Results 61 to 70 of about 15,452 (256)

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Nonparametric Click Modeling Using Dirichlet Process Mixture Model for Information Retrieval

IEEE Access
Click models are essential for comprehending user search behavior and enhancing ranking algorithms; nevertheless, current methodologies face challenges due to the variability of user interaction patterns across different query settings.
K. J. Amala, D. Rajeswari
doaj   +1 more source

Vernacular Futurism: How Persian Language Users Imagine AI

AI &Innovation, EarlyView.
ABSTRACT Public discourse about artificial intelligence increasingly unfolds through compressed forecasts, moral warnings, and everyday speculation circulating at platform speed. This study examines how Persian language users on X construct and contest AI futures, analyzing a corpus of 4741 posts collected between January 2023 and December 2025, with ...
Arthur Asa Berger, Ehsan Shahghasemi
wiley   +1 more source

Single‐cell RNA sequencing of peripheral blood defines two immunological subtypes of Sjögren's disease distinguished by anti‐SSA antibodies and aberrant B cell populations

Arthritis &Rheumatology, Accepted Article.
Objectives Sjögren's disease (SjD) is a heterogeneous autoimmune disorder characterized by substantial clinical and molecular diversity. This heterogeneity raises key questions regarding the existence of distinct pathogenic mechanisms underlying disease subtypes.
Geoffrey Urbanski, Kimberly E. Taylor, Emily Flynn, Armita Norouzi, Catherine Chu, Brittany Davidson, Arnab Ghosh, Joanne Nititham, Ravi K. Patel, Annie W. Poon, Gabriela K. Fragiadakis, Alexis J. Combes, Walter L. Eckalbar, Lindsey A. Criswell, Chun Jimmie Ye, Caroline H. Shiboski   +15 more
wiley   +1 more source

bspmma: An R Package for Bayesian Semiparametric Models for Meta-Analysis

Journal of Statistical Software, 2012
We introduce an R package, bspmma, which implements a Dirichlet-based random effects model specific to meta-analysis. In meta-analysis, when combining effect estimates from several heterogeneous studies, it is common to use a random-effects model.
Deborah Burr
doaj  

Machinery Early Fault Detection Based on Dirichlet Process Mixture Model

IEEE Access, 2019
The most commonly used single feature-based anomaly detection method for the complex machinery, such as large wind power equipment, steam turbine generator sets, and reciprocating compressors, exhibits a defect of low-alarm accuracy due to the non ...
Bo Ma, Yi Zhao, Ying Zhang, Qing Lei Jiang, Xiu Qun Hou   +4 more
doaj   +1 more source

Regularity of Gaussian Processes on Dirichlet Spaces [PDF]

Constructive Approximation, 2018
We are interested in the regularity of centered Gaussian processes (Z_x), x in M indexed by compact metric spaces M. It is shown that the almost everywhere Besov space regularity of such a process is (almost) equivalent to the Besov regularity of the covariance K(x,y) = E(Z_xZ_y) under the assumption that (i) there is an underlying Dirichlet structure ...
Kerkyacharian, Gerard, Ogawa, Shigeyoshi, Petrushev, Pencho, Picard, Dominique   +3 more
openaire   +4 more sources

Context‐centric proactive information delivery for Knowledge Work support: Opportunities, challenges, and directions. An Annual Review of Information Science and Technology (ARIST) paper

Journal of the Association for Information Science and Technology, EarlyView.
Abstract Context‐centric proactive information delivery (PID) is a relatively underexplored domain within recommender systems (RS) aimed at enhancing Knowledge Workers' productivity by proactively providing relevant information during digital tasks.
Mahta Bakhshizadeh, Christian Jilek, Markus Schröder, Heiko Maus, Andreas Dengel   +4 more
wiley   +1 more source

Accelerated Variational Dirichlet Process Mixtures [PDF]

, 2007
Dirichlet Process (DP) mixture models are promising candidates for clustering applications where the number of clusters is unknown a priori. Due to computational considerations these models are unfortunately unsuitable for large scale data-mining applications.
Kurihara, K., Welling, M., Vlassis, N.
openaire   +4 more sources

Incremental refinement of relevance rankings: Balancing relevance depth and scope

Journal of the Association for Information Science and Technology, EarlyView.
Abstract Delivering both relevant and topically diverse results is a key challenge in information retrieval (IR). This study introduces a hybrid method that incrementally refines rankings by combining probabilistic topic modeling (latent dirichlet allocation [LDA]) with citation‐based pennant retrieval grounded in Relevance Theory (RT), optimizing for ...
Müge Akbulut, Yaşar Tonta
wiley   +1 more source