Results 91 to 100 of about 37,640 (313)
Advanced Intelligent Discovery, EarlyView.This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source
IEEE Access, 2018 With the increasing demand for unsupervised learning for fault diagnosis, the subspace clustering has been considered as a promising technique enabling unsupervised fault diagnosis. Although various subspace clustering methods have been developed to deal
Jie Gao +4 more
doaj +1 more source
Subspace discovery for video anomaly detection
, 2010 PhDIn automated video surveillance anomaly detection is a challenging task. We address this task as a novelty detection problem where pattern description is limited and labelling information is available only for a small sample of normal instances.
Tziakos, Ioannis
core
Advanced Intelligent Discovery, EarlyView.Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi +2 more
wiley +1 more source
The Performance of Subspace Algorithm Cointegration Analysis: A Simulation Study [PDF]
This paper presents a simulation study that assesses the finite sample performance of the subspace algorithm cointegration analysis developed in Bauer und Wagner (2002b).
Martin Wagner, Dietmar Bauer
core
Multi-view subspace clustering
, 2016 For many computer vision applications, the data sets distribute on certain low;dimensional subspaces. Subspace clustering is to find such underlying subspaces and cluster the data points correctly.
Gao, Hongchang (hongchanggao@gmail.com) +4 more
core +1 more source
Advanced Intelligent Systems, EarlyView.HTFC gets 3D refractive index tomograms of flowing cells. Label‐free monocytes are engineered to express patterns of cytoplasmic vacuoles. From the tomogram, an efficient dimensionality reduction is operated. Interpretable features are extracted to classify the expression severity of phenotypes coexisting in each cell, visually represented by a seven ...
Marika Valentino +9 more
wiley +1 more source
A dynamic subspace anomaly detection method using generic algorithm for streaming network data
, 2015 A great deal of research attention has been paid to data mining on data streams in recent years. In this chapter, the authors carry out a case study of anomaly detection in large and high-dimensional network connection data streams using Stream Projected
Zhang, Ji, Li, Hongzhou
core +1 more source
Advanced Physics Research, EarlyView.ABSTRACT We introduce a family of bosonic quantum error‐correcting codes built as a rotation‐symmetric superposition of squeezed vacuum states, which promise protection against both loss and dephasing noise channels. The robustness of these “squeezed‐vacuum codes” arises from being arranged at evenly spaced angles in phase‐space, and simultaneously in ...
Nir Gutman +4 more
wiley +1 more source
Using Subspace Methods for Estimating ARMA Models for Multivariate Time Series with Conditionally Heteroskedastic Innovations [PDF]
This paper deals with the estimation of linear dynamic models of the ARMA type for the conditional mean for time series with conditionally heteroskedastic innovation process widely used in modelling financial time series.
Dietmar Bauer
core