標(biāo)題: Titlebook: Discovery Science; 26th International C Albert Bifet,Ana Carolina Lorena,Pedro H. Abreu Conference proceedings 2023 The Editor(s) (if appli [打印本頁] 作者: damped 時(shí)間: 2025-3-21 17:43
書目名稱Discovery Science影響因子(影響力)
書目名稱Discovery Science影響因子(影響力)學(xué)科排名
書目名稱Discovery Science網(wǎng)絡(luò)公開度
書目名稱Discovery Science網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Discovery Science被引頻次
書目名稱Discovery Science被引頻次學(xué)科排名
書目名稱Discovery Science年度引用
書目名稱Discovery Science年度引用學(xué)科排名
書目名稱Discovery Science讀者反饋
書目名稱Discovery Science讀者反饋學(xué)科排名
作者: MILL 時(shí)間: 2025-3-21 21:28 作者: intelligible 時(shí)間: 2025-3-22 00:41 作者: engender 時(shí)間: 2025-3-22 07:30 作者: GAVEL 時(shí)間: 2025-3-22 12:37 作者: condescend 時(shí)間: 2025-3-22 16:38 作者: condescend 時(shí)間: 2025-3-22 18:51 作者: Ventilator 時(shí)間: 2025-3-23 01:01
0302-9743 theory and network analysis; time series and forecasting; healthcare and biological data analysis; anomaly, outlier and novelty detection..978-3-031-45274-1978-3-031-45275-8Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: etidronate 時(shí)間: 2025-3-23 03:05 作者: Defraud 時(shí)間: 2025-3-23 06:15
Eignet sich meine Arbeit zur Publikation?ntologies and NLP embedding techniques to link relevant information present in the patient’s clinical notes to the original explanation. Our experiments, involving a human expert, highlight promising performance in correctly identifying relevant information about the diseases of the patients.作者: PHONE 時(shí)間: 2025-3-23 10:53 作者: 停止償付 時(shí)間: 2025-3-23 16:31
Semantic Enrichment of?Explanations of?AI Models for?Healthcarentologies and NLP embedding techniques to link relevant information present in the patient’s clinical notes to the original explanation. Our experiments, involving a human expert, highlight promising performance in correctly identifying relevant information about the diseases of the patients.作者: 逃避責(zé)任 時(shí)間: 2025-3-23 19:52
Conference proceedings 2023ber 2023.?The 37 full papers and 10 short papers presented in this volume were carefully reviewed and selected from 133 submissions. They were organized in topical sections as follows: Machine learning methods and applications; natural language processing and social media analysis; interpretability 作者: placebo 時(shí)間: 2025-3-23 22:18 作者: HEDGE 時(shí)間: 2025-3-24 03:45 作者: ANIM 時(shí)間: 2025-3-24 09:31
https://doi.org/10.1007/978-3-031-66913-2ications in various fields, including medical research, environmental monitoring, and quality control. For instance, medical research often estimates the prevalence of a particular disease in a population. Despite being a thriving research area, most existing quantification methods are limited to bi作者: Vasodilation 時(shí)間: 2025-3-24 11:03 作者: perpetual 時(shí)間: 2025-3-24 15:49
,The Learner’s Perspective Study,ataset. In this paper we explore a method that can reduce a large configuration space to a significantly smaller one and so help to reduce the search time for the potentially best workflow. We empirically validate the method on a set of workflows that include four ML algorithms (SVM, RF, LogR and LD作者: tackle 時(shí)間: 2025-3-24 21:43 作者: surmount 時(shí)間: 2025-3-24 23:52
Daniel T. L. Shek,Lu Yu,Diego Busiolhods combining data-driven and model-based approaches. However, while such hybrid methods have been tested in various scientific applications, they have been mostly tested on dynamical systems, with only limited study about the influence of each model component on global performance and parameter id作者: MILK 時(shí)間: 2025-3-25 03:32 作者: Mercantile 時(shí)間: 2025-3-25 10:07
Deane E. Neubauer,Shingo Ashizawas utilizing advanced pre-trained Natural Language Inference (NLI) models offer a viable solution when training data is unavailable. This work introduces the . framework, an unsupervised stance detection framework based on Zero-Shot Learning. It detects a five-valued user’s stance on social-political作者: STAT 時(shí)間: 2025-3-25 13:01
https://doi.org/10.1007/978-3-658-21246-9t is commonly made by malicious users or automated programs (i.e., bots) that mimic human behaviour. With the recent boom of online review systems, performing accurate review spam detection has become of primary importance for a review platform, to mitigate the effect of malicious users responsible 作者: negotiable 時(shí)間: 2025-3-25 17:32
