標(biāo)題: Titlebook: Advances in Knowledge Discovery and Data Mining; 20th Pacific-Asia Co James Bailey,Latifur Khan,Ruili Wang Conference proceedings 2016 Spri [打印本頁] 作者: 驅(qū)逐 時(shí)間: 2025-3-21 18:50
書目名稱Advances in Knowledge Discovery and Data Mining影響因子(影響力)
書目名稱Advances in Knowledge Discovery and Data Mining影響因子(影響力)學(xué)科排名
書目名稱Advances in Knowledge Discovery and Data Mining網(wǎng)絡(luò)公開度
書目名稱Advances in Knowledge Discovery and Data Mining網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Advances in Knowledge Discovery and Data Mining被引頻次
書目名稱Advances in Knowledge Discovery and Data Mining被引頻次學(xué)科排名
書目名稱Advances in Knowledge Discovery and Data Mining年度引用
書目名稱Advances in Knowledge Discovery and Data Mining年度引用學(xué)科排名
書目名稱Advances in Knowledge Discovery and Data Mining讀者反饋
書目名稱Advances in Knowledge Discovery and Data Mining讀者反饋學(xué)科排名
作者: FUME 時(shí)間: 2025-3-21 22:54
978-3-319-31752-6Springer International Publishing Switzerland 2016作者: dithiolethione 時(shí)間: 2025-3-22 02:10
https://doi.org/10.1007/978-1-4471-7293-2g problems, JCHL uses a single feature space to jointly classify multiple classification tasks with heterogeneous labels. For instance, biologists usually have to label the gene expression images with developmental stages and simultaneously annotate their anatomical terms. We would like to classify 作者: 跑過 時(shí)間: 2025-3-22 06:42
Giacomo Vivanti,Melanie Pellecchiaesentatives of sampling methods, undersampling and oversampling cannot outperform each other. That is, undersampling fits some data sets while oversampling fits some other. Besides, the sampling rate also significantly influences the performance of a classifier, while existing methods usually adopt 作者: 固執(zhí)點(diǎn)好 時(shí)間: 2025-3-22 10:45
Kristen Bottema-Beutel,Shannon Crowleyexity and sparsity levels of the solution. Addressing the sparsity is important to improve learning generalization, prediction accuracy and computational speedup. In this paper, we employ the max-margin principle and sparse approach to propose a new Sparse AMM (SAMM). We solve the new optimization o作者: Highbrow 時(shí)間: 2025-3-22 15:05
https://doi.org/10.1007/978-3-031-04927-9, and relational connections between users in review systems. Although these methods can successfully identify spam activities, evolving fraud strategies can successfully escape from the detection rules by purchasing positive comments from massive random users, i.e., user Cloud. In this paper, we st作者: Cabinet 時(shí)間: 2025-3-22 18:58
Clinical Guide to Exposure Therapytive models such as SVM. However, extra difficulties do arise in optimizing non-convex learning objectives and selecting multiple hyperparameters. Observing that many variations of large margin learning could be reformulated as jointly minimizing a parameterized quadratic objective, in this paper we作者: Habituate 時(shí)間: 2025-3-22 21:22
https://doi.org/10.1007/978-3-031-04927-9sion is to complementally generate base models and elaborately combine their outputs. Traditionally, the weighted average of the outputs is treated as the final prediction. This means each base model plays a constant role in the whole data space. In fact, we know the predictive accuracy of each base作者: Hallowed 時(shí)間: 2025-3-23 01:27
Clinical Guide to Exposure Therapyh test pattern with some predefined probability. In order to fully utilize the predictions provided by a conformal classifier, it is essential that those predictions are reliable, i.e., that a user is able to assess the quality of the predictions made. Although conformal classifiers are statisticall作者: 結(jié)合 時(shí)間: 2025-3-23 05:31
https://doi.org/10.1007/978-3-031-04927-9ed degree pathways to facilitate successful and timely graduation. This paper presents future-course grade predictions methods based on sparse linear models and low-rank matrix factorizations that are specific to each course or student-course tuple. These methods identify the predictive subsets of p作者: GEAR 時(shí)間: 2025-3-23 11:55
https://doi.org/10.1007/978-3-319-43773-6ansfer knowledge from a completed source optimisation task to a new target task in order to overcome the cold start problem. We model source data as noisy observations of the target function. The level of noise is computed from the data in a Bayesian setting. This enables flexible knowledge transfer作者: Isometric 時(shí)間: 2025-3-23 17:28
