Results 31 to 40 of about 8,068,470 (297)
A Semi-Supervised Learning Method for Vietnamese Part of Speech Tagging [PDF]
, 2010 This paper presents a semi-supervised learning method for Vietnamese part of speech tagging. We take into account two powerful tagging models including Conditional Random Fields (CRFs)and the Guided Online-Learning models (GLs) as base learning models ...
Nguyen, Viet Cuong +4 more
core +1 more source
Semi-supervised learning with regularized Laplacian [PDF]
Optimization Methods and Software, 2016 We study a semi-supervised learning method based on the similarity graph and RegularizedLaplacian. We give convenient optimization formulation of the Regularized Laplacian method and establishits various properties. In particular, we show that the kernel of the methodcan be interpreted in terms of discrete and continuous time random walks and possesses
Konstantin Avrachenkov +2 more
openaire +4 more sources
Quantum semi-supervised kernel learning
Quantum Machine Intelligence, 2021 Quantum computing leverages quantum effects to build algorithms that are faster then their classical variants. In machine learning, for a given model architecture, the speed of training the model is typically determined by the size of the training dataset.
Seyran Saeedi +2 more
openaire +4 more sources
Semi‐supervised learning dehazing algorithm based on the OSV model
IET Image Processing, 2023 Despite the great progress that has been made in the task of single image dehazing, the results of the existing models in restoring image edge and texture information are still challenging.
Lijun Zhu +5 more
doaj +1 more source
Towards semi-supervised ensemble clustering using a new membership similarity measure
Automatika, 2023 Hierarchical clustering is a common type of clustering in which the dataset is hierarchically divided and represented by a dendrogram. Agglomerative Hierarchical Clustering (AHC) is a common type of hierarchical clustering in which clusters are created ...
Wenjun Li, Ting Li, Musa Mojarad
doaj +1 more source
Driving Maneuver Classification Using Domain Specific Knowledge and Transfer Learning
IEEE Access, 2021 With the increasing number of vehicles, the usage of technology has also been increased in the transportation system. Although automobile companies are using advanced technologies to develop high performing transports, traffic safety still remains to be ...
Supriya Sarker +2 more
doaj +1 more source
Graph Laplacian for Semi-supervised Learning
, 2023 Semi-supervised learning is highly useful in common scenarios where labeled data is scarce but unlabeled data is abundant. The graph (or nonlocal) Laplacian is a fundamental smoothing operator for solving various learning tasks. For unsupervised clustering, a spectral embedding is often used, based on graph-Laplacian eigenvectors.
Streicher, Or, Gilboa, Guy
openaire +3 more sources
Semi-Supervised Deep Representation Learning [PDF]
, 2019 Deep neural networks need a lot of data to show their full potential in modeling and solving problems. However, in many real-world applications labeling data is expensive or not feasible while abundant unlabeled data is available.
Vahid Noroozi (8973485)
core +1 more source
Dual Learning-Based Safe Semi-Supervised Learning
IEEE Access, 2018 In many real-world applications, labeled instances are generally limited and expensively collected, while the most instances are unlabeled and the amount is often sufficient.
Haitao Gan +3 more
doaj +1 more source
Full body virtual try‐on with semi‐self‐supervised learning
Electronics Letters, 2021 This paper proposes a full body virtual try‐on which handles both top and bottom garments and generates realistic try‐on images. For the full body virtual try‐on, this paper addresses lack of suitable training data to align and fit top and bottom ...
Hyug‐Jae Lee +5 more
doaj +1 more source