標(biāo)題: Titlebook: Robust Representation for Data Analytics; Models and Applicati Sheng Li,Yun Fu Book 2017 Springer International Publishing AG, part of Spri [打印本頁(yè)] 作者: SCOWL 時(shí)間: 2025-3-21 18:07
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書(shū)目名稱Robust Representation for Data Analytics被引頻次
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書(shū)目名稱Robust Representation for Data Analytics讀者反饋
書(shū)目名稱Robust Representation for Data Analytics讀者反饋學(xué)科排名
作者: 共同確定為確 時(shí)間: 2025-3-21 23:18 作者: 指令 時(shí)間: 2025-3-22 01:49 作者: cochlea 時(shí)間: 2025-3-22 07:50
https://doi.org/10.1007/978-3-319-60176-2Robust Representations; Graph Construction; Subspace Learning; Outlier Detection; Multi-view Learning作者: 禁令 時(shí)間: 2025-3-22 10:07 作者: 歡笑 時(shí)間: 2025-3-22 13:39
Robust Representation for Data Analytics978-3-319-60176-2Series ISSN 1610-3947 Series E-ISSN 2197-8441 作者: 衍生 時(shí)間: 2025-3-22 18:34 作者: Exploit 時(shí)間: 2025-3-23 00:20 作者: Cantankerous 時(shí)間: 2025-3-23 03:54 作者: 貪婪的人 時(shí)間: 2025-3-23 05:59 作者: 向下五度才偏 時(shí)間: 2025-3-23 13:32 作者: SEED 時(shí)間: 2025-3-23 15:14 作者: ANTI 時(shí)間: 2025-3-23 21:30
Sheng Li,Yun Fuie heutigen Friedensbewegungen stammen insbesondere aus der zweiten H?lfte des 19. und aus der ersten H?lfte des 20. Jahrhunderts. Von Anfang an mussten sie sich mit den Ideologien zur Rechtfertigung von Kriegen auseinandersetzen. Dies gilt im Grunde bis heute.作者: 啞劇 時(shí)間: 2025-3-24 01:48 作者: 苦惱 時(shí)間: 2025-3-24 05:08
Sheng Li,Yun Fucht scharf zwischen Dichtern und Philosophen und l??t seinen Protagoras erkl?ren, da? die alten Dichter in Wirklichkeit Sophisten gewesen seien, ihre Ansichten aber aus Angst, Feindschaft zu wecken, getarnt h?tten (. 316d-e). Soweit wir wissen, war Aristoteles der erste Autor, der terminologisch zwi作者: 柔聲地說(shuō) 時(shí)間: 2025-3-24 09:26 作者: 假裝是你 時(shí)間: 2025-3-24 13:27 作者: Defraud 時(shí)間: 2025-3-24 16:51 作者: BRINK 時(shí)間: 2025-3-24 19:15 作者: Common-Migraine 時(shí)間: 2025-3-25 01:32
Robust Multi-view Subspace Learnings m.t.s.?from different views onto a shared latent subspace. Second, MDBP incorporates discriminative information by minimizing the within-class separability and maximizing the between-class separability of m.t.s.?in the shared latent subspace. Moreover, a Laplacian regularization term is designed t作者: 傳授知識(shí) 時(shí)間: 2025-3-25 03:37
Robust Dictionary Learningy and target domains, the proposed approach learns expressive codings for the samples in the target domain. Since many types of visual data have been proven to contain subspace structures, a low-rank constraint is introduced into the coding objective to better characterize the structure of the given作者: invulnerable 時(shí)間: 2025-3-25 10:44 作者: Jejune 時(shí)間: 2025-3-25 12:03
Robust Representations for Response Predictionctorization (DCMF) to address this problem. Our model considers temporal dynamics of post-click conversions and also takes advantages of the side information of users, advertisements, and items. An efficient optimization algorithm based on stochastic gradient descent is presented in the chapter. We 作者: ARIA 時(shí)間: 2025-3-25 18:14
Robust Representations for Outlier Detectionrmulate a regularized rank-minimization problem which is solved by an efficient optimization algorithm. Second, the outliers are identified through an outlier score estimation procedure. Different from the existing multi-view outlier detection methods, MLRA is able to detect two different types of o作者: 放縱 時(shí)間: 2025-3-25 23:00 作者: aptitude 時(shí)間: 2025-3-26 00:56 作者: 表兩個(gè) 時(shí)間: 2025-3-26 08:10
Sheng Li,Yun Fuerende und Lehrende der Friedens- und Konfliktforschung.Politische Akteurinnen und Akteure sowie in der Friedenspraxis T?tige.Die allgemein an friedenspolitischen Themen interessierte ?ffentlichkeit.Die Herausgeber.Prof. Dr. Hans J. Gie?mann.?ist Direktor der Berghof Foundation in Berlin..Dr. Bernhard R978-3-658-23644-1作者: 分散 時(shí)間: 2025-3-26 09:31
