Abstract 旨在解决Answer Selection Task,basic framework 是 build embeddings of QA based onbiLSTM, measure their closeness byCosine Similarity. 特点是用了CNN,Attention,以及两者融合。用的Datasets是TREC-QA, InsuranceQA. (即 对 选答案,将QA用biLSTM做表征,用的余弦相似性,将模型用CNN, Attention拓展。) ...
Lstm-based deep learning models for non-factoid answer selection. arXiv preprint arXiv:1511.04108, 2015.Tan, M.; Santos, C.D.; Xiang, B.; Zhou, B. LSTM-based deep learning models for non-factoid answer selection. arXiv 2015, arXiv:1511.04108....
Li J, Yin Z-Y (2021) Time integration algorithms for elasto-viscoplastic models with multiple hardening laws for geomaterials: enhancement and comparative study. Arch Comput Methods Eng 28(5):3869–3886. https://doi.org/10.1007/s11831-021-09527-4 Article MathSciNet Google Scholar Liu X, Zh...
Transformer language models with lstm-based cross-utterance information representation[C]//ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021: 7363-7367. 基于LSTM 跨句间表征的 Transformer 语言模型 摘要:传统语言模型都是在句子层面传统进行建模...
The new components used in this article include the coordination of stacked long short-term memory-based models and feature engineering methods. Also, more accurate and realistic modeling of the problem has been implemented according to the existing conditions through COVID-19 epidemic data. The ...
此外,我们可以在预测配置中使用一个以上的前瞻步骤,因为预测精度仍然得到保证。如果不是必须的,我们应该将前瞻性步骤定义为1。The 正常 训练 用于 预测 models. 学习我们使用Adam optimizer,学习率为0.1。我们还配置了100个提前停止的训练脚本,得到了用于异常检测算法的训练模型。
Firstly, SL-Modelling is used to obtain sequence-type trajectory models of normal trajectory groups directly for subsequent detection with no need to extract a large number of features manually and adapting to different sequence length. Then we introduce the concept of distance and semantic interest ...
We used the advanced models in trajectory prediction as the comparison models, such as LSTM, support vector machine (SVM), back propagation (BP) neural network, Hidden Markov Model (HMM), and convolutional long-term memory neural network (CNN-LSTM). The model we proposed is superior to the ...
The AUC metrics do not penalize low-valued false positives giving an high score for high-valued predictions placed at fixated locations and ignoring the others. Besides, the sAUC is designed to penalize models that take into account the center bias present in eye fixations. The NSS, instead, ...
This study addresses the pressing need for improved stock price prediction models in the financial markets, focusing on the Indonesian stock market. It int... M Diqi,IW Ordiyasa - 《Journal of Automation Mobile Robotics & Intelligent Systems》 被引量: 0发表: 2024年 Real-time risk prediction ...