Learning via automaton minimization and matrix factorization Dahkki Marusic, I

“…</p> <p>The second part of the thesis studies nonnegative matrix factorization (NMF), a powerful dimension-reduction and feature-extraction technique with numerous applications in machine learning and other scientific disciplines. …”

Essays on time series econometrics and financial econometrics Dahkki Xu, W

“…</p> <p>The first essay proposes a new class of multivariate volatility models utilizing realized measures of asset volatility and covolatility extracted from high-frequency data. Dimension reduction for estimation of large covariance matrices is achieved by imposing a factor structure with time-varying conditional factor loadings. …”

Application of machine learning techniques to tuberculosis drug resistance analysis Dahkki Kouchaki, S, Yang, Y, Walker, T, Walker, A, Wilson, D, Peto, T, Crook, D, Clifton, D, Cryptic Consortium

“…<br/><br/> <strong>Summary</strong> Several machine learning classifiers and linear dimension reduction techniques were developed and compared for a cohort of 13402 isolates collected from 16 countries across six continents and tested 11 drugs. …”

Percolation games, probabilistic cellular automata, and the hard-core model Dahkki Holroyd, A, Marcovici, I, Martin, J

“…This is proved via a dimension reduction to a hard-core lattice gas in dimension d−1 . …”

Optimising arrival management in air traffic control Dahkki Yang, L

“…Further we explore dimension reduction/feature representation through path signatures. …”

Non-fiducial based ECG biometric authentication using one-class support vector machine Dahkki Hejazi, Maryamsadat, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Hashim, Shaiful Jahari, Abdul Aziz, Ahmad Fazli, Singh, Yashwant Prasad

“…The experiments were carried out with defining a number of scenarios on ECG data sets designed rely on feature extractors which were modeled based on an autocorrelation in conjunction with linear and nonlinear dimension reduction methods. The experimental results show that Kernel Principal Component Analysis has lower error rate in binary and one-class SVMs on random unknown ECG data sets. …”
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An investigation on leading characteristics of rapidkuantan bus passengers using correspondence analysis Dahkki Sharifah, Awang

“…This study shows how the analysis can be done for categorical travel data (qualitative analysis) using correspondence analysis which is a dimension reduction technique similar to factor analysis but extends factor analysis in handling of categorical data/variables. …”
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A decomposition-based uncertainty quantification approach for environmental impacts of aviation technology and operation Dahkki Amaral, Sergio Daniel Marques, Allaire, Douglas L, De La Rosa Blanco, Elena, Willcox, Karen E

“…In this work, we demonstrate how to handle a high-dimensional multicomponent interface using sensitivity-based dimension reduction and a novel importance sampling method. …”
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Neural Stress Fields for Reduced-order Elastoplasticity and Fracture Dahkki Zong, Zeshun, Li, Xuan, Li, Minchen, Chiaramonte, Maurizio M., Matusik, Wojciech, Grinspun, Eitan, Carlberg, Kevin, Jiang, Chenfanfu, Chen, Peter Yichen

“…We demonstrate dimension reduction by up to 100,000 × and time savings by up to 10 ×.…”
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Reduced Basis Approximation and a Posteriori Error Estimation for the Parametrized Unsteady Boussinesq Equations Dahkki Knezevic, David, Nguyen, Ngoc Cuong, Patera, Anthony T.

“…The essential ingredients are Galerkin projection onto a low-dimensional space associated with a smooth parametric manifold — to provide dimension reduction; an efficient proper orthogonal decomposition–Greedy sampling method for identification of optimal and numerically stable approximations — to yield rapid convergence; accurate (online) calculation of the solution-dependent stability factor by the successive constraint method — to quantify the growth of perturbations/residuals in time; rigorous a posteriori bounds for the errors in the RB approximation and associated outputs — to provide certainty in our predictions; and an offline–online computational decomposition strategy for our RB approximation and associated error bound — to minimize marginal cost and hence achieve high performance in the real-time and many-query contexts. …”
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Questionnaire data analysis using information geometry Dahkki Har-Shemesh, Omri, Quax, Rick, Lansing, J. Stephen, Sloot, Peter M. A.

“…Compare to previous analysis and known anthropological knowledge we conclude that our method best discriminates between different behaviours, paving the way to dimension reduction as effective as for continuous data.…”
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New directions in four-dimensional mathematical visualization Dahkki Yan, Xiaoqi

“…In more detail, projecting a 4D object onto 3D space is actually a dimension reduction. Certain geometrical information, such as symmetry and curvature, is unavoidably lost after the projection because we rely on the 3D projection view to explore the geometry that actually exists in four dimensions. …”
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Penggunaan metode kondensasi dinamis dan metode perturbed parameters dalam evaluasi kekuatan sisa struktur balok beton retak Dahkki Perpustakaan UGM, i-lib

“…At this condition, the dimension reduction, stiffness matrix and mass matrix are needed, so the use of the dynamic condensation method is an appropriate way. …”

Quantification of spatial and phenotypic heterogeneity in an agent-based model of tumour-macrophage interactions Dahkki Bull, JA, Byrne, HM

“…We also define a distinct ‘PCF signature’ that characterises each of the three Es of immunoediting, by combining wPCF measurements with the cross-PCF describing interactions between vessels and tumour cells. By applying dimension reduction techniques to this signature, we identify its key features and train a support vector machine classifier to distinguish between simulation outputs based on their PCF signature. …”

Novel risk index for the identification of age-related macular degeneration using radon transform and DWT features Dahkki Acharya, U.R., Mookiah, M.R.K., Koh, J.E.W., Tan, J.H., Noronha, K., Bhandary, S.V., Rao, A.K., Hagiwara, Y., Chua, C.K., Laude, A.

“…The extracted features are subjected to dimension reduction using LSDA and ranked using t-test. …”

Objective identification of pain due to uterine contraction during the first stage of labour using continuous EEG signals and SVM Dahkki Sai, Chong Yeh, Mokhtar, Norrima, Yip, Hing Wa, Bak, Lindy Li Mei, Hasan, Mohd Shahnaz, Arof, Hamzah, Cumming, Paul, Mat Adenan, Noor Azmi

“…SVM using the spectral activities, statistical and non-linear features of the EEG classified the state of pain with 83% accuracy using a classification model generalizable across subjects. Furthermore, dimension reduction using Principal Component Analysis (PCA) successfully reduced the number of features used in the classification while achieving a maximum classification accuracy of 84%. …”

Optimized intelligent classifier for early breast cancer detection using ultra-wide band transceiver Dahkki Abdul Halim, Ahmad Ashraf, Andrew, Allan Melvin, Mustafa, Wan Azani, Mohd Yasin, Mohd Najib, Jusoh, Muzammil, Veeraperumal, Vijayasarveswari, Abd Rahman, Mohd Amiruddin, Zamin, Norshuhani, Mary, Mervin Retnadhas, Khatun, Sabira

“…Consequently, the dataset was fed into the MSFS–BPSO framework and started with feature normalization before it was reduced using feature dimension reduction. Then, the feature selection (based on time/frequency domain) using seven different classifiers selected the frequency domain compared to the time domain and continued to perform feature extraction. …”

Reduced-order modeling for ensemble real-time estimation and control Dahkki Lin, Binghuai

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Polynomial identity testing of read-once oblivious algebraic branching programs Dahkki Forbes, Michael Andrew

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Performance comparison on graph-based sparse coding methods for face representation Dahkki Zhao, Xiaozhi

“…The impact of dictionary size, choice of distance metric, and PCA dimension reduction on face recognition accuracy is also examined. …”
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