Results 21 to 30 of about 5,885,991 (322)
VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation [PDF]
Annual Meeting of the Association for Computational Linguistics, 2021 We introduce VoxPopuli, a large-scale multilingual corpus providing 400K hours of unlabeled speech data in 23 languages. It is the largest open data to date for unsupervised representation learning as well as semi-supervised learning.
Changhan Wang +8 more
semanticscholar +1 more source
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017 We propose a new regularization method based on virtual adversarial loss: a new measure of local smoothness of the conditional label distribution given input.
Takeru Miyato +3 more
semanticscholar +1 more source
Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2021 Anomaly detection on attributed networks attracts considerable research interests due to wide applications of attributed networks in modeling a wide range of complex systems.
Yixin Liu +5 more
semanticscholar +1 more source
CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning [PDF]
Computer Vision and Pattern Recognition, 2021 Semi-supervised learning on class-imbalanced data, although a realistic problem, has been under studied. While existing semi-supervised learning (SSL) methods are known to perform poorly on minority classes, we find that they still generate high ...
Chen Wei +4 more
semanticscholar +1 more source
On semi-supervised learning [PDF]
TEST, 2019 arXiv admin note: substantial text overlap with arXiv:1709 ...
A. Cholaquidis, R. Fraiman, M. Sued
openaire +4 more sources
CONTRASTIVE SELF-SUPERVISED DATA FUSION FOR SATELLITE IMAGERY [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Self-supervised learning has great potential for the remote sensing domain, where unlabelled observations are abundant, but labels are hard to obtain. This work leverages unlabelled multi-modal remote sensing data for augmentation-free contrastive self ...
L. Scheibenreif, M. Mommert, D. Borth
doaj +1 more source
Dual Supervised Learning [PDF]
, 2020 Many supervised learning tasks are emerged in dual forms, e.g., English-to-French translation vs. French-to-English translation, speech recognition vs. text to speech, and image classification vs. image generation. Two dual tasks have intrinsic connections with each other due to the probabilistic correlation between their models.
Yingce Xia +5 more
openaire +3 more sources
Brain Sciences, 2021 Visual encoding models are important computational models for understanding how information is processed along the visual stream. Many improved visual encoding models have been developed from the perspective of the model architecture and the learning ...
Jingwei Li +6 more
doaj +1 more source
Weakly supervised machine learning
CAAI Transactions on Intelligence Technology, 2023 Supervised learning aims to build a function or model that seeks as many mappings as possible between the training data and outputs, where each training data will predict as a label to match its corresponding ground‐truth value.
Zeyu Ren, Shuihua Wang, Yudong Zhang
doaj +1 more source
Enhancing IoT Network Security: Unveiling the Power of Self-Supervised Learning against DDoS Attacks
Sensors, 2023 The Internet of Things (IoT), projected to exceed 30 billion active device connections globally by 2025, presents an expansive attack surface. The frequent collection and dissemination of confidential data on these devices exposes them to significant ...
Josue Genaro Almaraz-Rivera +2 more
doaj +1 more source