標(biāo)題: Titlebook: Low-Rank and Sparse Modeling for Visual Analysis; Yun Fu Book 2014 Springer International Publishing Switzerland 2014 Compressive Sensing. [打印本頁] 作者: 我贊成 時間: 2025-3-21 19:39
書目名稱Low-Rank and Sparse Modeling for Visual Analysis影響因子(影響力)
書目名稱Low-Rank and Sparse Modeling for Visual Analysis影響因子(影響力)學(xué)科排名
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書目名稱Low-Rank and Sparse Modeling for Visual Analysis網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Low-Rank and Sparse Modeling for Visual Analysis被引頻次
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書目名稱Low-Rank and Sparse Modeling for Visual Analysis讀者反饋
書目名稱Low-Rank and Sparse Modeling for Visual Analysis讀者反饋學(xué)科排名
作者: Maximize 時間: 2025-3-21 20:19
Latent Low-Rank Representation,x itself is chosen as the dictionary, resulting in a powerful method that is useful for both subspace clustering and error correction. However, such a strategy may depress the performance of LRR, especially when the observations are insufficient and/or grossly corrupted. In this chapter we therefore作者: NEX 時間: 2025-3-22 02:57
Scalable Low-Rank Representation,under large-scale settings. In this chapter we therefore address the problem of solving nuclear norm regularized optimization problems (NNROPs), which contain a category of problems including LRR. Based on the fact that the optimal solution matrix to an NNROP is often low-rank, we revisit the classi作者: 隼鷹 時間: 2025-3-22 05:53 作者: Density 時間: 2025-3-22 09:13
Low-Rank Transfer Learning,beled data for the new task may save considerable labeling efforts. However, data in the auxiliary databases are often obtained under conditions that differ from those in the new task. Transfer learning provides techniques for transferring learned knowledge from a . domain?to a . domain by mitigatin作者: GNAW 時間: 2025-3-22 15:51
Sparse Manifold Subspace Learning,ods considering global data structure e.g., PCA, LDA, SMSL aims at preserving the local neighborhood structure on the data manifold and provides a more accurate data representation via locality sparse coding. In addition, it removes the common concerns of many local structure based subspace learning作者: 菊花 時間: 2025-3-22 20:06
Low Rank Tensor Manifold Learning,s fact, two interesting questions naturally arise: How does the human brain represent these tensor perceptions in a “manifold” way, and how can they be recognized on the “manifold”? In this chapter, we present a supervised model to learn the intrinsic structure of the tensors embedded in a high dime作者: 外觀 時間: 2025-3-22 23:49 作者: Crohns-disease 時間: 2025-3-23 03:46
Low-Rank Outlier Detection,tion (SVDD) model. Different from the traditional SVDD, our approach learns multiple hyper-spheres to fit the normal data. The low-rank constraint helps us group the complicated dataset into several clusters dynamically. We present both primal and dual solutions to solve this problem, and provide th作者: septicemia 時間: 2025-3-23 06:30 作者: Recessive 時間: 2025-3-23 10:44 作者: 遠(yuǎn)地點(diǎn) 時間: 2025-3-23 17:49
Ivan Markovsky,Konstantin Usevichren and their families.Challenges the view that refugees areThis book examines the agreements and discrepancies between public understanding and assumptions about refugees, and the actual beliefs and practices among the refugees themselves in a time of increasing mobility fuelled by what many call ‘作者: Decrepit 時間: 2025-3-23 20:21 作者: 我不死扛 時間: 2025-3-24 01:07 作者: 吸氣 時間: 2025-3-24 03:34
Sheng Li,Liangyue Li,Yun Futwentieth century. Literature from the former colonies often provides a clearer picture of various manifestations of such power dynamics in local practices. The cultural or economic exchanges involved in the process are dismantled through local mini-narratives which challenge and reconceptualise the作者: 苦惱 時間: 2025-3-24 09:06 作者: Bone-Scan 時間: 2025-3-24 14:20 作者: modest 時間: 2025-3-24 16:33 作者: 忙碌 時間: 2025-3-24 21:21
Yang Cong,Ji Liu,Junsong Yuan,Jiebo Luotadrama. If we look beyond the social, political, and economic issues that Shaw explored in these two plays, we discover that the stories of the two “Shavian sisters”— Barbara Undershaft and Eliza Doolittle—are deeply concerned with performance and what Jacques Derrida calls “the problem of language作者: Cubicle 時間: 2025-3-25 00:24 作者: 貿(mào)易 時間: 2025-3-25 06:15 作者: triptans 時間: 2025-3-25 09:11
