Results 81 to 90 of about 3,113,449 (308)

Deep active learning for multi label text classification

Scientific Reports
Given a set of labels, multi-label text classification (MLTC) aims to assign multiple relevant labels for a text. Recently, deep learning models get inspiring results in MLTC.
Qunbo Wang, Hangu Zhang, Wentao Zhang, Lin Dai, Yu Liang, Haobin Shi   +5 more
doaj   +1 more source

Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning

IEEE Access, 2019
In existing visual representation learning tasks, deep convolutional neural networks (CNNs) are often trained on images annotated with single tag, such as ImageNet.
Baoyuan Wu, Weidong Chen, Yanbo Fan, Yong Zhang, Jinlong Hou, Jie Liu, Tong Zhang   +6 more
doaj   +1 more source

Multi-label Classification with Meta-Labels [PDF]

2014 IEEE International Conference on Data Mining, 2014
The area of multi-label classification has rapidly developed in recent years. It has become widely known that the baseline binary relevance approach can easily be outperformed by methods which learn labels together. A number of methods have grown around the label power set approach, which models label combinations together as class values in a multi ...
Jesse Read, Antti Puurula, Albert Bifet
openaire   +3 more sources

Weighted Ensemble Classification of Multi-label Data Streams

, 2017
Many real world applications involve classification of multilabel data streams. However, most existing classification models mostly focused on classifying single-label data streams.
Hong Shen, Hui Tian, Tian, H., Shen, Hong, Wang, Lulu, Tian, Hui, Shen, H., Wang, L., Lulu Wang   +8 more
core   +1 more source

Structure‐forward targeting of claudins with synthetic binders

FEBS Letters, EarlyView.
Claudins form the paracellular barriers between epithelial and endothelial tissues at tight junctions and are targets for molecular binders with the goal of modulating barrier permeability. Claudin‐binding molecules are relevant in drug delivery or in altering claudin interactions with disease‐causing proteins.
Alex J. Vecchio
wiley   +1 more source

Engineering peptides into antibodies—opportunities and strategies for therapeutic innovation

FEBS Letters, EarlyView.
Peptides and antibodies occupy complementary therapeutic niches. Peptides recognize difficult targets in a compact format, while antibodies add specificity, long half‐life, and effector functions. This review examines strategies that merge both modalities—peptide grafting into loops, terminal and Fc fusions, and bioconjugation—highlighting how ...
Jinling Wang, Ruslana Romaniuk, Hristo L. Svilenov   +2 more
wiley   +1 more source

Partial Multi-Label Learning with Label Distribution

, 2020
Partial multi-label learning (PML) aims to learn from training examples each associated with a set of candidate labels, among which only a subset are valid for the training example. The common strategy to induce predictive model is trying to disambiguate
Xu, Ning, Liu, Yun-Peng, Geng, Xin
core   +1 more source

Label construction for multi-label feature selection [PDF]

, 2014
Multi-label learning handles datasets where each instance is associated with multiple labels, which are often correlated. As other machine learning tasks, multi-label learning also suffers from the curse of dimensionality, which can be mitigated by ...
Lee, Huei Diana, Huei Lee, Tsoumakas, Grigorios, Spolaôr, Newton, Grigorios Tsoumakas, Maria Carolina Monard, Newton Spolaor, Monard, Maria Carolina   +7 more
core   +1 more source

Epigenetic reprogramming of lineage switching in cancer

FEBS Letters, EarlyView.
Cancer cells rarely commit to a single identity. Epigenetic mechanisms and tumor microenvironment cues push epithelial cells toward flexible, hybrid states that can shift into mesenchymal, neuroendocrine, or stem‐like fates, driving metastasis, drug resistance, and tumor heterogeneity. Targeting the epigenetic regulators behind these transitions, using
Ezgi Boyvatlı, Burcu Akman, Ezgi Bağırsakçı, Nese Atabey, Serap Erkek‐Ozhan   +4 more
wiley   +1 more source

Incomplete multi–view partial multi–label learning network with structure–aware consistent fusion

Journal of King Saud University: Computer and Information Sciences
In recent years, incomplete multi-view partial multi-label classification has attracted growing attention due to its practical relevance. However, many existing methods rely on equal-weight (average) fusion and thus overlook sample-wise reliability ...
Xingang Mao, Yang Xu, Wenbin Bu, Zherui Yang   +3 more
doaj   +1 more source