標(biāo)題: Titlebook: Data Science; 8th International Co Yang Wang,Guobin Zhu,Zeguang Lu Conference proceedings 2022 The Editor(s) (if applicable) and The Author [打印本頁(yè)] 作者: Sentry 時(shí)間: 2025-3-21 16:50
書目名稱Data Science影響因子(影響力)
書目名稱Data Science影響因子(影響力)學(xué)科排名
書目名稱Data Science網(wǎng)絡(luò)公開(kāi)度
書目名稱Data Science網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書目名稱Data Science被引頻次
書目名稱Data Science被引頻次學(xué)科排名
書目名稱Data Science年度引用
書目名稱Data Science年度引用學(xué)科排名
書目名稱Data Science讀者反饋
書目名稱Data Science讀者反饋學(xué)科排名
作者: 清真寺 時(shí)間: 2025-3-21 21:32 作者: immunity 時(shí)間: 2025-3-22 01:13 作者: indifferent 時(shí)間: 2025-3-22 08:09
https://doi.org/10.1007/978-3-319-56585-9extraction of essential data and the modeling strategy chosen. The data of the CTR task are often very sparse, and Factorization Machines (FMs) are a class of general predictors working effectively with it. However, the performance of FMs can be limited by the fixed feature representation and the sa作者: 有罪 時(shí)間: 2025-3-22 11:02
Nikolay Konstantinov,Sergey Dorichenkots at combining low-order and high-order functions. However, they ignore the importance of the attention mechanism for learning input features. The ECABiNet model is proposed in this article to enhance the performance of CTR. On the one hand, the ECABiNet model can learn the importance of features d作者: Entropion 時(shí)間: 2025-3-22 13:26 作者: Entropion 時(shí)間: 2025-3-22 20:15 作者: Celiac-Plexus 時(shí)間: 2025-3-22 22:35
Nikolay Konstantinov,Sergey Dorichenkoflow graphs have attracted much attention since they can deal with the obfuscation problem to a certain extent. Many malware classification methods based on data flow graphs have been proposed. Some of them are based on user-defined features or graph similarity of data flow graphs. Graph neural netw作者: malign 時(shí)間: 2025-3-23 04:55
https://doi.org/10.1007/978-3-030-24933-5 and cannot obtain satisfactory results in some scenarios. In this paper, we design a semisupervised time series anomaly detection algorithm based on metric learning. The algorithm model mines the features in the time series from the perspectives of the time domain and frequency domain. Furthermore,作者: MAOIS 時(shí)間: 2025-3-23 09:30 作者: Seizure 時(shí)間: 2025-3-23 11:21
Managing Brands in Competitive Marketplacesap the complex and diverse user relationships, so it is difficult to obtain an accurate modeling representation of the user. To solve this, we propose a multirelationship aware personalized recommendation(MrAPR) model, which aggregates the various relationships between social users from two aspects 作者: 存在主義 時(shí)間: 2025-3-23 17:07 作者: 中世紀(jì) 時(shí)間: 2025-3-23 19:36 作者: 非實(shí)體 時(shí)間: 2025-3-23 23:54 作者: condemn 時(shí)間: 2025-3-24 04:45
Concluding Remarks and New Directionsmed the dynamic reasoning and information bottleneck (DRIB) to improve human interpretability and understandability. In the method, a novel dynamic reasoning decision algorithm was proposed to reduce multiply accumulate operations and improve the interpretability of the calculation. The information 作者: 強(qiáng)行引入 時(shí)間: 2025-3-24 09:50
Europe of Regions — A Nordic Viewng in misalignment between input low resolution (LR) images and output high resolution (HR) images. GAN training has difficulty converging. Based on this, an advanced GAN-based image SR reconstruction method is presented. First, the dense connection residual block and attention mechanism are integra作者: Semblance 時(shí)間: 2025-3-24 14:36 作者: Entropion 時(shí)間: 2025-3-24 17:01
https://doi.org/10.1007/978-981-19-5194-7artificial intelligence; communication systems; computer hardware; computer networks; computer systems; c作者: 輕信 時(shí)間: 2025-3-24 19:06
978-981-19-5193-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor作者: 青春期 時(shí)間: 2025-3-24 23:09
Data Science978-981-19-5194-7Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: Harrowing 時(shí)間: 2025-3-25 06:58 作者: Efflorescent 時(shí)間: 2025-3-25 10:24
A Preliminary Study of Interpreting CNNs Using Soft Decision Treesf feature visualization and human-labeled features, we demonstrate that the soft decision trees identify more consistent features while maintaining much higher classification performance than the normal decision tree.作者: grandiose 時(shí)間: 2025-3-25 13:31 作者: 過(guò)于平凡 時(shí)間: 2025-3-25 19:22 作者: JUST 時(shí)間: 2025-3-25 20:34 作者: languor 時(shí)間: 2025-3-26 02:51 作者: instructive 時(shí)間: 2025-3-26 07:38
Competitions for Young Mathematiciansd other optimizations were tested after system deployment on the Lenovo cluster of the NMEFC. After optimization, a well-balanced performance of the system is obtained, and computing resources are reasonably utilized, thus laying the foundation for real-time tropical cyclone forecasting.作者: 易發(fā)怒 時(shí)間: 2025-3-26 10:13 作者: HUSH 時(shí)間: 2025-3-26 13:43 作者: Curmudgeon 時(shí)間: 2025-3-26 20:48
A Survey of Malware Classification Methods Based on Data Flow Graphre classification methods. Their respective advantages and disadvantages are summarized as well. In addition, the future trend of the data flow graph-based malware classification method is analyzed, which is of great significance for promoting the development of malware detection technology.作者: 組裝 時(shí)間: 2025-3-27 00:47
