標(biāo)題: Titlebook: Analysis of Images, Social Networks and Texts; 8th International Co Wil M. P. van der Aalst,Vladimir Batagelj,Elena Tu Conference proceedin [打印本頁(yè)] 作者: 解放 時(shí)間: 2025-3-21 16:37
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書目名稱Analysis of Images, Social Networks and Texts讀者反饋學(xué)科排名
作者: 調(diào)情 時(shí)間: 2025-3-21 22:19 作者: saturated-fat 時(shí)間: 2025-3-22 00:41 作者: 吸氣 時(shí)間: 2025-3-22 07:24
An Algorithm for Constructing a Topological Skeleton for Semi-structured Spatial Data Based on Persie article. In the work, the main topological feature for analysis of object is a hole. The application of the developed algorithm to solve the actual problem of geoinformatics in the matching of spatial objects at different scales of map is shown. Comparison of topological skeletons at different tree depths is demonstrated.作者: instructive 時(shí)間: 2025-3-22 10:45 作者: 粗糙 時(shí)間: 2025-3-22 15:08 作者: TAG 時(shí)間: 2025-3-22 19:11
,Digitale Produktion: Bottom-up-?konomie,Being more expensive to compute than plain stochastic gradient descent, K-FAC allows the agent to converge a bit faster in terms of epochs compared to Adam on simple reinforcement learning tasks and tend to be more stable and less strict to hyperparameters selection. Considering the latest results w作者: CIS 時(shí)間: 2025-3-23 00:34
Der Mensch im Digitalzeitalter: Sapiens 2.0,ral methods for induction of decision trees and their ensembles based on evolutionary algorithms. The main difference of our approach is using real-valued vector representation of decision tree that allows to use a large number of different optimization algorithms, as well as optimize the whole tree作者: 不怕任性 時(shí)間: 2025-3-23 05:13
Critical Perspectives on Digitising Africae article. In the work, the main topological feature for analysis of object is a hole. The application of the developed algorithm to solve the actual problem of geoinformatics in the matching of spatial objects at different scales of map is shown. Comparison of topological skeletons at different tre作者: Flustered 時(shí)間: 2025-3-23 06:39
Electronic Theses and Dissertationso validate our approach on a data about revenue of a large Russian restaurant chain. We pay special attention to solve two problems: data heterogeneity and a high number of correlated features. We describe methods for considering heterogeneity—observations weighting and estimating models on subsampl作者: 先行 時(shí)間: 2025-3-23 11:55
https://doi.org/10.1007/978-94-6091-299-3to solve problems of determining various diseases. Neural networks are onearameters of augmentations of the approaches to solving such problems. In this paper, the usage of online augmentation during the training of neural networks was proposed to improve the quality of the ECGs classification. The 作者: Indurate 時(shí)間: 2025-3-23 14:41 作者: Reverie 時(shí)間: 2025-3-23 18:56 作者: Abjure 時(shí)間: 2025-3-24 00:22 作者: 得體 時(shí)間: 2025-3-24 02:41 作者: forecast 時(shí)間: 2025-3-24 08:16 作者: 偽書 時(shí)間: 2025-3-24 12:16 作者: Ointment 時(shí)間: 2025-3-24 17:02
Aggeliki Aggeli,Mette Mechlenborggraphs, and for representation of graphs as a whole. This paper considers the popular graph2vec approach, which shows quite good results for ordinary graphs. In the field of natural language processing, however, a graph structure called a dependency tree is often used to express the connections betw作者: CRUC 時(shí)間: 2025-3-24 19:35 作者: Musket 時(shí)間: 2025-3-25 01:18 作者: Occlusion 時(shí)間: 2025-3-25 05:35 作者: Culmination 時(shí)間: 2025-3-25 10:32 作者: Hdl348 時(shí)間: 2025-3-25 11:40
https://doi.org/10.1007/978-981-10-7697-8omputer-readable documents). To highlight in the text of people, organizations, geographical locations, etc., many approaches are used. Although, well-known bidirectional LSTM neural networks, show good results, there are points for improvement. Usually, the word embedding vector are used as the inp作者: 原諒 時(shí)間: 2025-3-25 19:18
