Zobrazeno 1 - 10
of 1 707
pro vyhledávání: '"P. Bagnall"'
There is a long history of research into time series clustering using distance-based partitional clustering. Many of the most popular algorithms adapt k-means (also known as Lloyd's algorithm) to exploit time dependencies in the data by specifying a
Externí odkaz:
http://arxiv.org/abs/2410.14269
Autor:
Kornjača, Milan, Hu, Hong-Ye, Zhao, Chen, Wurtz, Jonathan, Weinberg, Phillip, Hamdan, Majd, Zhdanov, Andrii, Cantu, Sergio H., Zhou, Hengyun, Bravo, Rodrigo Araiza, Bagnall, Kevin, Basham, James I., Campo, Joseph, Choukri, Adam, DeAngelo, Robert, Frederick, Paige, Haines, David, Hammett, Julian, Hsu, Ning, Hu, Ming-Guang, Huber, Florian, Jepsen, Paul Niklas, Jia, Ningyuan, Karolyshyn, Thomas, Kwon, Minho, Long, John, Lopatin, Jonathan, Lukin, Alexander, Macrì, Tommaso, Marković, Ognjen, Martínez-Martínez, Luis A., Meng, Xianmei, Ostroumov, Evgeny, Paquette, David, Robinson, John, Rodriguez, Pedro Sales, Singh, Anshuman, Sinha, Nandan, Thoreen, Henry, Wan, Noel, Waxman-Lenz, Daniel, Wong, Tak, Wu, Kai-Hsin, Lopes, Pedro L. S., Boger, Yuval, Gemelke, Nathan, Kitagawa, Takuya, Keesling, Alexander, Gao, Xun, Bylinskii, Alexei, Yelin, Susanne F., Liu, Fangli, Wang, Sheng-Tao
Quantum machine learning has gained considerable attention as quantum technology advances, presenting a promising approach for efficiently learning complex data patterns. Despite this promise, most contemporary quantum methods require significant res
Externí odkaz:
http://arxiv.org/abs/2407.02553
Autor:
Middlehurst, Matthew, Ismail-Fawaz, Ali, Guillaume, Antoine, Holder, Christopher, Rubio, David Guijo, Bulatova, Guzal, Tsaprounis, Leonidas, Mentel, Lukasz, Walter, Martin, Schäfer, Patrick, Bagnall, Anthony
aeon is a unified Python 3 library for all machine learning tasks involving time series. The package contains modules for time series forecasting, classification, extrinsic regression and clustering, as well as a variety of utilities, transformations
Externí odkaz:
http://arxiv.org/abs/2406.14231
Autor:
Zhang, Irina, Denholm, Jim, Hamidinekoo, Azam, Ålund, Oskar, Bagnall, Christopher, Huix, Joana Palés, Sulikowski, Michal, Vito, Ortensia, Lewis, Arthur, Unwin, Robert, Soderberg, Magnus, Burlutskiy, Nikolay, Qaiser, Talha
Accurate segmentation of glomerulus instances attains high clinical significance in the automated analysis of renal biopsies to aid in diagnosing and monitoring kidney disease. Analyzing real-world histopathology images often encompasses inter-observ
Externí odkaz:
http://arxiv.org/abs/2406.16900
Autor:
Ayllón-Gavilán, Rafael, Guijo-Rubio, David, Gutiérrez, Pedro Antonio, Bagnall, Anthony, Hervás-Martínez, César
Time Series Classification (TSC) covers the supervised learning problem where input data is provided in the form of series of values observed through repeated measurements over time, and whose objective is to predict the category to which they belong
Externí odkaz:
http://arxiv.org/abs/2306.10084
Autor:
Zia, Ali, Sharma, Renuka, Arablouei, Reza, Bishop-Hurley, Greg, McNally, Jody, Bagnall, Neil, Rolland, Vivien, Kusy, Brano, Petersson, Lars, Ingham, Aaron
Existing image/video datasets for cattle behavior recognition are mostly small, lack well-defined labels, or are collected in unrealistic controlled environments. This limits the utility of machine learning (ML) models learned from them. Therefore, w
Externí odkaz:
http://arxiv.org/abs/2305.16555
Autor:
Guijo-Rubio, David, Middlehurst, Matthew, Arcencio, Guilherme, Silva, Diego Furtado, Bagnall, Anthony
Time Series Extrinsic Regression (TSER) involves using a set of training time series to form a predictive model of a continuous response variable that is not directly related to the regressor series. The TSER archive for comparing algorithms was rele
Externí odkaz:
http://arxiv.org/abs/2305.01429
Bake off redux: a review and experimental evaluation of recent time series classification algorithms
In 2017, a research paper compared 18 Time Series Classification (TSC) algorithms on 85 datasets from the University of California, Riverside (UCR) archive. This study, commonly referred to as a `bake off', identified that only nine algorithms perfor
Externí odkaz:
http://arxiv.org/abs/2304.13029
We present AlgCo (Algebraic Coinductives), a practical framework for inductive reasoning over commonly used coinductive types such as conats, streams, and infinitary trees with finite branching factor. The key idea is to exploit the notion of algebra
Externí odkaz:
http://arxiv.org/abs/2301.09802
Autor:
Charlotte Louise Bagnall, Elizabeth Stevenson, Darel Cookson, Frederick Jones, Nicholas James Garnett
Publikováno v:
Frontiers in Psychology, Vol 15 (2024)
IntroductionPrimary–secondary school transitions are critical transitions for children that can be emotionally demanding longitudinal experiences, which can positively and negatively impact future emotional wellbeing and mental health. However, int
Externí odkaz:
https://doaj.org/article/d88330c22b934296baabf5c467cec5ce
