, Shuntao Huang, Zulfiqar Ahmed, Lenox Pius, Mengjin Zhu, Dequan Xu   +8 more
wiley   +1 more source

Geometry of reproducing kernels in model spaces near the boundary

, 2017
International audienceWe study two geometric properties of reproducing kernels in model spaces $K_\theta$ where $\theta$ is an inner function in the disc: overcompleteness and existence of uniformly minimal systems of reproducing kernels which do not ...
Kellay, Karim, Baranov, Anton, Hartmann, Andreas   +2 more
core   +1 more source

Inequalities for differentiable reproducing kernels and an application to positive integral operators

Journal of Inequalities and Applications, 2006
Let be an interval and let be a reproducing kernel on . We show that if is in the appropriate differentiability class, it satisfies a 2-parameter family of inequalities of which the diagonal dominance inequality for reproducing kernels is the 0th ...
Paixão AC, Buescu Jorge
doaj  

Tight frame expansions of multiscale reproducing kernels in Sobolev spaces

, 2005
Multiscale kernels are a new type of positive definite reproducing kernels in Hilbert spaces. They are constructed by a superposition of shifts and scales of a single refinable function and were introduced in the paper of R.
Opfer, R., Roland Opfer, Opfer, Roland
core   +1 more source

INB3P: A Multi‐Modal and Interpretable Co‐Attention Framework Integrating Property‐Aware Explanations and Memory‐Bank Contrastive Fusion for Blood–Brain Barrier Penetrating Peptide Discovery

Advanced Science, EarlyView.
INB3P is a multimodal framework for blood–brain barrier‐penetrating peptide prediction under extreme data scarcity and class imbalance. By combining physicochemical‐guided augmentation, sequence–structure co‐attention, and imbalance‐aware optimization, it improves predictive performance and interpretability.
Jingwei Lv, Qianyang Wu, Jian Liu, Binlu Yang, Yuanhao Li, Junlin Xu, Yajie Meng, Leyi Wei, Zilong Zhang, Quan Zou, Xiulai Li, Feifei Cui   +11 more
wiley   +1 more source

New Inequalities and an Integral Expression for the 𝒜-Berezin Number

Journal of Mathematics
This work examines a reproducing kernel Hilbert space XF,·,· constructed on a nonempty set F. Our investigation focuses on the A-Berezin number and the A-Berezin norm, where A denotes a positive bounded linear operator acting on XF.
Salma Aljawi, Ahad Alotaibi, Cristian Conde, Kais Feki   +3 more
doaj   +1 more source

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

Advanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu, Longfei Lv, Fan Zhang, Si Zhou, Weiwei Gao, Jijun Zhao   +5 more
wiley   +1 more source