Results 1 to 10 of about 825,885 (311)

Bayesian sequential data assimilation for COVID-19 forecasting [PDF]

Epidemics, 2022
We introduce a Bayesian sequential data assimilation and forecasting method for non-autonomous dynamical systems. We applied this method to the current COVID-19 pandemic.
Maria L. Daza-Torres, Marcos A. Capistrán, Antonio Capella, J. Andrés Christen   +3 more
doaj   +2 more sources

A Machine Learning Framework for Balancing Training Sets of Sensor Sequential Data Streams [PDF]

Sensors, 2021
The recent explosive growth in the number of smart technologies relying on data collected from sensors and processed with machine learning classifiers made the training data imbalance problem more visible than ever before.
Budi Darma Setiawan, Uwe Serdült, Victor Kryssanov   +2 more
doaj   +2 more sources

Predicting Organization Performance Changes: A Sequential Data-Based Framework [PDF]

Frontiers in Psychology, 2022
The business environment is increasingly uncertain due to the rapid development of disruptive information technologies, the changing global economy, and the COVID-19 pandemic.
Meiqi Song, Xiangling Fu, Shan Wang, Zhao Du, Yuanqiu Zhang   +4 more
doaj   +2 more sources

Getting a Better Sense of Data Drift in Dynamic Systems: Sequence-Based Deep Learning for Monitoring Slowly Evolving Degradation Processes

Engineering Proceedings, 2023
Deep Learning (DL) for monitoring slowly evolving degradation processes typically involves overcoming data drift, complexity, and unavailability issues resulting from dynamic and harsh conditions and the rarity of labeled failure patterns, respectively ...
Tarek Berghout, Mohamed Benbouzid
doaj   +1 more source

Comparison of sequential data analysis and functional data analysis for locomotor adaptation [PDF]

PLoS ONE
Torin Quinlivan, Kacy Kane, Christopher M. Hill, Duchwan Ryu   +3 more
doaj   +2 more sources

Kernel Clustering With Sigmoid Regularization for Efficient Segmentation of Sequential Data

IEEE Access, 2022
The segmentation of sequential data can be formulated as a clustering problem, where the data samples are grouped into non-overlapping clusters with the constraint that all members of each cluster are in a successive order.
Tung Doan, Atsuhiro Takasu
doaj   +1 more source

Convolutional signature for sequential data

Digital Finance, 2022
AbstractSignature is an infinite graded sequence of statistics known to characterize geometric rough paths. While the use of the signature in machine learning is successful in low-dimensional cases, it suffers from the curse of dimensionality in high-dimensional cases, as the number of features in the truncated signature transform grows exponentially ...
Ming Min, Tomoyuki Ichiba
openaire   +3 more sources

Distribution Regression for Sequential Data [PDF]

, 2020
Published at AISTATS ...
Lemercier, M, Salvi, C, Damoulas, T, Bonilla, EV, Lyons, T   +4 more
openaire   +5 more sources

Subspace Clustering for Sequential Data [PDF]

2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014
We propose Ordered Subspace Clustering (OSC) to segment data drawn from a sequentially ordered union of subspaces. Current subspace clustering techniques learn the relationships within a set of data and then use a separate clustering algorithm such as NCut for final segmentation.
Stephen Tierney, Junbin Gao, Yi Guo 0001
openaire   +1 more source

Sequential Classification of Palm Gestures Based on A* Algorithm and MLP Neural Network for Quadrocopter Control

Metrology and Measurement Systems, 2017
This paper presents an alternative approach to the sequential data classification, based on traditional machine learning algorithms (neural networks, principal component analysis, multivariate Gaussian anomaly detector) and finding the shortest path in a
Wodziński Marek, Krzyżanowska Aleksandra   +1 more
doaj   +1 more source