Zobrazeno 1 - 10
of 156
pro vyhledávání: '"Bian Song"'
Autor:
Waga, Masaki, Matsuoka, Kotaro, Suwa, Takashi, Matsumoto, Naoki, Banno, Ryotaro, Bian, Song, Suenaga, Kohei
When monitoring a cyber-physical system (CPS) from a remote server, keeping the monitored data secret is crucial, particularly when they contain sensitive information, e.g., biological or location data. Recently, Banno et al. (CAV'22) proposed a prot
Externí odkaz:
http://arxiv.org/abs/2405.16767
Fully Homomorphic Encryption (FHE) allows one to outsource computation over encrypted data to untrusted servers without worrying about data breaching. Since FHE is known to be extremely computationally-intensive, application-specific accelerators eme
Externí odkaz:
http://arxiv.org/abs/2404.15819
Autor:
Liu, Yizhong, Liu, Andi, Lu, Yuan, Pan, Zhuocheng, Li, Yinuo, Liu, Jianwei, Bian, Song, Conti, Mauro
Sharding enhances blockchain scalability by dividing the network into shards, each managing specific unspent transaction outputs or accounts. As an introduced new transaction type, cross-shard transactions pose a critical challenge to the security an
Externí odkaz:
http://arxiv.org/abs/2403.03655
Autor:
Lu, Yao, Bian, Song, Chen, Lequn, He, Yongjun, Hui, Yulong, Lentz, Matthew, Li, Beibin, Liu, Fei, Li, Jialin, Liu, Qi, Liu, Rui, Liu, Xiaoxuan, Ma, Lin, Rong, Kexin, Wang, Jianguo, Wu, Yingjun, Wu, Yongji, Zhang, Huanchen, Zhang, Minjia, Zhang, Qizhen, Zhou, Tianyi, Zhuo, Danyang
In this paper, we investigate the intersection of large generative AI models and cloud-native computing architectures. Recent large models such as ChatGPT, while revolutionary in their capabilities, face challenges like escalating costs and demand fo
Externí odkaz:
http://arxiv.org/abs/2401.12230
Many convex optimization problems with important applications in machine learning are formulated as empirical risk minimization (ERM). There are several examples: linear and logistic regression, LASSO, kernel regression, quantile regression, $p$-norm
Externí odkaz:
http://arxiv.org/abs/2305.17482
Publikováno v:
ICML 2024
We study the certifiable robustness of ML classifiers on dirty datasets that could contain missing values. A test point is certifiably robust for an ML classifier if the classifier returns the same prediction for that test point, regardless of which
Externí odkaz:
http://arxiv.org/abs/2303.04811
Large-scale Transformer models are known for their exceptional performance in a range of tasks, but training them can be difficult due to the requirement for communication-intensive model parallelism. One way to improve training speed is to compress
Externí odkaz:
http://arxiv.org/abs/2301.02654
Community search is a problem that seeks cohesive and connected subgraphs in a graph that satisfy certain topology constraints, e.g., degree constraints. The majority of existing works focus exclusively on the topology and ignore the nodes' influence
Externí odkaz:
http://arxiv.org/abs/2207.01029
In many Internet of Things (IoT) applications, data sensed by an IoT device are continuously sent to the server and monitored against a specification. Since the data often contain sensitive information, and the monitored specification is usually prop
Externí odkaz:
http://arxiv.org/abs/2206.03582
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
BackgroundSingle-pulse transcranial magnetic stimulation (spTMS) applied to the Early Visual Cortex (EVC) has demonstrated the ability to suppress the perception on visual targets, akin to the effect of visual masking. However, the reported spTMS sup
Externí odkaz:
https://doaj.org/article/dbdb8def48114c64aeeee556cf5f4c5f
