Machine learning methods for pattern analysis and clustering
Machine learning methods for pattern analysis and clustering
... 134 Summary and Future Work Bibliography Machine Learning Methods for Pattern Analysis 137 A Ji He Machine Learning Methods for Pattern Analysis and Clustering Ji He, 2004 National ... 4.3 Machine Learning Methods for Pattern Analysis Ji He Machine Learning Methods for Pattern Analysis and Clustering Ji He, 2004 National University of Singapore CHAPTER INTRODUCTION 1.1 Pattern ... summarizes the thesis contents and proposes future work Machine Learning Methods for Pattern Analysis Ji He Machine Learning Methods for Pattern Analysis and Clustering Ji He, 2004 National...
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kernel methods for pattern analysis
... of kernels: K = ∑ λ i K i i (more general classes are possible) Kernels form a cone www.support-vector.net/nello.html Last part of the talk… All information needed by kernel- methods is in the kernel ... and haussler; bill noble; …) Kernels for trees, graphs, general structures Semantic Kernels for text, etc etc Kernels based on generative models (see phylogenetic kernels, by J.P Vert) www.support-vector.net/nello.html ... sequences, can be used to define/learn formal languages (see next) … (a task of syntactical pattern analysis) www.support-vector.net/nello.html A simple kernel for sequences Consider a space with...
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Novel methods for quantitative analysis and evaluation of effects of chronic exposure to microcystins by capillary electrophoresis and metabolomic studies
... NOVEL METHODS FOR QUANTITATIVE ANALYSIS AND EVALUATION OF EFFECTS OF CHRONIC EXPOSURE TO MICROCYSTINS BY CAPILLARY ELECTROPHORESIS AND METABOLOMIC STUDIES GRACE BIRUNGI ... –DEVELOPMENT OF METHODS OF ANALYSIS 48 2.0 Development of CE Methods for the Determination of Cyanotoxins 48 2.1 CZE and MEKC Methods for Determination of Microcystins LR, RR, YR and Nodularin ... describes capillary electrophoresis (CE) methods for separation and quantification of cyanotoxins in water; and metabolomic and “metabonomic” approaches for investigation of the effect of exposure of...
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support vector and kernel methods for pattern recognition
... K(m,m) www .support- vector. net The Kernel Matrix ! The central structure in kernel machines ! Information ‘bottleneck’: contains all necessary information for the learning algorithm ! Fuses information ... (gaussian kernels) www .support- vector. net 16 Making kernels !From kernels (see closure properties): can obtain complex kernels by combining simpler ones according to specific rules www .support- vector. net ... z) = kernel K1(x, x)K1(z, z) www .support- vector. net Making kernels !From features: start from the features, then obtain the kernel Example: the polynomial kernel, the string kernel, … www .support- vector. net...
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Báo cáo sinh học: "Analysis of a simulated microarray dataset: Comparison of methods for data normalisation and detection of differential expression (Open Access publication)" pps
... to a simulated data set produced by the SIMAGE package [1] The data set is a simple comparison of two biological states on ten arrays, with dye-balance A number of data quality, normalisation and ... ensured that the variance in M values was consistent across arrays Data normalisation of gene expression analysis 675 Table II Summary of the 12 methods used for analysing the simulated data “Analysis ... based on traditional statistics performed less well than those methods Data normalisation of gene expression analysis 677 Table III Summary of the results of the analysis of the simulated data...
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Development of meshfree methods for three dimensional and adaptive analysis of solid mechanics problems
... DEVELOPMENT OF MESHFREE METHODS FOR THREE- DIMENSIONAL AND ADAPTIVE ANALYSES OF SOLID MECHANICS PROBLEMS ZHANG GUIYONG (B.Eng., DUT, CHINA) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY ... (LC-PIM) for both 2D and 3D problems, and to apply it to adaptive analysis The RPIM was originally proposed for 2D problems and applied for different types of problems The first contribution of the ... techniques and extended our minds in the quest for more effective and robust computational methods This thesis focuses on the development of new meshfree methods and the application of these methods for...
