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Clustering analysis of functional data, which comprises observations that evolve continuously over time or space, has gained increasing attention across various scientific disciplines. Practical applications often involve functional data…

Methodology · Statistics 2024-06-19 Tingyu Zhu , Lan Xue , Carmen Tekwe , Keith Diaz , Mark Benden , Roger Zoh

While the identification of nonlinear dynamical systems is a fundamental building block of model-based reinforcement learning and feedback control, its sample complexity is only understood for systems that either have discrete states and…

Machine Learning · Statistics 2020-06-19 Horia Mania , Michael I. Jordan , Benjamin Recht

We consider inference for misaligned multivariate functional data that represents the same underlying curve, but where the functional samples have systematic differences in shape. In this paper we introduce a new class of generally…

Applications · Statistics 2023-01-23 Niels Lundtorp Olsen , Bo Markussen , Lars Lau Rakêt

The problem of automatic identification of physical activities performed by human subjects is referred to as Human Activity Recognition (HAR). There exist several techniques to measure motion characteristics during these physical…

Machine Learning · Computer Science 2019-06-06 Antonio Bevilacqua , Kyle MacDonald , Aamina Rangarej , Venessa Widjaya , Brian Caulfield , Tahar Kechadi

Continual learning (CL) learns a sequence of tasks incrementally. This paper studies the challenging CL setting of class-incremental learning (CIL). CIL has two key challenges: catastrophic forgetting (CF) and inter-task class separation…

Machine Learning · Computer Science 2024-12-23 Saleh Momeni , Sahisnu Mazumder , Bing Liu

Many classification techniques when the data are curves or functions have been recently proposed. However, the presence of misaligned problems in the curves can influence the performance of most of them. In this paper, we propose a…

Methodology · Statistics 2020-11-05 Lin Tang , Pengcheng Zeng , Jian Qing Shi , Won-Seok Kim

The partial least squares procedure was originally developed to estimate the slope parameter in multivariate parametric models. More recently it has gained popularity in the functional data literature. There, the partial least squares…

Statistics Theory · Mathematics 2012-05-30 Aurore Delaigle , Peter Hall

Fisher Discriminant Analysis (FDA) is a subspace learning method which minimizes and maximizes the intra- and inter-class scatters of data, respectively. Although, in FDA, all the pairs of classes are treated the same way, some classes are…

Machine Learning · Statistics 2020-07-01 Benyamin Ghojogh , Milad Sikaroudi , H. R. Tizhoosh , Fakhri Karray , Mark Crowley

Location estimation is a central problem in functional data analysis. In this paper, we investigate penalized spline estimators of location for discretely sampled functional data under a broad class of convex loss functions. Our framework…

Methodology · Statistics 2025-08-19 Ioannis Kalogridis

Remaining Useful Life (RUL) of an equipment or one of its components is defined as the time left until the equipment or component reaches its end of useful life. Accurate RUL estimation is exceptionally beneficial to Predictive Maintenance,…

Machine Learning · Computer Science 2019-04-16 Qiyao Wang , Shuai Zheng , Ahmed Farahat , Susumu Serita , Chetan Gupta

This work studies the theoretical rules of feature selection in linear discriminant analysis (LDA), and a new feature selection method is proposed for sparse linear discriminant analysis. An $l_1$ minimization method is used to select the…

Methodology · Statistics 2013-04-23 Cheng Wang , Longbing Cao , Baiqi Miao

This paper introduces a robust estimation strategy for the spatial functional linear regression model using dimension reduction methods, specifically functional principal component analysis (FPCA) and functional partial least squares…

Methodology · Statistics 2024-10-28 Ufuk Beyaztas , Abhijit Mandal , Han Lin Shang

Existing work in human activity detection classifies physical activities using a single fixed-length subset of a sensor signal. However, temporally consecutive subsets of a sensor signal are not utilized. This is not optimal for classifying…

Neural and Evolutionary Computing · Computer Science 2018-12-06 Niko Reunanen , Ville Könönen , Hermanni Hälvä , Jani Mäntyjärvi , Arttu Lämsä , Jussi Liikka

Elder people consequence a variety of problems while living Activities of Daily Living (ADL) for the reason of age, sense, loneliness and cognitive changes. These cause the risk to ADL which leads to several falls. Getting real life fall…

Computer Vision and Pattern Recognition · Computer Science 2020-10-27 Asma Khatun , Sk. Golam Sarowar Hossain

During the last decades, many methods for the analysis of functional data including classification methods have been developed. Nonetheless, there are issues that have not been adressed satisfactorily by currently available methods, as, for…

Methodology · Statistics 2017-02-08 Karen Fuchs , Wolfgang Pößnecker , Gerhard Tutz

Linear regression and classification methods with repeated functional data are considered. For each statistical unit in the sample, a real-valued parameter is observed over time under different conditions related by some neighborhood…

Methodology · Statistics 2024-09-23 Issam-Ali Moindjié , Cristian Preda , Sophie Dabo-Niang

While automatic monitoring and coaching of exercises are showing encouraging results in non-medical applications, they still have limitations such as errors and limited use contexts. To allow the development and assessment of physical…

Machine Learning · Computer Science 2025-01-14 Sao Mai Nguyen , Maxime Devanne , Olivier Remy-Neris , Mathieu Lempereur , André Thepaut

Clinical assessments for neuromuscular disorders, such as Spinal Muscular Atrophy (SMA) and Duchenne Muscular Dystrophy (DMD), continue to rely on subjective measures to monitor treatment response and disease progression. We introduce a…

Despite increasing accessibility to function data, effective methods for flexibly estimating underlying functional trend are still scarce. We thereby develop functional version of trend filtering for estimating trend of functional data…

Methodology · Statistics 2022-02-22 Tomoya Wakayama , Shonosuke Sugasawa

Human Activity Recognition~(HAR) is the classification of human movement, captured using one or more sensors either as wearables or embedded in the environment~(e.g. depth cameras, pressure mats). State-of-the-art methods of HAR rely on…

Computer Vision and Pattern Recognition · Computer Science 2020-06-16 Anjana Wijekoon , Nirmalie Wiratunga
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