Results 181 to 190 of about 9,834 (275)

On Using the Shapley Value for Anomaly Localization: A Statistical Investigation

Applied AI Letters, Volume 7, Issue 2, June 2026.
ABSTRACT Recent publications have suggested using the Shapley value for anomaly localization for sensor data systems. We use a reasonable statistical model for the classifiers required to compute the Shapley value to provide repeatable and rigorous analysis in the anomaly localization application.
Rick S. Blum, Xubin Fang, Franziska Freytag   +2 more
wiley   +1 more source

Prototype-Based Classifiers and Vector Quantization on a Quantum Computer-Implementing Integer Arithmetic Oracles for Nearest Prototype Search. [PDF]

Entropy (Basel)
Engelsberger A, Pšeničkova M, Villmann T.   +2 more
europepmc   +1 more source

On the Meaning of Localization in Non‐Local Quantum Field Theory

Annalen der Physik, Volume 538, Issue 6, June 2026.
In non‐local quantum field theory nature does not necessarily allow objects or events to be localized to exact mathematical points. Instead any physical measurement has a built‐in finite resolution set by the non‐locality scale. Spacetime remains continuous and Lorentz‐covariant, but below this scale pointlike localization becomes an idealization ...
E. J. Thompson
wiley   +1 more source

Experimentally Validated Quantum-Secure Federated Learning over a Multi-user Quantum Network. [PDF]

Research (Wash D C)
Liu ZP, Cao XY, Liu HW, Sun XR, Bao Y, Shen JY, Lu YS, Yin HL, Chen ZB.   +8 more
europepmc   +1 more source

Rethinking Per‐Thread Computation for Machine Learning Design Exploration: A Work‐Efficient GPU Strategy for K‐Means and XGBoost

Concurrency and Computation: Practice and Experience, Volume 38, Issue 11, June 2026.
ABSTRACT This paper presents novel GPU implementation strategies that effectively exploit the available parallelism, based on the “more work per thread” approach, for three machine learning design exploration tasks: Multiple K‐means evaluation, dimensionality reduction through parallel K‐means encoding for XGBoost trees, and XGBoost tree pruning ...
Olavo Barros, Isabela Freitas, Pedro H. Pereira, Walter de B. Neto, Adrián Alcolea, María Villarroya‐Gaudó, Javier Resano, José Augusto M. Nacif, Ricardo Ferreira   +8 more
wiley   +1 more source

Sparse-selective quantization for real-time cyber threat detection in large-scale networks. [PDF]

PLoS One
Xie Y, Wang R, Dong L.
europepmc   +1 more source

Analysis of flow cytometry data by matrix relevance learning vector quantization. [PDF]

PLoS One, 2013
Biehl M, Bunte K, Schneider P.
europepmc   +1 more source

Backpropagation Network‐Based Contrastive Learning for Unsupervised Domain Adaptation

Engineering Reports, Volume 8, Issue 6, June 2026.
Unsupervised domain adaptation for contractive learning. ABSTRACT This study introduces a new method for domain adaptation for image classification tasks that aims to improve the model's performance on a target domain after being trained on a source domain.
Yushui Xiao, Yong Huang, Yujie Li
wiley   +1 more source

Optimized Signal Acquisition and Advanced AI for Robust 1D EMG Classification: A Comparative Study of Machine Learning, Deep Learning, and Reinforcement Learning. [PDF]

Bioengineering (Basel)
Shinde A, Shete V, Mehendale N.
europepmc   +1 more source

Graph Model‐Based Edge Node Pilot Attack Tracing Technology of Power Terminal Embedded Components

Engineering Reports, Volume 8, Issue 6, June 2026.
A graph model‐based pilot attack‐tracing method for power terminal embedded components is proposed, integrating dynamic trust adjustment with random‐walk graph embedding. The approach achieves high detection probability (0.999 at 400 iterations) and robust anti‐attack capability (≥ 0.97) while maintaining < 2.0% packet loss, enabling efficient edge ...
Peng Xiao, Jian Hu, Li Liu
wiley   +1 more source