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Development and interpretation of machine learning models for drug discovery
... concerned with the development and interpretation of machine learning models for drug discovery To this end, it describes the design and application of computational models for specialized use ... focus of this thesis is the development and interpretation of machine learning models for pharmaceutical tasks In drug discovery, project teams usually consist of experts from a variety of disciplines, ... some basic concepts of in silico modeling for drug discovery Concepts Machine learning models for drug discovery mostly try to model the structure-activity relationship of ligand-target interactions...
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Tài liệu Báo cáo khoa học: "Generalization Methods for In-Domain and Cross-Domain Opinion Holder Extraction" pdf
... (Wiebe et al., 2005) We adhere to the definition of opinion holders from previous work (Wiegand and Klakow, 2010; Wiegand and Klakow, 2011a; Wiegand and Klakow, 2011b), i.e every source of a private ... opinion holders and therefore can be seen as a proxy (4) I always supported this idea holder: agent (5) This worries me holder: patient (6) He disappointed me holder: patient We follow Wiegand and Klakow ... unlabeled corpus (§2) 3.3.2 Extension for Opinion Holders in Patient Position The downside of using prototypical opinion holders as a proxy for opinion holders is that it 327 anguish∗ , astonish,...
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Báo cáo khoa học: "Experiments in Graph-based Semi-Supervised Learning Methods for Class-Instance Acquisition" docx
... Workshop on Machine Learning for Web Search A Carlson, J Betteridge, R.C Wang, E.R Hruschka Jr, and T.M Mitchell 2010 Coupled Semi-Supervised Learning for Information Extraction In Proceedings of the ... reproducible research in this area Topics for future work include the incorporation of other kinds of semantic constraint for improved class-instance acquisition, further investigation into per-node ... that class-instance acquisition performance can be significantly improved by incorporating additional semantic constraints in the class-instance acquisition process, which for the experiments in...
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Báo cáo khoa học: "cdec: A Decoder, Alignment, and Learning Framework for Finite-State and Context-Free Translation Models" potx
... statistical machine translation In Proc of ACL, pages 160–167 K Papineni, S Roukos, T Ward, and W.-J Zhu 2002 BLEU: a method for automatic evaluation of machine translation In Proc of ACL, pages ... Chiang, K Knight, and W Wang 2009 11,001 new features for statistical machine translation In Proc of NAACL, pages 218–226 M Riedmiller and H Braun 1993 A direct adaptive method for faster backpropagation ... semiring framework (§5) 2.1 Translation hypergraphs Recent research has proposed a unified representation for the various translation and tagging formalisms that is based on weighted logic programming...
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Báo cáo khoa học: "A Re-examination of Machine Learning Approaches for Sentence-Level MT Evaluation" ppt
... on one group of MT systems evaluate the translation qualities of new systems? In this paper, we argue for the viability of a regression-based framework for sentence-level MTevaluation Through ... and Chris Brockett 2001 A machine learning approach to the automatic evaluation of machine translation In Proceedings of the 39th Annual Meeting of the Association for Computational Linguistics, ... Koehn 2006 Re-evaluating the role of BLEU in machine translation research In The Proceedings of the Thirteenth Conference of the European Chapter of the Association for Computational Linguistics...
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Báo cáo khoa học: "Using Emoticons to reduce Dependency in Machine Learning Techniques for Sentiment Classification" pot
... Dependencies in Sentiment Classification Experimental Setup In this section, we describe experiments we have carried out to determine the in uence of domain, topic and time on machine learning based sentiment ... negative sentiment (selected by independent trained annotators), each containing 100 stories We trained a model on a dataset relating to one topic and tested that model using the other topics Figure ... Domain dependency in sentiment classification Figure 1: Topic dependency in sentiment classification Ac- Accuracies, in percent Best performance on a test set for each model is highlighted in bold...
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Báo cáo khoa học: "A Seed-driven Bottom-up Machine Learning Framework for Extracting Relations of Various Complexity" pdf
... '98), March 1998 M E Califf and R J Mooney 2004 Bottom-Up Relational Learning of Pattern Matching Rules for Information Extraction Journal of Machine Learning Research, MIT Press W Drozdzynski, H.-U.Krieger, ... we use PI for Person_In, PO for Person_Out, POS for Position and ORG for Organisation In our experiments, we attempt to investigate the influence of the size of the seed and the size of the test ... or Person_Out The ambitious goal of our approach is to provide a general framework for the extraction of relations and events with various complexity Within this framework, the IE system learns...
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