Zobrazeno 1 - 10
of 97
pro vyhledávání: '"Xie, Sihong"'
Autor:
Hong, Zesheng, Yue, Yubiao, Chen, Yubin, Cong, Lele, Lin, Huanjie, Luo, Yuanmei, Wang, Mini Han, Wang, Weidong, Xu, Jialong, Yang, Xiaoqi, Chen, Hechang, Li, Zhenzhang, Xie, Sihong
Computer-aided diagnostics has benefited from the development of deep learning-based computer vision techniques in these years. Traditional supervised deep learning methods assume that the test sample is drawn from the identical distribution as the t
Externí odkaz:
http://arxiv.org/abs/2404.18279
Autor:
Chen, Chao, Guo, Chenghua, Xu, Rui, Liao, Xiangwen, Zhang, Xi, Xie, Sihong, Xiong, Hui, Yu, Philip
Graphical models have demonstrated their exceptional capabilities across numerous applications, such as social networks, citation networks, and online recommendation systems. Despite these successes, their performance, confidence, and trustworthiness
Externí odkaz:
http://arxiv.org/abs/2404.14642
Ensuring both accuracy and robustness in time series prediction is critical to many applications, ranging from urban planning to pandemic management. With sufficient training data where all spatiotemporal patterns are well-represented, existing deep-
Externí odkaz:
http://arxiv.org/abs/2404.01217
Uncertainty is critical to reliable decision-making with machine learning. Conformal prediction (CP) handles uncertainty by predicting a set on a test input, hoping the set to cover the true label with at least $(1-\alpha)$ confidence. This coverage
Externí odkaz:
http://arxiv.org/abs/2403.15025
Graphs are ubiquitous in social networks and biochemistry, where Graph Neural Networks (GNN) are the state-of-the-art models for prediction. Graphs can be evolving and it is vital to formally model and understand how a trained GNN responds to graph e
Externí odkaz:
http://arxiv.org/abs/2403.06425
Sequences of linear systems arise in the predictor-corrector method when computing the Pareto front for multi-objective optimization. Rather than discarding information generated when solving one system, it may be advantageous to recycle information
Externí odkaz:
http://arxiv.org/abs/2402.15941
General large language models (LLMs) such as ChatGPT have shown remarkable success, but it has also raised concerns among people about the misuse of AI-generated texts. Therefore, an important question is how to detect whether the texts are generated
Externí odkaz:
http://arxiv.org/abs/2310.14479
Robust explanations of machine learning models are critical to establish human trust in the models. Due to limited cognition capability, most humans can only interpret the top few salient features. It is critical to make top salient features robust t
Externí odkaz:
http://arxiv.org/abs/2307.04024
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering, 2023
Rumor spreaders are increasingly utilizing multimedia content to attract the attention and trust of news consumers. Though quite a few rumor detection models have exploited the multi-modal data, they seldom consider the inconsistent semantics between
Externí odkaz:
http://arxiv.org/abs/2306.02137
Robust explanations of machine learning models are critical to establishing human trust in the models. The top-$k$ intersection is widely used to evaluate the robustness of explanations. However, most existing attacking and defense strategies are bas
Externí odkaz:
http://arxiv.org/abs/2212.14106