https://doi.org/10.1007/978-3-658-28931-7ing tasks, current methods often rely on pre-trained neural language models. Using these models, the state-of-the-art supervised systems for key-phrase extraction require large amounts of labelled data and generalize poorly outside the training domain, while unsupervised approaches generally present作者: 厭倦嗎你 時(shí)間: 2025-3-25 22:34
Justus Junkermann,Ludwig Goldhahnlier detection is the task of individuating anomalous objects within a given data population they belong to. In this paper we propose a new technique to explain why a given data object has been singled out as anomalous. The explanation our technique returns also includes counterfactuals, each of whi作者: ARCH 時(shí)間: 2025-3-26 00:08
Bastian Baumeister,Roger Bergeruch capabilities are crucially important with the rising adoption of AI models in real-world applications, which require domain experts to understand how model predictions are extracted in order to make informed decisions. Despite the increasing number of XAI approaches for tabular, image, and graph作者: 火光在搖曳 時(shí)間: 2025-3-26 06:15
https://doi.org/10.1007/978-3-658-28931-7atisfied, and finally makes a decision by comparing the total score to a threshold. Scoring systems have a long history of active use in safety-critical domains such as healthcare and justice, where they provide guidance for making objective and accurate decisions. Given their genuine interpretabili作者: 侵蝕 時(shí)間: 2025-3-26 12:04
Justus Junkermann,Ludwig Goldhahn high-dimensional data sets in two-dimensional maps, using embeddings of data objects under exploration and representing their temporal relations with directed edges. Most existing dimensionality reduction techniques, such as t-SNE and UMAP, disregard the temporal or relational nature of the data du作者: 魯莽 時(shí)間: 2025-3-26 13:02 作者: 天然熱噴泉 時(shí)間: 2025-3-26 18:26
Eignet sich meine Arbeit zur Publikation?ocuses mainly on enabling computers to manipulate and generate human language, whereas TSA identifies patterns or components in time-dependent data. Given their different purposes, there has been limited exploration of combining them. In this study, we present an approach to convert text into time s作者: 剛開始 時(shí)間: 2025-3-27 00:56
https://doi.org/10.1007/978-3-031-45275-8computing methodologies; artificial intelligence; machine learning; natural language processing; search 作者: Accessible 時(shí)間: 2025-3-27 01:08 作者: 音的強(qiáng)弱 時(shí)間: 2025-3-27 07:54
Discovery Science978-3-031-45275-8Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 延期 時(shí)間: 2025-3-27 11:27 作者: 壓倒性勝利 時(shí)間: 2025-3-27 16:22
Exploring the?Intricacies of?Neural Network Optimizationually only affects training time, reducing it by up to 80% or increasing it by 200%. In contrast, the hidden layer size does not consistently affect the considered performance metrics. The optimizer can significantly affect the model’s overall performance while also varying the training time, with A作者: 知識分子 時(shí)間: 2025-3-27 18:54
iSOUP-SymRF: Symbolic Feature Ranking with?Random Forests in?Online Multi-target Regressionods’ parameters: the size of the ensemble and the number of selected features. Furthermore, to show the utility of iSOUP-SymRF and its rankings we use them in conjunction with two state-of-the-art online multi-target regression methods, iSOUP-Tree and AMRules, and analyze the impact of adding featur作者: 搖曳的微光 時(shí)間: 2025-3-28 01:51 作者: Abnormal 時(shí)間: 2025-3-28 03:22 作者: Affiliation 時(shí)間: 2025-3-28 09:08 作者: 把手 時(shí)間: 2025-3-28 11:43
: A Graph Convolutional Network-Based Approach for?Review Spam Detection author of a review to the reviewed item. Features of users, products and reviews are associated with nodes and edges, respectively..Experiments performed on publicly available review datasets prove the effectiveness of the proposed approach compared with some state-of-the-art approaches.作者: MIME 時(shí)間: 2025-3-28 16:04
Counterfactuals Explanations for?Outliers via?Subspaces Density Contrastive Lossrchitecture exploiting a . and . in order to learn both components of explanations. The learning procedure is guided by an . that simultaneously maximizes (minimizes, resp.) the isolation of the input outlier before applying the mask (resp., after the application of the mask returned by the mask gen作者: 廢止 時(shí)間: 2025-3-28 19:41 作者: 抗體 時(shí)間: 2025-3-29 00:51 作者: 高射炮 時(shí)間: 2025-3-29 04:38
Unmasking COVID-19 False Information on?Twitter: A Topic-Based Approach with?BERT作者: 構(gòu)成 時(shí)間: 2025-3-29 11:18