1610-3947 principles with real-world practiceThis book introduces the concepts and models of robust representation learning, and provides a set of solutions to deal with real-world data analytics tasks, such as clustering, classification, time series modeling, outlier detection, collaborative filtering, commu作者: 結(jié)合 時(shí)間: 2025-3-26 16:34
Introduction,easurements for different purposes. Several real-world scenarios are: In ., the consumer devices such as Kinect could capture and process visual information and motion data in real time; In ., people refine, upload, and comment on images or videos that are captured by mobile devices with high-defini作者: 帶來(lái) 時(shí)間: 2025-3-26 20:23 作者: 膝蓋 時(shí)間: 2025-3-26 23:41
Robust Subspace Learningperformance of most existing subspace learning methods would be limited. Recent advances in low-rank modeling provide effective solutions for removing noise or outliers contained in sample sets, which motivates us to take advantages of low-rank constraints in order to exploit robust and discriminati作者: 蕨類 時(shí)間: 2025-3-27 03:28 作者: fatty-acids 時(shí)間: 2025-3-27 08:43
Robust Dictionary Learningg methods have been developed to tackle this challenge by utilizing auxiliary samples from the same domain or from a different domain, respectively. Self-taught learning, which is a special type of transfer learning, has fewer restrictions on the choice of auxiliary data. It has shown promising perf作者: demote 時(shí)間: 2025-3-27 11:02
Robust Representations for Collaborative Filteringplays the most important role in collaborative filtering. Traditional CF methods based upon matrix factorization techniques learn the latent factors from the user-item ratings and suffer from the cold start problem as well as the sparsity problem. Some improved CF methods enrich the priors on the la作者: 瑣碎 時(shí)間: 2025-3-27 15:05
Robust Representations for Response Predictiono key performance indicators are the click-through rates (CTR) of the ads and conversion rates (CVR) on the advertisers website. Existing approaches for conversion prediction and for click prediction usually look at the two problems in isolation. However there is considerable benefit in jointly solv作者: 紋章 時(shí)間: 2025-3-27 20:21 作者: irritation 時(shí)間: 2025-3-27 23:30 作者: 光滑 時(shí)間: 2025-3-28 03:55
Book 2017arning, semi-supervised learning, multi-view learning, transfer learning, and deep learning.?.Robust Representations for Data Analytics.?covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision..作者: Hla461 時(shí)間: 2025-3-28 06:44
Book 2017 tasks, such as clustering, classification, time series modeling, outlier detection, collaborative filtering, community detection, etc. Three types of robust feature representations are developed, which extend the understanding of graph, subspace, and dictionary..Leveraging the theory of low-rank an作者: 禮節(jié) 時(shí)間: 2025-3-28 12:01
die Klagen über die damit verbundenen Anforderungen und Belastungen in unterschiedlichen Sektoren des modernen Alltags stark zugenommen. Auf der anderen Seite hat Beschleunigung als integraler Bestandteil eines weit mehr als hundertj?hrigen Modernisierungsprozesses der Gesellschaft paradoxer Weise e作者: 使乳化 時(shí)間: 2025-3-28 16:08
Sheng Li,Yun Fuhern und Lexika verfolgt, genie?t der Krieg im Gegensatz zum Frieden deutlich mehr Aufmerksamkeit als sein Gegenpart – 2.230 Mio. Eintr?ge bei Google (30.06.2018, 01.15) für ?war“ gegen 890 Mio. für ?peace“ bzw. 62 Mio. für ?Krieg“ gegen 37,4 Mio. für ?Frieden“; 32 Ausdruckseiten für ?war“ gegen 3,5作者: GRE 時(shí)間: 2025-3-28 22:44 作者: aristocracy 時(shí)間: 2025-3-29 02:36 作者: Ptsd429 時(shí)間: 2025-3-29 05:48
