Zobrazeno 1 - 10
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pro vyhledávání: '"Wang, TianHao"'
Autor:
Zhang, Mofan, Yang, Zhou, Zhang, Junpei, Huang, Chuyi, Wang, Tianhao, Chen, Yonghao, Fan, Ruirui, Snow, W. Michael
Polarized eV neutrons can address interesting scientific questions in nuclear physics, particle physics, and astrophysics/cosmology. We present the first experiment to polarize the neutrons on the Back-n beamline at the Chinese Spallation Neutron Sou
Externí odkaz:
http://arxiv.org/abs/2409.16598
Autor:
Fu, Yucheng, Wang, Tianhao
Differential privacy (DP) is widely employed to provide privacy protection for individuals by limiting information leakage from the aggregated data. Two well-known models of DP are the central model and the local model. The former requires a trustwor
Externí odkaz:
http://arxiv.org/abs/2409.10667
In-context learning (ICL) is a cornerstone of large language model (LLM) functionality, yet its theoretical foundations remain elusive due to the complexity of transformer architectures. In particular, most existing work only theoretically explains h
Externí odkaz:
http://arxiv.org/abs/2409.10559
As the utilization of network traces for the network measurement research becomes increasingly prevalent, concerns regarding privacy leakage from network traces have garnered the public's attention. To safeguard network traces, researchers have propo
Externí odkaz:
http://arxiv.org/abs/2409.05249
In the field of machine unlearning, certified unlearning has been extensively studied in convex machine learning models due to its high efficiency and strong theoretical guarantees. However, its application to deep neural networks (DNNs), known for t
Externí odkaz:
http://arxiv.org/abs/2408.00920
Video generation models (VGMs) have demonstrated the capability to synthesize high-quality output. It is important to understand their potential to produce unsafe content, such as violent or terrifying videos. In this work, we provide a comprehensive
Externí odkaz:
http://arxiv.org/abs/2407.12581
Numerous approaches have been recently proposed for learning fair representations that mitigate unfair outcomes in prediction tasks. A key motivation for these methods is that the representations can be used by third parties with unknown objectives.
Externí odkaz:
http://arxiv.org/abs/2406.16698
Deploying a well-optimized pre-trained speaker recognition model in a new domain often leads to a significant decline in performance. While fine-tuning is a commonly employed solution, it demands ample adaptation data and suffers from parameter ineff
Externí odkaz:
http://arxiv.org/abs/2406.07832
We prove that for any generating set $S$ of $\mathbb {Z}^n$, the continuous edge chromatic number of the Schreier graph of the Bernoulli shift action $G=F(S,2^{\mathbb{Z}^n})$ is $\chi'_c(G)=\chi'(G)+1$. In particular, for the standard generating set
Externí odkaz:
http://arxiv.org/abs/2406.02825
The fusion of raw features from multiple sensors on an autonomous vehicle to create a Bird's Eye View (BEV) representation is crucial for planning and control systems. There is growing interest in using deep learning models for BEV semantic segmentat
Externí odkaz:
http://arxiv.org/abs/2405.20986