Guangcan Liu,Shuicheng Yaninterplay of signs, that discourses gain identity by their relational difference to others and finally, that signs are fixed to a particular application only through dominant discourses, are used to frame this debate. Following the theoretical analysis, an analysis of John Key’s speeches applying La作者: giggle 時間: 2025-3-25 15:38 作者: 樹木中 時間: 2025-3-25 16:28 作者: 合法 時間: 2025-3-25 22:06 作者: Abduct 時間: 2025-3-26 02:43
Yang Cong,Ji Liu,Junsong Yuan,Jiebo Luodershaft’s Salvation Army shelter? Is English losing its precision and purity?Meanwhile, in the background, Shaw keeps reminding us that language and theatre are always present in our everyday lives—sometimes serving as stabilizing forces, and sometimes working to undo them..作者: glisten 時間: 2025-3-26 06:26 作者: biosphere 時間: 2025-3-26 12:03
Scalable Low-Rank Representation, that suboptimal solution can be found by the augmented Lagrange alternating direction method. For the robust PCA (RPCA) [.] problem, which is a typical example of NNROPs, theoretical results verify sub-optimality of the solution produced by our algorithm. For the general NNROPs, we empirically show作者: 宴會 時間: 2025-3-26 15:02 作者: GOUGE 時間: 2025-3-26 18:37
Low-Rank Transfer Learning,of the source domain are used to reconstruct the data in the target domain. Second, the discriminative power of the source domain is naturally passed on to the target domain. Third, noisy information will be filtered out in the knowledge transfer. Extensive experiments on synthetic data, and importa作者: 正論 時間: 2025-3-26 21:18 作者: enflame 時間: 2025-3-27 04:30
among transnational and diasporic communities, minoritized or marginalized groups for researchers in these fields as well as practitioners and resettlement agencies working with refugee populations.978-1-349-95458-2978-1-137-58756-5Series ISSN 2947-7506 Series E-ISSN 2947-7514 作者: 有幫助 時間: 2025-3-27 06:49
Ivan Markovsky,Konstantin Usevich among transnational and diasporic communities, minoritized or marginalized groups for researchers in these fields as well as practitioners and resettlement agencies working with refugee populations.978-1-349-95458-2978-1-137-58756-5Series ISSN 2947-7506 Series E-ISSN 2947-7514 作者: 獨(dú)行者 時間: 2025-3-27 11:07
Ming Shao,Mingbo Ma,Yun Fuimited myself in various ways. In the first place, I con- centrate only on those matters which are of particular interest to me, namely theories of meaning and 978-94-010-2228-6978-94-010-2226-2Series ISSN 0082-111X 作者: CHIDE 時間: 2025-3-27 16:43
Guoqiang Zhong,Mohamed Cherietimited myself in various ways. In the first place, I con- centrate only on those matters which are of particular interest to me, namely theories of meaning and 978-94-010-2228-6978-94-010-2226-2Series ISSN 0082-111X 作者: 粗野 時間: 2025-3-27 21:10 作者: stress-response 時間: 2025-3-27 22:22
Low-Rank Outlier Detection, time and memory space could be substantially reduced. The performance of our approach, along with other related methods, was evaluated using three image databases. Results show our approach outperforms other methods in most scenarios.作者: 喚起 時間: 2025-3-28 03:07 作者: Constant 時間: 2025-3-28 08:00 作者: 苦笑 時間: 2025-3-28 11:10
Sparse Manifold Subspace Learning,y sparse coding, and sparse eigen-decomposition in graph embedding yield a noise-tolerant framework. Finally, SMSL is learned in an inductive fashion, and therefore easily extended to different tests. We exhibit experimental results on several databases and demonstrate the effectiveness of the proposed method.作者: Anemia 時間: 2025-3-28 16:28 作者: 同步左右 時間: 2025-3-28 20:35
Low-Rank and Sparse Multi-task Learning,ed optimization algorithms to efficiently find their globally optimal solutions. We also conduct theoretical analysis on our MTL approaches, i.e., deriving performance bounds to evaluate how well the integration of low-rank and sparse representations can estimate multiple related tasks.作者: Gratulate 時間: 2025-3-29 00:36
d practice of sparse and low-rank analysis.Contributions froThis book provides a view of low-rank and sparse computing, especially approximation, recovery, representation, scaling, coding, embedding and learning among unconstrained visual data. The book includes chapters covering multiple emerging t作者: 鉆孔 時間: 2025-3-29 05:53 作者: Spartan 時間: 2025-3-29 10:23
Yun FuCovers the most state-of-the-art topics of sparse and low-rank modeling.Examines the theory of sparse and low-rank analysis to the real-world practice of sparse and low-rank analysis.Contributions fro作者: poliosis 時間: 2025-3-29 14:20 作者: Aggregate 時間: 2025-3-29 17:28
https://doi.org/10.1007/978-3-319-12000-3Compressive Sensing; Computer Vision; Dimensionality Reduction; Low-Rank Approximation; Low-Rank Recover