1865-0929 ientists, Engineers and Educators, ICPCSEE 2022 held in Chengdu, China, in? August, 2022...The 65 full papers and 26 short papers presented in these two volumes were carefully reviewed and selected from 261 submissions. The papers are organized in topical sections on: Big Data Mining and Knowledge M作者: STENT 時(shí)間: 2025-3-27 04:48 作者: 抗生素 時(shí)間: 2025-3-27 06:35 作者: LAY 時(shí)間: 2025-3-27 12:44 作者: 火車車輪 時(shí)間: 2025-3-27 15:38
Managing Brands in Competitive Marketplaces multiple relationships. The MrAPR model better describes the characteristics of user interest and can be compatible with the existing sequence recommendation methods. The experimental results on two real-world datasets clearly show the effectiveness of the MrAPR model.作者: Hemiplegia 時(shí)間: 2025-3-27 19:05
Interpreting the Chemical Residues StoryR images by shrinking the network, which will share similar degradation with real-world images. Finally, we make paired data of the generated real LR images and HR images for training the SR network. Our approach can obtain better results than the recent SR approach on the NTIRE2020 real-world SR challenge Track1 dataset.作者: intertwine 時(shí)間: 2025-3-28 00:55 作者: headway 時(shí)間: 2025-3-28 05:39
Automatic Generation of Graduation Thesis Comments Based on Multilevel Analysis review work of the graduation thesis from pure manual operation to machine review combined with manual operation can not only reduce manpower consumption but also make the review work more objective and fair, making it more objective on the basis of traditional subjective review.作者: Aspiration 時(shí)間: 2025-3-28 06:25
Multirelationship Aware Personalized Recommendation Model multiple relationships. The MrAPR model better describes the characteristics of user interest and can be compatible with the existing sequence recommendation methods. The experimental results on two real-world datasets clearly show the effectiveness of the MrAPR model.作者: lobster 時(shí)間: 2025-3-28 11:24 作者: arabesque 時(shí)間: 2025-3-28 15:53 作者: 鳥籠 時(shí)間: 2025-3-28 20:06 作者: 陳腐思想 時(shí)間: 2025-3-29 02:22 作者: Countermand 時(shí)間: 2025-3-29 03:19
Data Analyses and Parallel Optimization of the Tropical-Cyclone Coupled Numerical Modeldescription of physical processes between atmospheric-ocean fluids. An operational ocean-atmosphere-wave coupled modeling system is employed to improve the prediction accuracy of tropical cyclones in the National Marine Environmental Forecasting Center (NMEFC). Due to the urgent need for operational作者: 玉米棒子 時(shí)間: 2025-3-29 10:55 作者: 考博 時(shí)間: 2025-3-29 11:56
Focusing on the Importance of Features for CTR Predictionts at combining low-order and high-order functions. However, they ignore the importance of the attention mechanism for learning input features. The ECABiNet model is proposed in this article to enhance the performance of CTR. On the one hand, the ECABiNet model can learn the importance of features d作者: idiopathic 時(shí)間: 2025-3-29 15:44
Active Anomaly Detection Technology Based on Ensemble Learningectively detecting anomaly points. Most of the existing anomaly detection schemes are unsupervised methods, such as anomaly detection methods based on density, distance and clustering. In total, unsupervised anomaly detection methods have many limitations. For example, they cannot be well combined w作者: Homocystinuria 時(shí)間: 2025-3-29 20:08 作者: 繁忙 時(shí)間: 2025-3-30 01:44 作者: Dislocation 時(shí)間: 2025-3-30 05:33
Anomaly Detection of?Multivariate Time Series Based on?Metric Learning and cannot obtain satisfactory results in some scenarios. In this paper, we design a semisupervised time series anomaly detection algorithm based on metric learning. The algorithm model mines the features in the time series from the perspectives of the time domain and frequency domain. Furthermore,作者: orthopedist 時(shí)間: 2025-3-30 10:49 作者: lipids 時(shí)間: 2025-3-30 13:29
Multirelationship Aware Personalized Recommendation Modelap the complex and diverse user relationships, so it is difficult to obtain an accurate modeling representation of the user. To solve this, we propose a multirelationship aware personalized recommendation(MrAPR) model, which aggregates the various relationships between social users from two aspects 作者: fatuity 時(shí)間: 2025-3-30 16:38
Preliminary Study on Adapting ProtoPNet to Few-Shot Learning Using MAML learn class-specific prototypes and does not support few-shot learning. We propose the few-shot learning version of ProtoPNet by using MAML, enabling it to converge quickly on different classification tasks. We test our model on the Omniglot and MiniImagenet datasets and evaluate their prototype in作者: Coordinate 時(shí)間: 2025-3-30 23:33 作者: affinity 時(shí)間: 2025-3-31 03:31 作者: 過(guò)分 時(shí)間: 2025-3-31 06:02 作者: 滔滔不絕地講 時(shí)間: 2025-3-31 09:18 作者: Geyser 時(shí)間: 2025-3-31 14:27
Real-World Superresolution by Using Deep Degradation Learninggh-resolution (HR) images and low-resolution (LR) images. Conversely, their superresolution performance in real-world superresolution tests is reduced because these methods create paired LR images by simply interpolating and downsampling HR images, which is very different from natural degradation. I
