machine learning for profiling network traffic
Tài liệu Báo cáo khoa học: "Machine Learning for Coreference Resolution: From Local Classification to Global Ranking" ppt
... adopting the standard machine learning approach, outperforming them by as much as 4–7% on the three data sets for one of the performance metrics 3.1 Selecting Coreference Systems A learning- based coreference ... sample selection and error-driven pruning for machine learning of coreference rules In Proc of EMNLP, pages 55–62 V Ng and C Cardie 2002b Improving machine learning approaches to coreference resolution ... the ACL, pages 104–111 J R Quinlan 1993 C4.5: Programs for Machine Learning Morgan Kaufmann W M Soon, H T Ng, and D Lim 2001 A machine learning approach to coreference resolution of noun phrases...
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Machine Learning for Hackers pot
... Preface Machine Learning for Hackers To explain the perspective from which this book was written, it will be helpful to define the terms machine learning and hackers What is machine learning? ... R for Machine Learning Downloading and Installing R IDEs and Text Editors Loading and Installing R Packages R Basics for Machine Learning Further Reading on R 12 ... www.it-ebooks.info Machine Learning for Hackers Drew Conway and John Myles White Beijing • Cambridge • Farnham • Köln • Sebastopol • Tokyo www.it-ebooks.info Machine Learning for Hackers by Drew...
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Studies on machine learning for data analytics in business application
... space model for latent representation learning The major differences are, we adopt Restricted Boltzmann Machine (RBM) for latent representation learning, and additionally, we perform sentiment ... very little work which uses machine learning to address the problem Recently, there is increasing research interest in the application of machine learning methods for business analytics (Abbasi ... intend to fill the gap by proposing a model for estimating daily free app downloads, which complements Garg and Telang (2012) 1.3 MACHINE LEARNING Machine learning is a highly interdisciplinary field...
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Statistical Machine Learning for High Dimensional Data
... References • Statistical Machine Learning Lafferty, Liu and Wasserman (2012) • The Elements of Statistical Learning Hastie, Tibshirani and Friedman (2009) (www-stat.stanford.edu/˜tibs/ElemStatLearn/) ... and Friedman (2009) (www-stat.stanford.edu/˜tibs/ElemStatLearn/) • Pattern Recognition and Machine Learning Bishop (2009) Outline Regression predicting Y from X Structure and Sparsity finding ... with weak assumptions Latent Variable Models making use of hidden variables Introduction • Machine learning is statistics with a focus on prediction, scalability and high dimensional problems...
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Statistical Machine Learning for High Dimensional Data Lecture 2
... ● 16 Example Neighborhood Yahoo Inc (Information Technology): • Amazon.com Inc (Consumer Discretionary) • eBay Inc (Information Technology) • NetApp (Information Technology) 17 Example Neighborhood ... Meinshausen & Buhlmann (2006) for Gaussian case ¨ • Recovering graph structure equivalent to recovering neighborhood structure N (i) for every i ∈ V • Strategy: perform regularized logistic regression ... RSS 0.1894 41 Sparse Coding Mathematical formulation of dictionary learning: G y (i) − X α(i) 2n α,X such that g=1 Xj 2 + λ α(i) ≤1 42 Sparse Coding for Natural Images Original patch Reconstruction...
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Statistical Machine Learning for High Dimensional Data Lecture 3
... then predict: Y(i) = mh,(i) (Xi ) Repeat this for all observations The cross-validation estimate of risk is: R(h) = n n (Yi − Y(i) )2 i=1 Shortcut formula: R(h) = n where Lii = Kh (Xi , Xi )/ ... has dimension p > For example, just use K (x, y) = e− /2 x−y However, this is hard to interpret and is subject to the curse of dimensionality This means that the statistical performance and the ... = M(X ) + λV (X ) a.e., for some V ∈ ∂ |||M|||∗ 41 CRAM Backfitting Algorithm (Penalty 1) Input: Data (Xi , Yi ), regularization parameter λ Iterate until convergence: For each j = 1, , p:...