Alan Rosling,Kathryn Littlemore also estimates the cost of all sanctions - both for those who receive and those who impose them. As input variables for DEA model we use the impact of sender commitment, anticipated target and sender economic costs, and actual target and sender economic costs. As the output variable, we use the out作者: 陪審團(tuán)每個(gè)人 時(shí)間: 2025-3-25 22:47
Electronic Theses and Dissertationshe base model. The obtained results demonstrate quality on par with state-of-the-art systems, which serves to re-establish the importance of semantic features in coreference resolution, as well as the applicability of neural networks for the task.作者: Injunction 時(shí)間: 2025-3-26 02:30 作者: 有幫助 時(shí)間: 2025-3-26 05:36
https://doi.org/10.1007/978-981-10-7697-8used in our work in two modes: feature extraction and fine-tuning for the NER task. Evaluation of the results was carried out on the FactRuEval dataset and the BiLSTM network (FastText?+?CNN?+?extra) was taken as the baseline. Our model, built on fine-tuned deep contextual BERT model, shows good res作者: BUDGE 時(shí)間: 2025-3-26 12:16 作者: 肉身 時(shí)間: 2025-3-26 13:31
Using Semantic Information for Coreference Resolution with Neural Networks in Russianhe base model. The obtained results demonstrate quality on par with state-of-the-art systems, which serves to re-establish the importance of semantic features in coreference resolution, as well as the applicability of neural networks for the task.作者: 慎重 時(shí)間: 2025-3-26 17:01
Recognition of Parts of Speech Using the Vector of Bigram Frequenciesequencies of syntactic bigrams including the test word and one of the 10.000 most frequent words was at the inputs of the network. The neural network was trained by the criterion of minimum cross–entropy. When recognizing parts of speech on the test sample, the average recognition accuracy was 99.1%作者: jealousy 時(shí)間: 2025-3-26 23:50 作者: 和音 時(shí)間: 2025-3-27 02:41
Wil M. P. van der Aalst,Vladimir Batagelj,Elena Tu作者: Peculate 時(shí)間: 2025-3-27 05:22 作者: lobster 時(shí)間: 2025-3-27 11:01 作者: ONYM 時(shí)間: 2025-3-27 14:08
,Digitale Produktion: Bottom-up-?konomie, Adam on simple reinforcement learning tasks and tend to be more stable and less strict to hyperparameters selection. Considering the latest results we show that DDQN with K-FAC learns more quickly than with other optimizers and improves constantly in contradiction to similar with Adam or RMSProp.作者: Fillet,Filet 時(shí)間: 2025-3-27 17:57 作者: 奴才 時(shí)間: 2025-3-28 01:11
https://doi.org/10.1007/978-981-10-7697-8 network architectures: recurrent and convolutional, as well as simpler feedforward networks. Classification accuracy was evaluated for different architectures, text representations and sets of miscellaneous parameters.作者: 記憶 時(shí)間: 2025-3-28 03:40 作者: glacial 時(shí)間: 2025-3-28 08:33 作者: 不開心 時(shí)間: 2025-3-28 13:24 作者: travail 時(shí)間: 2025-3-28 16:33
Evolutionary Algorithms for Constructing an Ensemble of Decision Trees or ensemble for avoiding local optima. Differential evolution and evolution strategies were chosen as optimization algorithms, as they have good results in reinforcement learning problems. We test the predictive performance of this methods using several public UCI data sets, and the proposed methods show better quality than classical methods.作者: hidebound 時(shí)間: 2025-3-28 19:26 作者: Range-Of-Motion 時(shí)間: 2025-3-29 02:54 作者: separate 時(shí)間: 2025-3-29 05:04
A Method of Semantic Change Detection Using Diachronic Corpora Datatered. The method is tested on a group of English and Russian words which gained new meanings in the 20th century. The obtained results show that the proposed method allows one to detect semantics changes, as well as to determine the time of these changes.作者: 縱火 時(shí)間: 2025-3-29 10:04
Automated Approach to Rhythm Figures Search in English Textnts a new automated approach to integrated search of rhythm figures in fiction including anaphora, epiphora, anadiplosis, symploce and simple repetition provided for by an original lexical tool designed within the framework of the research. The ad hoc experiments have proved this approach to be reliable and informative.作者: Corroborate 時(shí)間: 2025-3-29 12:05
