Prototype-based classification

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Webb16 jan. 2024 · Processing big data streams through machine learning algorithms has various challenges, such as little time to train the models, hardware memory constraints, and concept drift. In this paper, we show that prototype-based kernel classifiers designed by sparsification procedures, such as the approximate linear dependence (ALD) method, … Webb24 aug. 2014 · In this paper, we propose a prototype-based classification model for evolving data streams, called SyncStream, which dynamically models time-changing concepts and makes predictions in a local fashion.

Prototype-based classifier learning for long-tailed visual …

Webb16 maj 2024 · In our PCL, we propose to generate the categorical classifiers based on the prototypes by performing a learnable mapping function. To further alleviate the impact … Webb28 feb. 2024 · Deep neural network (DNN) based on incremental learning provides support for efficient garbage classification tasks. However, it is always challenging to accurately learn and preserve the information of known classes for updating DNN while new tasks are continuously emerging, which also affects the generalization performance of the model. … lack spot repair

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Webb3 maj 2024 · Causality-based Counterfactual Explanation for Classification Models Tri Dung Duong, Qian Li, Guandong Xu Counterfactual explanation is one branch of … Webb27 maj 2024 · The hierarchical prototype network (HPN) uses prototypes and a training routine based upon conditional subsets of training data to create hierarchically-organized prototypes (Hase et al., 2024). Garnot and Landrieu ( 2024 ) also use prototypes for hierarchical classification in Metric-Guided Prototype Learning (MGP) by adjusting the … WebbFör 1 dag sedan · Due to the limitations of inadequate Whole-Slide Image (WSI) samples with weak labels, pseudo-bag-based multiple instance learning (MIL) appears as a … proofpoint organizational safe list

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Prototype-based classification Applied Intelligence

Webb28 jan. 2024 · The CSN is inspired by and matches the performance of existing prototype-based classifiers that promote interpretability. One-sentence Summary: A new neural … Webb24 feb. 2024 · This paper presents a novel low-cost integrated system prototype, called School Violence Detection system (SVD), based on a 2D Convolutional Neural Network (CNN). It is used for classifying and identifying automatically violent actions in educational environments based on shallow cost hardware. Moreover, the paper fills the gap of real … proofpoint pdr checkWebb1 dec. 2024 · Abstract. In this paper, a novel hierarchical prototype-based approach for classification is proposed. This approach is able to perceive the data space and derive the multimodal distributions from streaming data at different levels of granularity in an online manner, based on which it further identifies meaningful prototypes to self-organize and … proofpoint outbound smart host

"Webb13 okt. 2009 · Abstract. In this chapter, one of themost popular and intuitive prototype-based classification algorithms, learning vector quantization (LVQ), is revisited, and … " - Prototype-based classification

Prototype-based classification

Quantum-inspired learning vector quantizers for prototype-based ...

Webb1 juli 2024 · Thanks to the prototype-based nature, the system structure of the proposed classifier is highly transparent, and its learning process is of “one pass” type and computationally lean. Its... Webb1 aug. 2024 · HP classifier is prototype-based approach with a multi-layered structure, which is of the same type as the proposed MLOP classifier. Nonetheless, the layer …

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Webb1 dec. 2024 · Prototypes play an instrumental role in prototype-based classification algorithms. Different prototype-based approaches use different ways to identify prototypes from data, and this creates the differences in performance, computational efficiency, system transparency and interpretability. Webb8 jan. 2016 · A particularly unique advantage of prototype-based methods is the narrow barrier in transitioning the learned classifier to a production system. In this paper, we …

http://www.scholarpedia.org/article/Fuzzy_classifiers Webb1 aug. 2024 · In this paper, a novel approach to the self-organization of hierarchical prototype-based classifiers from data is proposed. The approach recursively partitions the data at multiple levels of granularity into shape-free clusters of different sizes, resembling Voronoi tessellation, and naturally aggregates the resulting cluster medoids into a multi …

Webb3 dec. 2024 · Prototype-based methods use interpretable representations to address the black-box nature of deep learning models, in contrast to post-hoc explanation methods that only approximate such models. We propose the Neural Prototype Tree (ProtoTree), an intrinsically interpretable deep learning method for fine-grained image recognition. … Webb26 sep. 2024 · State-of-the-art (SOTA) deep learning mammogram classifiers, trained with weakly-labelled images, often rely on global models that produce predictions with limited interpretability, which is a key barrier to their successful translation into clinical practice.On the other hand, prototype-based models improve interpretability by associating …

Webb24 nov. 2024 · Prototype-based models like the Generalized Learning Vector Quantization (GLVQ) belong to the class of interpretable classifiers. Moreover, quantum-inspired methods get more and more into focus in machine learning due to its potential efficient computing. Further, its interesting mathematical perspectives offer new ideas for …

Webb11 apr. 2024 · In this paper, we study the task of unsupervised 2D image-based 3D shape retrieval (UIBSR), which aims to retrieve unlabeled shapes (target domain) using labeled images (source domain). Previous works on UIBSR mainly focus on aligning the prototypes generated by the source labels and predicted target pseudo labels for reducing the cross … proofpoint outbound dmarcWebb1 sep. 2013 · In this paper, a novel projected-prototype based classifier is proposed for text categorization, in which a document category is represented by a set of prototypes, each assembling a representative for the documents in a subclass and its corresponding term subspace. lack storage shedWebb1 juni 2007 · Prototype-based classification Abstract. Image-based diagnostic tools are important tools for the determination of diseases in many medical... Author … proofpoint outbound smtp serverWebb16 sep. 2024 · Our approach has been designed to enable the integration of prototype-based interpretable model to any highly accurate global mammogram classifier, where … lack sofa table as tv standWebbClass Prototypes based Contrastive Learning for Classifying Multi-Label and Fine-Grained Educational Videos Rohit Gupta · Anirban Roy · Sujeong Kim · Claire Christensen · Todd Grindal · Sarah Gerard · Madeline Cincebeaux · Ajay Divakaran · Mubarak Shah MaskCon: … lack straps corsageWebb11 okt. 2024 · The prototypical network is a prototype classifier based on meta-learning and is widely used for few-shot learning because it classifies unseen examples by constructing class-specific prototypes without adjusting … lack sleep side effectsWebb3 maj 2024 · A prototype-based counterfactual explanation framework (ProCE) is proposed that is capable of preserving the causal relationship underlying the features … proofpoint phish alarm