https://doi.org/10.1007/978-3-031-66913-2dels on 31 multi-class datasets. Our experimental results indicate that FMC-MQ is the best-performing quantifier outperforming other single and ensemble methods. Also, aggregating quantifier outputs seem to be a more promising research direction than aggregating classification scores for quantificat作者: 網(wǎng)絡(luò)添麻煩 時(shí)間: 2025-3-29 13:40
Mathematics is a Powerful Tool,ually only affects training time, reducing it by up to 80% or increasing it by 200%. In contrast, the hidden layer size does not consistently affect the considered performance metrics. The optimizer can significantly affect the model’s overall performance while also varying the training time, with A作者: 容易生皺紋 時(shí)間: 2025-3-29 16:41
https://doi.org/10.1007/978-981-287-582-2ods’ parameters: the size of the ensemble and the number of selected features. Furthermore, to show the utility of iSOUP-SymRF and its rankings we use them in conjunction with two state-of-the-art online multi-target regression methods, iSOUP-Tree and AMRules, and analyze the impact of adding featur作者: Favorable 時(shí)間: 2025-3-29 23:39
Daniel T. L. Shek,Lu Yu,Diego Busiolid approach based on partial dependence functions. Experiments are carried out with different types of machine learning models, including tree-based models and artificial neural networks. Our Python implementations of the hybrid methods are available at ..作者: 與野獸博斗者 時(shí)間: 2025-3-30 03:00 作者: essential-fats 時(shí)間: 2025-3-30 06:58 作者: labile 時(shí)間: 2025-3-30 08:51
https://doi.org/10.1007/978-3-658-21246-9 author of a review to the reviewed item. Features of users, products and reviews are associated with nodes and edges, respectively..Experiments performed on publicly available review datasets prove the effectiveness of the proposed approach compared with some state-of-the-art approaches.作者: dysphagia 時(shí)間: 2025-3-30 14:14
Justus Junkermann,Ludwig Goldhahnrchitecture exploiting a . and . in order to learn both components of explanations. The learning procedure is guided by an . that simultaneously maximizes (minimizes, resp.) the isolation of the input outlier before applying the mask (resp., after the application of the mask returned by the mask gen作者: Arresting 時(shí)間: 2025-3-30 18:05 作者: 火光在搖曳 時(shí)間: 2025-3-30 22:19 作者: 拋媚眼 時(shí)間: 2025-3-31 03:40 作者: bisphosphonate 時(shí)間: 2025-3-31 06:46 作者: 不怕任性 時(shí)間: 2025-3-31 11:09
Exploring the?Reduction of?Configuration Spaces of?Workflowsataset. In this paper we explore a method that can reduce a large configuration space to a significantly smaller one and so help to reduce the search time for the potentially best workflow. We empirically validate the method on a set of workflows that include four ML algorithms (SVM, RF, LogR and LD作者: 不公開 時(shí)間: 2025-3-31 15:17 作者: GUILT 時(shí)間: 2025-3-31 19:07
Knowledge-Guided Additive Modeling for?Supervised Regressionhods combining data-driven and model-based approaches. However, while such hybrid methods have been tested in various scientific applications, they have been mostly tested on dynamical systems, with only limited study about the influence of each model component on global performance and parameter id作者: debouch 時(shí)間: 2025-4-1 01:01 作者: 小卒 時(shí)間: 2025-4-1 02:01 作者: 開花期女 時(shí)間: 2025-4-1 09:43
: A Graph Convolutional Network-Based Approach for?Review Spam Detectiont is commonly made by malicious users or automated programs (i.e., bots) that mimic human behaviour. With the recent boom of online review systems, performing accurate review spam detection has become of primary importance for a review platform, to mitigate the effect of malicious users responsible 作者: floodgate 時(shí)間: 2025-4-1 13:21
Unsupervised Key-Phrase Extraction from?Long Texts with?Multilingual Sentence Transformersing tasks, current methods often rely on pre-trained neural language models. Using these models, the state-of-the-art supervised systems for key-phrase extraction require large amounts of labelled data and generalize poorly outside the training domain, while unsupervised approaches generally present作者: cancer 時(shí)間: 2025-4-1 15:09 作者: 充滿人 時(shí)間: 2025-4-1 19:49 作者: 濃縮 時(shí)間: 2025-4-2 01:00
Probabilistic Scoring Lists for?Interpretable Machine Learningatisfied, and finally makes a decision by comparing the total score to a threshold. Scoring systems have a long history of active use in safety-critical domains such as healthcare and justice, where they provide guidance for making objective and accurate decisions. Given their genuine interpretabili
