Zobrazeno 1 - 10
of 4 341
pro vyhledávání: '"Kang, Wei"'
We investigate the demand private coded caching problem, which is an $(N,K)$ coded caching problem with $N$ files, $K$ users, each equipped with a cache of size $M$, and an additional privacy constraint on user demands. We first present a new virtual
Externí odkaz:
http://arxiv.org/abs/2404.06884
In order to solve the problem that current convolutional neural networks can not capture the correlation features between the time domain signals of rolling bearings effectively, and the model accuracy is limited by the number and quality of samples,
Externí odkaz:
http://arxiv.org/abs/2403.15483
Autor:
Shen, Jingxiang, Kang, Wei
For the data analysis problem of shock-ramp compression, i.e., ramp compression after a relatively strong initial shock, a characteristics-based method that strictly deals with the initial hydrodynamic shock is described in detail. Validation of this
Externí odkaz:
http://arxiv.org/abs/2403.13380
In this paper, we consider the case that sharing many secrets among a set of participants using the threshold schemes. All secrets are assumed to be statistically independent and the weak secure condition is focused on. Under such circumstances we in
Externí odkaz:
http://arxiv.org/abs/2312.05737
We investigate the multi-access coded caching problem, which involves $N$ files, $K$ users, and $K$ caches in this paper. Each user can access $L$ adjacent caches in a cyclic manner. We present a coded placement scheme for the case of cache $M=\frac{
Externí odkaz:
http://arxiv.org/abs/2312.04922
We propose an ansatz without adjustable parameters for the calculation of dynamical structure factor. The ansatz combines quasi-particle Green's function, especially the contribution from the renormalization factor, and the exchange-correlation kerne
Externí odkaz:
http://arxiv.org/abs/2311.15008
Autor:
Yao, Zengwei, Guo, Liyong, Yang, Xiaoyu, Kang, Wei, Kuang, Fangjun, Yang, Yifan, Jin, Zengrui, Lin, Long, Povey, Daniel
The Conformer has become the most popular encoder model for automatic speech recognition (ASR). It adds convolution modules to a transformer to learn both local and global dependencies. In this work we describe a faster, more memory-efficient, and be
Externí odkaz:
http://arxiv.org/abs/2310.11230
Autor:
Kang, Wei, Yang, Xiaoyu, Yao, Zengwei, Kuang, Fangjun, Yang, Yifan, Guo, Liyong, Lin, Long, Povey, Daniel
In this paper, we introduce Libriheavy, a large-scale ASR corpus consisting of 50,000 hours of read English speech derived from LibriVox. To the best of our knowledge, Libriheavy is the largest freely-available corpus of speech with supervisions. Dif
Externí odkaz:
http://arxiv.org/abs/2309.08105
Autor:
Yang, Xiaoyu, Kang, Wei, Yao, Zengwei, Yang, Yifan, Guo, Liyong, Kuang, Fangjun, Lin, Long, Povey, Daniel
Prompts are crucial to large language models as they provide context information such as topic or logical relationships. Inspired by this, we propose PromptASR, a framework that integrates prompts in end-to-end automatic speech recognition (E2E ASR)
Externí odkaz:
http://arxiv.org/abs/2309.07414
Autor:
Wang, Guohong, Ma, Hua, Gao, Yansong, Abuadbba, Alsharif, Zhang, Zhi, Kang, Wei, Al-Sarawib, Said F., Zhang, Gongxuan, Abbott, Derek
Image camouflage has been utilized to create clean-label poisoned images for implanting backdoor into a DL model. But there exists a crucial limitation that one attack/poisoned image can only fit a single input size of the DL model, which greatly inc
Externí odkaz:
http://arxiv.org/abs/2309.04036