Zobrazeno 1 - 10
of 545
pro vyhledávání: '"Wang, Jingyao"'
In this paper, we explore the embedding of nonlinear dynamical systems into linear ordinary differential equations (ODEs) via the Carleman linearization method. Under dissipative conditions, numerous previous works have established rigorous error bou
Externí odkaz:
http://arxiv.org/abs/2405.12714
Autor:
Wang, Jingyao, Qiang, Wenwen, Song, Zeen, Si, Lingyu, Li, Jiangmeng, Zheng, Changwen, Su, Bing
The goal of universality in self-supervised learning (SSL) is to learn universal representations from unlabeled data and achieve excellent performance on all samples and tasks. However, these methods lack explicit modeling of the universality in the
Externí odkaz:
http://arxiv.org/abs/2405.01053
Micro-expressions (MEs) are involuntary movements revealing people's hidden feelings, which has attracted numerous interests for its objectivity in emotion detection. However, despite its wide applications in various scenarios, micro-expression recog
Externí odkaz:
http://arxiv.org/abs/2404.12024
Autor:
Zhang, Jianqi, Wang, Jingyao, Qiang, Wenwen, Xu, Fanjiang, Zheng, Changwen, Sun, Fuchun, Xiong, Hui
Transformer-based methods have made significant progress in time series forecasting (TSF). They primarily handle two types of tokens, i.e., temporal tokens that contain all variables of the same timestamp, and variable tokens that contain all input t
Externí odkaz:
http://arxiv.org/abs/2404.10337
Meta-learning enables rapid generalization to new tasks by learning knowledge from various tasks. It is intuitively assumed that as the training progresses, a model will acquire richer knowledge, leading to better generalization performance. However,
Externí odkaz:
http://arxiv.org/abs/2312.05771
The long-term goal of machine learning is to learn general visual representations from a small amount of data without supervision, mimicking three advantages of human cognition: i) no need for labels, ii) robustness to data scarcity, and iii) learnin
Externí odkaz:
http://arxiv.org/abs/2308.14267
Handwriting authentication is a valuable tool used in various fields, such as fraud prevention and cultural heritage protection. However, it remains a challenging task due to the complex features, severe damage, and lack of supervision. In this paper
Externí odkaz:
http://arxiv.org/abs/2307.11100
Meta-learning aims to learn general knowledge with diverse training tasks conducted from limited data, and then transfer it to new tasks. It is commonly believed that increasing task diversity will enhance the generalization ability of meta-learning
Externí odkaz:
http://arxiv.org/abs/2307.08924
In recent years, self-supervised learning (SSL) has emerged as a promising approach for extracting valuable representations from unlabeled data. One successful SSL method is contrastive learning, which aims to bring positive examples closer while pus
Externí odkaz:
http://arxiv.org/abs/2307.08913
Text-based person search (TBPS) aims to retrieve the images of the target person from a large image gallery based on a given natural language description. Existing methods are dominated by training models with parallel image-text pairs, which are ver
Externí odkaz:
http://arxiv.org/abs/2305.12964