1865-0929 cial network analysis; analysis of images and video; optimization problems on graphs and network structures; analysis of dynamic behaviour through event data..978-3-030-39574-2978-3-030-39575-9Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: Congregate 時(shí)間: 2025-3-29 18:27 作者: 讓你明白 時(shí)間: 2025-3-29 20:53
Formalization of Medical Records Using an Ontology: Patient Complaintseir values. The algorithm corrects syntactical mistakes according to the hierarchical information from the ontology. The resulting algorithm was proved on 3000 clinical records of Department of Neurosurgery of FEFU.作者: 琺瑯 時(shí)間: 2025-3-30 00:44
Conference proceedings 2020ed without being reviewed). The papers are organized in topical sections on general topics of data analysis; natural language processing; social network analysis; analysis of images and video; optimization problems on graphs and network structures; analysis of dynamic behaviour through event data..作者: Fraudulent 時(shí)間: 2025-3-30 06:18
Der Mensch im Digitalzeitalter: Sapiens 2.0, or ensemble for avoiding local optima. Differential evolution and evolution strategies were chosen as optimization algorithms, as they have good results in reinforcement learning problems. We test the predictive performance of this methods using several public UCI data sets, and the proposed methods show better quality than classical methods.作者: tendinitis 時(shí)間: 2025-3-30 12:14 作者: 枯燥 時(shí)間: 2025-3-30 14:03
https://doi.org/10.1007/978-94-6091-299-3possibility of using various types of online augmentations was explored. The most promising methods were highlighted. Experimental studies showed that the quality of the classification was improved for various tasks and various neural network architectures.作者: ascetic 時(shí)間: 2025-3-30 19:36 作者: intention 時(shí)間: 2025-3-30 21:21 作者: 土產(chǎn) 時(shí)間: 2025-3-31 01:00 作者: Crater 時(shí)間: 2025-3-31 08:01 作者: 偏離 時(shí)間: 2025-3-31 09:11
Christian Kassung,Sebastian Schwesingerthat the performance of the CNN models was much worse on this set (an almost 30% drop in word accuracy). We performed a classification of errors made by the best model both on the standard test set and the new one.作者: sphincter 時(shí)間: 2025-3-31 16:14
Guided Layer-Wise Learning for Deep Models Using Side Informationscriminative training of deep neural networks, DR is defined as a distance over the features and included in the learning objective. With our experimental tests, we show that DR can help the backpropagation to cope with vanishing gradient problems and to provide faster convergence and smaller generalization errors.作者: Progesterone 時(shí)間: 2025-3-31 18:26
Adapting the Graph2Vec Approach to Dependency Trees for NLP Tasksres of dependency trees. This new vector representation can be used in NLP tasks where it is important to model syntax (e.g. authorship attribution, intention labeling, targeted sentiment analysis etc.). Universal Dependencies treebanks were clustered to show the consistency and validity of the proposed tree representation methods.作者: 一回合 時(shí)間: 2025-4-1 00:58
Morpheme Segmentation for Russian: Evaluation of Convolutional Neural Network Modelsthat the performance of the CNN models was much worse on this set (an almost 30% drop in word accuracy). We performed a classification of errors made by the best model both on the standard test set and the new one.作者: Ballad 時(shí)間: 2025-4-1 01:52
Optimizing Q-Learning with K-FAC AlgorithmBeing more expensive to compute than plain stochastic gradient descent, K-FAC allows the agent to converge a bit faster in terms of epochs compared to Adam on simple reinforcement learning tasks and tend to be more stable and less strict to hyperparameters selection. Considering the latest results w作者: 影響 時(shí)間: 2025-4-1 09:51
Evolutionary Algorithms for Constructing an Ensemble of Decision Treesral methods for induction of decision trees and their ensembles based on evolutionary algorithms. The main difference of our approach is using real-valued vector representation of decision tree that allows to use a large number of different optimization algorithms, as well as optimize the whole tree