Jignesh Patel MD, PhD,Jon Kobashigawa MD, degrade the performance of traditional online learning algorithms. Thus, many existing works focus on detecting concept drift based on statistical evidence. Other works use sliding window or similar mechanisms to select the data that closely reflect current concept. Nevertheless, few works study h作者: COUCH 時(shí)間: 2025-3-23 20:24
W. Kim Halford,Jemima Petch,Debra Creedytering methods by letting a user select samples based on his/her knowledge. However, due to knowledge limitation, a single user may only pick out the samples that s/he is familiar with while ignore the others, such that the selected samples are often biased. We propose a framework to address this is作者: CREST 時(shí)間: 2025-3-24 01:16
W. Kim Halford,Jemima Petch,Debra Creedyrd classification and regression problems where a domain expert can provide the labels for the data in a reasonably short period of time, training data in such longitudinal studies must be obtained only by waiting for the occurrence of sufficient number of events. The main objective of this work is 作者: palliative-care 時(shí)間: 2025-3-24 04:35 作者: 貪婪的人 時(shí)間: 2025-3-24 06:35
Patricia R. Recupero,Samara E. Harmsence between pair-wise consecutive frames at a specific time, we measure the divergence between two OCSVM classifiers, which are learnt from two contextual sets, i.e., immediate past set and immediate future set. To speed up the processing procedure, the two OCSVM classifiers are updated in an onlin作者: Emmenagogue 時(shí)間: 2025-3-24 13:16 作者: magnanimity 時(shí)間: 2025-3-24 17:15
Andrew Hecht,Jonathan S. Markowitzupervised nonlinear dimensionality reduction method that aims at lower space complexity is proposed. First, a positive and negative competitive learning strategy is introduced to the single layered Self-Organizing Incremental Neural Network (SOINN) to process partially labeled datasets. Then, we for作者: 水槽 時(shí)間: 2025-3-24 22:38
Ryan Budwany,Tony K. George,Timothy R. Deer usually have different physical interpretations. It may be inappropriate to map multiple views of data onto a shared feature space and directly compare them. In this paper, we propose a simple yet effective Cross-View Feature Hashing (CVFH) algorithm via a “partition and match” approach. The featur作者: Reclaim 時(shí)間: 2025-3-25 01:08
Advances in Knowledge Discovery and Data Mining978-3-319-31753-3Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 高調(diào) 時(shí)間: 2025-3-25 04:05 作者: 不愛防注射 時(shí)間: 2025-3-25 10:40 作者: 脫落 時(shí)間: 2025-3-25 12:31 作者: 詳細(xì)目錄 時(shí)間: 2025-3-25 17:51
0302-9743 al and image data; anomalydetection and clustering; novel models and algorithms; and text mining andrecommender systems..978-3-319-31752-6978-3-319-31753-3Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 骯臟 時(shí)間: 2025-3-25 23:50 作者: Torrid 時(shí)間: 2025-3-26 01:38
https://doi.org/10.1007/978-3-031-04927-9 regularization is also included to make the objective function well-posed. The proposed method is evaluated on several UCI datasets. Compared with single models and other ensemble models, our proposed achieves better performance. From the experiments, we also find that the convergence of Locally Weighted Ensemble is fast.作者: CANON 時(shí)間: 2025-3-26 07:46 作者: 暴發(fā)戶 時(shí)間: 2025-3-26 09:18 作者: NORM 時(shí)間: 2025-3-26 12:37 作者: Ledger 時(shí)間: 2025-3-26 18:06 作者: Reverie 時(shí)間: 2025-3-26 23:14 作者: appall 時(shí)間: 2025-3-27 04:01 作者: FID 時(shí)間: 2025-3-27 08:59 作者: 硬化 時(shí)間: 2025-3-27 10:51
Front Matteres of psychosocial actions are tc be understood, described, and explained. In this tradition, behaviors that are deemed unacceptable or disruptive for a socio-cultural group are said to be explained by, caused by, or attributable to some defect, deficiency, disruption, or disorganization of some age作者: aplomb 時(shí)間: 2025-3-27 16:49
to new grounds.Offers an effortless interpretation and synt.In a sweeping synthesis of new research in a number of different disciplines, this book argues that we humans are not who we think we are. As he explores the interconnections between cutting-edge work in bioanthropology, evolutionary biolo作者: 借喻 時(shí)間: 2025-3-27 21:07
Joint Classification with Heterogeneous Labels Using Random Walk with Dynamic Label Propagationed of a sort of racism, for what is important about us is not that we are of the same biological species, but that we are both persons, and I have not cast doubt on that. One’s dignity does not depend on one’s parentage even to the extent of having been born of women or born at all. We normally igno作者: 改變立場(chǎng) 時(shí)間: 2025-3-27 22:13 作者: 輕快帶來危險(xiǎn) 時(shí)間: 2025-3-28 05:11 作者: 使閉塞 時(shí)間: 2025-3-28 09:35 作者: Classify 時(shí)間: 2025-3-28 11:43
