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Robust low dimensional structure learning for big data and its applications

Robust low dimensional structure learning for big data and its applications

Robust low dimensional structure learning for big data and its applications

... learning algorithms for processing big realistic data 1.2 Thesis Focus and Main Contributions In this thesis, we focus on robust and efficient low- dimensional structure learning for big data analysis ... process the data in a streaming manner and thus are memory and computationally efficient for analyzing big data Third, we devise two low- dimensional learning algorithms for visual data and solve ... efficiency for handling large-scale data Second, we propose two online learning methods, ORPCA and online RPCA, to further enhance the scalability for robustly learning the low- dimensional structure...
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Workload model for video decoding and its applications

Workload model for video decoding and its applications

... derived from the decoding workload, we thus focus on the model between decoding workload and video quality and its relevant applications in this thesis The study of the decoding workload model is important ... implementations and target platforms We also propose two relevant video applications: the decoding workload scalable transcoder and the decoding workload scalable encoder Based on the decoding workload model, ... Objective Video Quality Measure 19 Chapter3: Decoding Workload Model 23 3.1 Video Decoding Procedure 23 3.2 Decoding Workload Model and Analysis 24 3.2.1 VLD, IQ and...
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Robust learning with low dimensional structure   theory,algorithms and applications

Robust learning with low dimensional structure theory,algorithms and applications

... only a good approximation, learning the parameters of a given structure becomes a much more difficult task In this thesis, we study the robust learning of low- dimensional structures when there are ... indeed obey certain low- dimensional structures, such as sparsity and low- rank, the high dimensionality can result in desirable data redundancy which makes it possible to provably and exactly recover ... developing methodology in the robust learning of low- dimensional structures We contribute to the field by providing both theoretical analysis and practically working algorithms to robustly learn the parameterization...
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Robust learning with low dimensional structure   theory,algorithms and applications

Robust learning with low dimensional structure theory,algorithms and applications

... only a good approximation, learning the parameters of a given structure becomes a much more difficult task In this thesis, we study the robust learning of low- dimensional structures when there are ... indeed obey certain low- dimensional structures, such as sparsity and low- rank, the high dimensionality can result in desirable data redundancy which makes it possible to provably and exactly recover ... developing methodology in the robust learning of low- dimensional structures We contribute to the field by providing both theoretical analysis and practically working algorithms to robustly learn the parameterization...
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Báo cáo hóa học:

Báo cáo hóa học: " Low Complexity Turbo Equalization for High Data Rate Wireless Communications" doc

... approximate implementation offers very good performance at linear complexity Thus, the latter low complexity equalization algorithm is suitable for high data- rate wireless communication systems with limited ... [18]) Figures and demonstrate the performance of various receivers performing turbo equalization for the aforementioned channels The cases shown correspond to (a) conventional equalization and decoding ... which has linear complexity Simulation results have shown that the proposed algorithm exhibits very good performance characteristics that make it suitable for high data rate wireless communications...
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Machine learning based classification system for overlapping data and irregular repetititve signals

Machine learning based classification system for overlapping data and irregular repetititve signals

... 0.000001 for normal match tracking and ε = −0.01 for MT- The choice parameter was set to α = 0.000001 2.4.1 Results for UCI Datasets Results for Yeast Database The yeast database from Machine Learning ... simulated data 33 2.4.2 Results for Synthetic Data Results for Synthetic data without noise This data is simulated and has a size of 49500 There are 165 classes and the data has attributes before ... for large datasets with higher amounts of noise Expert knowledge on the signals and their sources is available for the signal sorting module in the form of a database The information in the database...
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Báo cáo khoa học:

Báo cáo khoa học: "Hierarchical Sequential Learning for Extracting Opinions and their Attributes" ppt

... Inference for Linguistic Annotation Pipelines In EMNLP M Hu and B Liu 2004 Mining and Summarizing Customer Reviews In KDD S Kim and E Hovy 2004 Determining the sentiment of opinions In COLING S Kim and ... prior of 1.0 for regularization We use 135 documents for development, and test on a different set of 400 documents using 10-fold crossvalidation We investigate three options for jointly extracting ... and determine their attributes — polarity and intensity Empirical results indicate that the simple joint sequential tagging approach even without exploiting the hierarchy brings a better performance...
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Báo cáo hóa học:

Báo cáo hóa học: " Research Article Robust Adaptive Modified Newton Algorithm for Generalized Eigendecomposition and Its Application" pdf

... 3, the generalized eigendecomposition problem is reinterpreted as a nonlinear optimization problem, and a robust adaptive modified Newton algorithm is developed to estimate the principal generalized ... global minimum and no other local minima, and then apply an appropriate Hessian matrix approximation to derive an adaptive modified Newton algorithm The resulting algorithm is numerically robust no ... eigenvector corresponding to the maximum generalized eigenvalue of the matrix pencil (Rs , Ru ), that is, (19) ROBUST ADAPTIVE MODIFIED NEWTON ALGORITHM FOR GENERALIZED EIGENDECOMPOSITION To solve a class...
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An efficient and robust algorithm for incompressible flow and its application in heat transfer enhancement

An efficient and robust algorithm for incompressible flow and its application in heat transfer enhancement

... AN EFFICIENT AND ROBUST ALGORITHM FOR INCOMPRESSIBLE FLOW AND ITS APPLICATION IN HEAT TRANSFER ENHANCEMENT CHENG YONGPAN (B Eng., M Eng., Xian Jiaotong University, China) A THESIS SUBMITTED FOR ... airside convective heat transfer coefficient for the wet and frosted surfaces in heat exchangers with simultaneous heat and mass transfer 1.2.2.2 Wavy fin -and- tube heat exchanger Jang and Chen (1997) ... performance for plain fin -and- tube heat exchanger in wet conditions Niederer (1986) performed experiments to investigate the frosting and defrosting effects on the heat transfer in heat exchangers...
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Escrow techniques for mobile sales and inventory applications  doc

Escrow techniques for mobile sales and inventory applications  doc

... design and analysis of algorithms, architectures and protocols for mobile computing and communications, including techniques for locating mobile users, mobile database access, and mobile sales applications ... site-transaction escrow method, that is suitable for sales and inventory applications supporting both stationary and mobile users We provided a formal model for reasoning about site-transaction escrow, and ... Krishnakumar, R Jain / Escrow techniques for mobile applications that the site-transaction escrow technique is more suitable than traditional database locking schemes for the mobile sales and inventory application...
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Báo cáo khoa học:

Báo cáo khoa học: "Jointly optimizing a two-step conditional random field model for machine transliteration and its fast decoding algorithm" pdf

... Dong Yang, Paul Dixon, Yi-Cheng Pan, Tasuku Oonishi, Masanobu Nakamura and Sadaoki Furui 2009 Combining a Two-step Conditional Random Field Model and a Joint Source Channel Model for Machine Transliteration, ... Lafferty, Andrew McCallum, and Fernando Pereira 2001 Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data., Proceedings of International Conference on Machine ... Kumar Naskar and Sivaji Bandyopadhyay 2006 A modified joint source-channel model for transliteration, Proceedings of the COLING/ACL, pages 191-198 Bo-June Hsu and James Glass 2008 Iterative Language...
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Đề tài

Đề tài " Sum rules for Jacobi matrices and their applications to spectral theory " pdf

... 253–321 Sum rules for Jacobi matrices and their applications to spectral theory By Rowan Killip and Barry Simon* Abstract We discuss the proof of and systematic application of Case’s sum rules for Jacobi ... book [58] noted this consequence before Favard’s work 255 SUM RULES FOR JACOBI MATRICES Given the one -to- one correspondence between µ’s and J’s, it is natural to ask how properties of one are ... We realized that the key to SUM RULES FOR JACOBI MATRICES 257 Denisov’s result was a sum rule, not the particular method he used to construct his potentials We decided to focus first on the discrete...
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Visual Design for Web Sites  and Web Applications

Visual Design for Web Sites and Web Applications

... phenomenon Use Lucida Grande for Mac, and Lucida Sans Unicode for PC Designed by: Charles Bigelow & Chris Holmes (1985) PC: 96.14% Mac 94.46% web typography Palatino is underused and underappreciated, ... pages Over the past years, Web site and Web application designers have shown an increased interest in the technique as well why bother with a grid? consistency framework for many pages ease of use ... non -Web safe fonts? pixel renderings [image file] sIFR [flash] cufon [javascript] typekit [javascript] web typography: type tech web typography: free font resource - theleagueofmovabletype.com web...
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