Results 61 to 70 of about 24,126 (306)
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
Advanced Science, EarlyView.This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source
Graph-Based Clustering via Group Sparsity and Manifold Regularization
IEEE Access, 2019 Clustering refers to the problem of partitioning data into several groups according to the predefined criterion. Graph-based method is one of main clustering approaches and has been shown impressive performance in many literatures.
Jianyu Miao +3 more
doaj +1 more source
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Advanced Science, EarlyView.Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source
Graph and Manifold Co-Regularization
, 2013 Classical foundations of Statistical Learning Theory rely on the assumption that the input patterns are independently and identically distributed. However, in many applications, the inputs, represented as feature vectors, are also embedded into a network
Saccà, Claudio +5 more
core +1 more source
Graph Regularized Hierarchical Diffusion Process With Relevance Feedback for Medical Image Retrieval
IEEE Access, 2021 Befitting from the interpretability and the capacity in capturing the underlying manifold structure, diffusion process (DP) has attracted increasing attention in the field of image retrieval.
Liming Xu +4 more
doaj +1 more source
The Electronic Journal of Combinatorics, 2016 This is a survey of distance-regular graphs. We present an introduction to distance-regular graphs for the reader who is unfamiliar with the subject, and then give an overview of some developments in the area of distance-regular graphs since the monograph 'BCN' [Brouwer, A.E., Cohen, A.M., Neumaier, A., Distance-Regular Graphs, Springer-Verlag, Berlin,
Edwin R. van Dam +2 more
openaire +4 more sources
Advanced Science, EarlyView.SpaMode introduces a versatile framework for spatial multi‐omics integration across vertical, horizontal, and mosaic scenarios. By disentangling modality‐invariant and variant features through a mixture‐of‐experts mechanism, it adaptively reconfigures spatially heterogeneous signals.
Xubin Zheng +6 more
wiley +1 more source
Consistent Semi-Supervised Graph Regularization for High Dimensional Data
, 2021 International audienceSemi-supervised Laplacian regularization, a standard graph-based approach for learning from both labelled and unlabelled data, was recently demonstrated to have an insignificant high dimensional learning efficiency with respect to ...
Mai, Xiaoyi, Couillet, Romain
core +1 more source
Quality aware graph learning regularization for heterogeneous air quality sensor networks [PDF]
, 2023 © Owner/Author | ACM 2023. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in EWSN '23: Proceedings of the 2023 International Conference on embedded
García Vidal, Jorge +2 more
core +1 more source
Nonlinear and oblique boundary value problems for the Stokes equations
Electronic Journal of Qualitative Theory of Differential Equations, 2011 In this paper we consider the nonlinear boundary value problem governed by a stationary perturbed Stokes system with mixed boundary conditions (Dirichlet- maximal monotone graph), in a smooth domain.
Hamid Benseridi, Mourad Dilmi
doaj +1 more source