Results 71 to 80 of about 36,894 (295)
A Geometric Perspective on Functional Outlier Detection
Stats, 2021 We consider functional outlier detection from a geometric perspective, specifically: for functional datasets drawn from a functional manifold, which is defined by the data’s modes of variation in shape, translation, and phase.
Moritz Herrmann, Fabian Scheipl
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, 2016 This paper gives an attempt to explore the manifold in the label space for multi-label learning. Traditional la-bel space is logical, where no manifold exists. In order to study the label manifold, the label space should be extended to a Euclidean space.
Min-ling Zhang +5 more
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Charting the Right Manifold: Manifold Mixup for Few-shot Learning
, 2020 Few-shot learning algorithms aim to learn model parameters capable of adapting to unseen classes with the help of only a few labeled examples. A recent regularization technique - Manifold Mixup focuses on learning a general-purpose representation, robust
Singh, Mayank +11 more
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Advanced Functional Materials, EarlyView.Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner +14 more
wiley +1 more source
Probability Distribution-Based Dimensionality Reduction on Riemannian Manifold of SPD Matrices
IEEE Access, 2020 Representing images and videos with Symmetric Positive Definite (SPD) matrices and utilizing the intrinsic Riemannian geometry of the resulting manifold has proved successful in many computer vision tasks.
Jieyi Ren, Xiao-Jun Wu
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Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites
Advanced Functional Materials, EarlyView.A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou +5 more
wiley +1 more source
Sensors, 2014 For decades, bearing factory quality evaluation has been a key problem and the methods used are always static tests. This paper investigates the use of piezoelectric ultrasonic transducers (PUT) as dynamic diagnostic tools and a relevant signal ...
Xiaoguang Chen +4 more
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Manifold Constrained Low-Rank and Joint Sparse Learning for Dynamic Cardiac MRI
IEEE Access, 2020 Reconstruction from highly accelerated dynamic magnetic resonance imaging (MRI) is of great significance for medical diagnosis. The application of low-rank and sparse matrix decomposition to MRI can improve imaging speed and efficiency.
Qingmin Meng, Xianchao Xiu, Yan Li
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Near‐Infrared Light‐Driven Zn/Au Janus Micromotors for Multiplex SERS Detection of Anticancer Drugs
Advanced Functional Materials, EarlyView.Zn/Au Janus micromotors, propelled by thermophoretic effects under NIR light, function as active SERS platforms for single and multiplex detection of anticancer drugs. Their dynamic motion enhances analyte exchange at the Au interface, reducing saturation and competitive adsorption, thereby improving sensitivity and extending the linear detection range.
Tijana Maric +8 more
wiley +1 more source
Local non‐linear alignment for non‐linear dimensionality reduction
IET Computer Vision, 2017 In manifold learning, alignment is performed with the objective of deriving the global low‐dimensional coordinates of input data from their local coordinates.
Guo Niu, Zhengming Ma
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