Optimal Training and Efficient Model Selection for Parameterized Large Margin Learningheight, but conventional flight is possible only in its denser layers. In fact, about 99% of the total mass of the air is found below about 40 km (25 miles). Commercial airliners fly considerably below this height at roughly 30,000 to 50,000 ft (9 to 15 km), with the supersonic Concorde going to abo作者: BYRE 時(shí)間: 2025-3-28 16:44
Reliable Confidence Predictions Using Conformal Prediction live births. Thus for some women at least, childbirth is now easier and safer than it has ever been in human history. However for others it remains extremely dangerous. More than half a million still die from pregnancy-related causes each year, almost all of them in the third world, where 86 per ce作者: 下級(jí) 時(shí)間: 2025-3-28 20:23
A Simple Unlearning Framework for Online Learning Under Concept Driftsthor participated, and critical legal and political reflectiThis book provides a discussion of some of the most pressing challenges facing EU integration: political and economic governance, constitutional status and citizenship. It does so by discussing the work of one of the most original Portugues作者: 極小量 時(shí)間: 2025-3-28 23:44 作者: DIKE 時(shí)間: 2025-3-29 05:48
Cross-View Feature Hashing for Image Retrievales this mean, then, in the context of collaborative research projects involving teams of researchers? How do the contexts, dynamics and interests of research partners shape, complement or undermine the interests and reflections of autoethnographic researchers working towards collective goals? To ref作者: Factorable 時(shí)間: 2025-3-29 08:48 作者: GUILT 時(shí)間: 2025-3-29 11:57
Giacomo Vivanti,Melanie Pellecchiathe specifically selected sampling rate for each data set. The experiments are conducted on 26 data sets from the UCI data repository, in which the proposed method in comparison with the existing counterparts is evaluated by three evaluation metrics. Experiments show that, combined with bagging, the作者: 紅潤 時(shí)間: 2025-3-29 17:18 作者: 表示向前 時(shí)間: 2025-3-29 21:39 作者: Outwit 時(shí)間: 2025-3-30 01:38
Jignesh Patel MD, PhD,Jon Kobashigawa MDliding window that selects some data flexibly for different kinds of concept drifts. We design concrete approaches from the framework based on three popular online learning algorithms. Empirical results show that the framework consistently improves those algorithms on ten synthetic data sets and two作者: START 時(shí)間: 2025-3-30 07:59
W. Kim Halford,Jemima Petch,Debra Creedyo design a scalable approach to cluster large graphs with millions of nodes. We propose the approach . (.lustering .raphs with .ultiple .nnotations) to address these challenges. . is able to combine the crowd’s consensus opinions in an unbiased way, and conducts an effective clustering with low time作者: 果仁 時(shí)間: 2025-3-30 11:49
W. Kim Halford,Jemima Petch,Debra CreedyESP-NB and ESP-TAN, respectively, for early stage event prediction by modifying the posterior probability of event occurrence using different extrapolations that are based on Weibull and Lognormal distributions. The proposed framework is evaluated using a wide range of synthetic and real-world bench作者: 亞當(dāng)心理陰影 時(shí)間: 2025-3-30 16:16
https://doi.org/10.1007/978-1-4614-5447-2ogeneity of daily treatments and performs toxicity prediction at different prediction points. Our method was evaluated on a real-word dataset of more than 2000 cancer patients and had achieved a better prediction accuracy in terms of AUC than the state-of-art baselines.作者: tenuous 時(shí)間: 2025-3-30 17:55 作者: 裂縫 時(shí)間: 2025-3-31 00:16
Ryan Budwany,Tony K. George,Timothy R. Deerhe Hamming space; and (2) the binary codes for multiple views of the same sample should be similar in the shared Hamming space. We apply CVFH to cross-view image retrieval. The experimental results show that CVFH can outperform the Canonical Component Analysis (CCA) based cross-view method.作者: Type-1-Diabetes 時(shí)間: 2025-3-31 04:53
established by recent research, he inspires readers to reflect for themselves on the very question of who we are—a key consideration for anyone interested in society, government, schools, health, activism, culture and diversity, or even just survival..978-3-030-50381-9978-3-030-50382-6作者: 雄偉 時(shí)間: 2025-3-31 06:46 作者: 精確 時(shí)間: 2025-3-31 09:39