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Tài liệu Báo cáo khoa học: "Bucking the Trend: Large-Scale Cost-Focused Active Learning for Statistical Machine Translation" docx
... has a preference for covering frequent n-grams before covering infrequent n-grams The VG method is depicted in Figure Figure shows the learning curves for both jHier and jSyntax for VG selection ... vector machine active learning with applications to text classification Journal of Machine Learning Research (JMLR), 2:45–66 David Vickrey, Oscar Kipersztok, and Daphne Koller 2010 An active learning ... estimate the time required for POS annotating Kapoor et al (2007) assign costs for AL based on message length for a voicemail classification task In contrast, we show for SMT that annotation times...
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Tài liệu Báo cáo khoa học: "Trimming CFG Parse Trees for Sentence Compression Using Machine Learning Approaches" pptx
... Zhu 2002 Bleu: a Method for Automatic Evaluation of Machine Translation In Proc of ACL’02, pages 311– 318 J Turner and E Charniak 2005 Supervised and Unsupervised Learning for Sentence Compression ... method to unsupervised learning to overcome the lack of training data However their model also has the same problem McDonald (McDonald, 2006) independently proposed a new machine learning approach ... create a compression forest as Knight and Marcu did We select the tree assigned the highest probability from the forest Features in the maximum entropy model are defined for a tree node and its...
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Báo cáo khoa học: "Using Machine-Learning to Assign Function Labels to Parser Output for Spanish" ppt
... Processing architecture for the machinelearning-based method 4.2 Cast3LB Function Tagging For the task of Cast3LB function tag assignment we experimented with three generic machine learning algorithms: ... TiMBL (Daelemans et al., 2004) for MemoryBased Learning, the MaxEnt Toolkit (Le, 2004) for Maximum Entropy and LIBSVM (Chang and Lin, 2001) for Support Vector Machines For TiMBL we used k nearest ... machine- learning- based method avoids some sparse data problems and allows for more control over Cast3LB tag assignment We have found that the SVM algorithm outperforms the other two machine learning...
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Báo cáo khoa học: "Transductive learning for statistical machine translation" potx
... through semi-supervised learning There are two main reasons for this improvement: Firstly, the selection step provides important feedback for the system The confidence estimation, for example, discards ... relevant for translating the new data are reinforced The probability distribution over the phrase pairs thus gets more focused on the (reliable) parts which are relevant for the test data For an ... Callison-Burch 2002 Co-training for statistical machine translation Master’s thesis, School of Informatics, University of Edinburgh A Fraser and D Marcu 2006 Semi-supervised training for statistical word...
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Báo cáo khoa học: "A Re-examination of Machine Learning Approaches for Sentence-Level MT Evaluation" ppt
... resource for measuring the reliability of automatic evaluation metrics In this paper, we show that they are also informative in developing better metrics MT Evaluation with Machine Learning A ... argument structures for certain syntactic categories Empirical Studies In these studies, the learning models used for both classification and regression are support vector machines (SVM) with ... many criteria Machine learning affords a unified framework to compose these criteria into a single metric In this paper, we have demonstrated the viability of a regression approach to learning the...
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Natural Language Annotation for Machine Learning potx
... Annotation for Machine Learning James Pustejovsky and Amber Stubbs Beijing • Cambridge • Farnham • Köln • Sebastopol • Tokyo www.it-ebooks.info Natural Language Annotation for Machine Learning ... Annotation for Machine Learning More specifically, this book details the multi-stage process for building your own annotated natural language dataset (known as a corpus) in order to train machine learning ... provides case studies for four different annotation tasks These tasks are examined in detail to provide context for the reader and help provide a foundation for their own machine learning goals Additionally,...
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Báo cáo khoa học: "Using Emoticons to reduce Dependency in Machine Learning Techniques for Sentiment Classification" pot
... percent Best performance on a test set for each model is highlighted in bold curacies, in percent Best performance on a test set for each model is highlighted in bold does not perform to the state-of-the-art, ... how machineo learning techniques for sentiment classification can be topic dependent However, that study focused on a three-way classification (positive, negative and neutral) In this paper, for ... the bestperforming settings for the Na¨ve Bayes classifier ı was a window context of 130 tokens taken from the largest training set of 22,000 articles Similarly, the best performance for the SVM...
