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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 16 of 16 1 Self-Training Sampling with Monolingual Data Uncertainty for Neural Machine Translation ... Jiao, Wenxiang; Wang, Xing; Tu, Zhaopeng. - : arXiv, 2021 BASE Show details 2 Self-Training Sampling with Monolingual Data Uncertainty for Neural Machine Translation ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Jiao, Wenxiang; King, Irwin. - : Underline Science Inc., 2021 BASE Show details 3 Anatomical Study on the Safety of Anterior Cervical Craniovertebral Fusion with Clival Screw Placement in Children Aged 1–6 Years Zhang, Shao-Jie; Li, Kun; Li, Zhi-Jun... In: Int J Gen Med (2021) BASE Show details 4 Multi-Task Learning with Shared Encoder for Non-Autoregressive Machine Translation ... Hao, Yongchang; He, Shilin; Jiao, Wenxiang. - : arXiv, 2020 BASE Show details 5 Assessing the Bilingual Knowledge Learned by Neural Machine Translation Models ... He, Shilin; Wang, Xing; Shi, Shuming. - : arXiv, 2020 BASE Show details 6 Information Aggregation for Multi-Head Attention with Routing-by-Agreement ... Li, Jian; Yang, Baosong; Dou, Zi-Yi. - : arXiv, 2019 BASE Show details 7 Neuron Interaction Based Representation Composition for Neural Machine Translation ... Li, Jian; Wang, Xing; Yang, Baosong. - : arXiv, 2019 BASE Show details 8 Multi-Granularity Self-Attention for Neural Machine Translation ... Hao, Jie; Wang, Xing; Shi, Shuming. - : arXiv, 2019 BASE Show details 9 Towards Understanding Neural Machine Translation with Word Importance ... He, Shilin; Tu, Zhaopeng; Wang, Xing. - : arXiv, 2019 BASE Show details 10 Towards Better Modeling Hierarchical Structure for Self-Attention with Ordered Neurons ... Hao, Jie; Wang, Xing; Shi, Shuming. - : arXiv, 2019 BASE Show details 11 Exploiting Deep Representations for Neural Machine Translation ... Dou, Zi-Yi; Tu, Zhaopeng; Wang, Xing. - : arXiv, 2018 BASE Show details 12 Temporal Coding of Voice Pitch Contours in Mandarin Tones Peng, Fei; Innes-Brown, Hamish; McKay, Colette M.. - : Frontiers Media S.A., 2018 BASE Show details 13 Hardware string matching engine for large and dynamic pattern set ; Da xing dong tai zi fu chuan ji de ying jian pi pei ji ; 大型動態字符串集的硬件匹配機 Wang, Xing (王興). - : City University of Hong Kong, 2014 BASE Show details 14 Multi-Stride String Searching for High-Speed Content Inspection Pao, Derek; Wang, Xing. - : Oxford University Press, 2012 BASE Show details 15 Multi-String Searching for High-Speed Content Inspection Pao, Derek; Wang, Xing. - : Oxford University Press, 2012 Abstract: Design of hardware-assisted high-speed string-matching engine for content inspection has been an active research topic. Scalability, flexibility and speed are the three major challenges. In this paper, we shall present a high-speed string matching engine for virus scanning that can process 3 bytes of input data per cycle. Our design uses a memory-based architecture. The hardware circuits need not be reconfigured when the pattern set is updated. We evaluate our design using the ClamAV virus database with over 82K patterns, and the memory cost of our method is about 2.4 MB. The proposed method is an improved version of our previously published method called quick sampling with on demand verification. The previous design has a memory cost of 1.4 MB and a throughput of 1 byte per cycle. Two novel architectural features are incorporated into the new design, namely a new technique to construct near-minimal dynamic perfect hash tables using the bit-shuffle approach, and the introduction of a new concept called byte-shift invariant code (BSIC). With the BSIC, a suffix verification unit can be shared by multiple prefix sampling units. Hence, the processing rate of the new design can be speeded up to three times the processing rate of the old design, while the memory cost is only increased by 72%. Keyword: Section D: Security in Computer Systems and Networks URL: http://comjnl.oxfordjournals.org/cgi/content/short/bxs093v1 https://doi.org/10.1093/comjnl/bxs093 BASE Hide details 16 Multi-Stride String Searching for High-Speed Content Inspection Pao, Derek; Wang, Xing. - : Oxford University Press, 2012 BASE Show details

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