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Akademický článek
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Autor:
Zhang, Kai-Yi, Huang, An-Jing, Tu, Kun, Li, Ming-Han, Zhang, Chi, Qi, Wei, Wu, Ya-Dong, Yu, Yu
Secure multiparty computation enables collaborative computations across multiple users while preserving individual privacy, which has a wide range of applications in finance, machine learning and healthcare. Secure multiparty computation can be reali
Externí odkaz:
http://arxiv.org/abs/2411.04558
Spatial self-similarity is a hallmark of critical phenomena. We investigate the dynamic process of percolation, in which bonds are incrementally inserted to an empty lattice until fully occupied, and track the gaps describing the changes in cluster s
Externí odkaz:
http://arxiv.org/abs/2411.04748
Autor:
Zhang, Charles, Peng, Benji, Sun, Xintian, Niu, Qian, Liu, Junyu, Chen, Keyu, Li, Ming, Feng, Pohsun, Bi, Ziqian, Liu, Ming, Zhang, Yichao, Fei, Cheng, Yin, Caitlyn Heqi, Yan, Lawrence KQ, Wang, Tianyang
Word embeddings and language models have transformed natural language processing (NLP) by facilitating the representation of linguistic elements in continuous vector spaces. This review visits foundational concepts such as the distributional hypothes
Externí odkaz:
http://arxiv.org/abs/2411.05036
Understanding the extent of urban flooding is crucial for assessing building damage, casualties and economic losses. Synthetic Aperture Radar (SAR) technology offers significant advantages for mapping flooded urban areas due to its ability to collect
Externí odkaz:
http://arxiv.org/abs/2411.04153
High-quality training triplets (instruction, original image, edited image) are essential for instruction-based image editing. Predominant training datasets (e.g., InsPix2Pix) are created using text-to-image generative models (e.g., Stable Diffusion,
Externí odkaz:
http://arxiv.org/abs/2411.04713
Autor:
Yin, Shi, Tan, Hongqi, Chong, Li Ming, Liu, Haofeng, Liu, Hui, Lee, Kang Hao, Tuan, Jeffrey Kit Loong, Ho, Dean, Jin, Yueming
Background: Cone-beam computed tomography (CBCT) plays a crucial role in image-guided radiotherapy, but artifacts and noise make them unsuitable for accurate dose calculation. Artificial intelligence methods have shown promise in enhancing CBCT quali
Externí odkaz:
http://arxiv.org/abs/2411.01575
Recent studies on large language models (LLMs) and large multimodal models (LMMs) have demonstrated promising skills in various domains including science and mathematics. However, their capability in more challenging and real-world related scenarios
Externí odkaz:
http://arxiv.org/abs/2411.01492
Autor:
Andrews, Donald W. K., Li, Ming
This paper considers nonparametric estimation and inference in first-order autoregressive (AR(1)) models with deterministically time-varying parameters. A key feature of the proposed approach is to allow for time-varying stationarity in some time per
Externí odkaz:
http://arxiv.org/abs/2411.00358
In recent years, bundle recommendation systems have gained significant attention in both academia and industry due to their ability to enhance user experience and increase sales by recommending a set of items as a bundle rather than individual items.
Externí odkaz:
http://arxiv.org/abs/2411.00341