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Báo cáo khoa học: "Active Learning for Multilingual Statistical Machine Translation∗" ppt
... Osborne 2003b Cotraining for statistical machine translation In Proceedings of the 6th Annual CLUK Research Colloquium Chris Callison-burch 2003 Active learning for statistical machine translation ... d=1 8: Monitor the performance on the test set 9: end for 3.3 Disagreement among the candidate translations of a particular entry is evidence for the difficulty of that entry for different translation ... 2: The performance of different sentence selection strategies as the iteration of AL loop goes on for three translation tasks Plots show the performance of sentence selection methods for single...
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Báo cáo khoa học: "A Seed-driven Bottom-up Machine Learning Framework for Extracting Relations of Various Complexity" pdf
... 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, ... patterns for projections We propose a rule representation that supports this strategy Therefore, our learning approach is seed-driven and bottom-up Here we use dependency trees as input for pattern ... Person_Out, Position, Organisation> In the following tables, 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...
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Báo cáo khoa học: "Feasibility Study for Ellipsis Resolution in Dialogues by Machine-Learning Technique" docx
... 36.8 33.9 26.1 3.8 7.7 1.3 20.5 :before 72(facilities) :before 94(building) :before 83(language) Speaker's role '-gozaimasu'(poliie) :before 16(situation) :before 34(statement) '-de'(case particle) ... 'ga(v.)' case, except for a few attributes Conclusion and Future Work This paper proposed a m e t h o d for resolving the ellipsis that appear in Japanese dialogues A machine- learning algorithm ... positional information, i.e., search space of morphemes from the target predicate Positional information can be one of five kinds: before, at the latest, here, next, and afterward For example,...
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Báo cáo khoa học: "Using Machine Learning Techniques to Build a Comma Checker for Basque" pdf
... important background for our work, we note where the linguistic information on the comma for the Basque language was formalised This information was extracted after analysing the theories of some ... Related work Machine learning techniques have been applied in many fields and for many purposes, but we have found only one reference in the literature related to the use of machine learning techniques ... report quite good results using machine learning techniques Car reras and Màrquez (2003) get one of the best per formances in this task (84.36% in test) There fore, we decided to adopt this...
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Báo cáo khoa học: "Active learning for interactive machine translation" pot
... Active learning for IMT The aim of the IMT framework is to obtain highquality translations while minimizing the required human effort Despite the fact that IMT may reduce the required effort with ... designed for its use in batch learning scenarios For such models, the incremental version of the EM algorithm (Neal and Hinton, 1999) is applied A detailed description of the update algorithm for ... system is equal to SCS but it not perform any SMT retraining Results in Figure show a consistent reduction in required user effort when using AL For a given human effort the use of AL methods allowed...
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bayesian methods for machine learning
... summer schools He is interested in Bayesian machine learning, computational approaches to sensorimotor control, and applications of machine learning to bioinformatics Zoubin Ghahramani Gatsby Computational ... Ghahramani is a Reader in Machine Learning at the Gatsby Unit in London, and an Associate Research Professor at CALD at CMU He has given tutorials at NIPS, ICANN, the Machine Learning Summer School ... Discriminative Modelling [20 minutes] o o Bayes Point Machines vs Support Vector Machines o Myth: Bayesian methods = Generative models Bayesian Neural Networks From Parametric to Nonparametric Bayes...
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A novel supervised machine learning algorithm for intrusion detection k Prototype+ID3
... gathered on an evaluation test bed simulating network traffic similar to that seen between an Air Force base (INSIDE network) and the Internet (OUTSIDE network) Nearly seven weeks of training data ... 4.1 Network Anomaly Data: Here we give brief description of each sub data set of NAD The data set is extracted from MIT-DARPA network traffic, each data sub set contain artificial neural network- based ... data set Network Anomaly Data (NAD) The NAD contains three sub data sets They are 1) NAD 98 2) NAD 99 3) NAD 00, obtained by attribute extracting the 1998, 1999, and 2000 MIT-DARPA network traffic...
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