Results 141 to 150 of about 137,972 (308)

The Challenge of Handling Structured Missingness in Integrated Data Sources

Advanced Intelligent Discovery, EarlyView.
As data integration becomes ever more prevalent, a new research question that emerges is how to handle missing values that will inevitably arise in these large‐scale integrated databases? This missingness can be described as structured missingness, encompassing scenarios involving multivariate missingness mechanisms and deterministic, nonrandom ...
James Jackson, Marius Hofert, Eleni‐Rosalina Andrinopoulou, Niels Hagenbuch, Sarah McGough, Chris Harbron, Robin Mitra   +6 more
wiley   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

An error bound for Lasso and Group Lasso in high dimensions

CoRR, 2019
We leverage recent advances in high-dimensional statistics to derive new L2 estimation upper bounds for Lasso and Group Lasso in high-dimensions. For Lasso, our bounds scale as $(k^*/n) \log(p/k^*)$---$n\times p$ is the size of the design matrix and $k^*$ the dimension of the ground truth $\boldsymbolβ^*$---and match the optimal minimax rate. For Group
openaire   +2 more sources

Orlando di Lasso Ensemble, ensamble vocal (Alemania)

, 2006
Concierto interpretado por el Orlando di Lasso Ensemble. Fundado en Hannover en 1981, el Orlando di Lasso Ensemble es uno de los más distinguidos ensambles vocales de alemanes dedicados a la interpretación de la música antigua.
Orlando di Lasso Ensemble - Ensamble vocal (Alemania)
core  

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Estimation of treatment effects with high-dimensional controls [PDF]

We propose methods for inference on the average effect of a treatment on a scalar outcome in the presence of very many controls. Our setting is a partially linear regression model containing the treatment/policy variable and a large number p of controls ...
Christian Hansen, Victor Chernozhukov, Alexandre Belloni   +2 more
core  

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Neural lasso: a unifying approach of lasso and neural networks

International Journal of Data Science and Analytics
Abstract In recent years, there has been a growing interest in establishing bridges between statistics and neural networks. This article focuses on the adaptation of the widely used lasso algorithm within the context of neural networks. To accomplish this, the network configuration is first designed.
Ernesto Curbelo, David Delgado-Gómez, Danae Carreras   +2 more
openaire   +3 more sources

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source

Bronchoscopy Robot with Enhanced Flexibility and Stability via Multi‐Segment Variable Stiffness Catheter

Advanced Intelligent Systems, EarlyView.
This work presents a magnetic bronchoscopy robot with a novel multi‐segment variable stiffness catheter. This catheter can not only move flexibly in the narrow bronchi but also harden according to the need to provide support. Combined with remote wireless magnetic field drive, it provides a more precise and effective solution for biopsy of deep lung ...
Shucong Yin, Bin Huang, Shiyuan Dong, Junhao Wang, Liangshen Zhao, Yang Yang, Bingkun Bao, Hongen Liao, Fang Chen, Tianqi Huang, Boyu Zhang   +10 more
wiley   +1 more source