Suchergebnisse - Computing methodologies Machine learning Machine learning approaches Factorization methods

Selection of a Suitable Rock Mixing Method for Computing Gardner’s Constant Through a Machine Learning (ML) Approach to Estimate the Compressional Velocity: A study from the Jaisalmer sub-basin, India von Yalamanchi, Pydiraju, Datta Gupta, Saurabh

“… The frequent variability of petrophysical properties makes hydrocarbon exploration challenging in carbonate reservoirs. Nowadays, quantitative interpretation …”
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A Novel Sequence-Based Method of Predicting Protein DNA-Binding Residues, Using a Machine Learning Approach von Cai, Yudong, Shanghai University, Shanghai, People's Republic of China, He, ZhiSong, Zhejiang University, ZheJiang, People's Republic of China, Shi, Xiaohe, Chinese Academy of Sciences and Shanghai Jiao Tong University School of Medicine, People's Republic of China, Kong, Xiangying, Chinese Academy of Sciences and Shanghai Jiao Tong University School of Medicine, People's Republic of China, Gu, Lei, Fraunhofer Institute for Algorithms and Scientific Computing, Germany, Xie, Lu, Shanghai Center for Bioinformation Technology, Shanghai, People's Republic of China

“… Some in silico methods have been developed, but there are still considerable limitations. In this study, we used a machine learning approach to develop a new sequence-based method of predicting protein-DNA binding residues …”
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An Extension to Basis-Hypervectors for Learning from Circular Data in Hyperdimensional Computing von Nunes, Igor, Heddes, Mike, Givargis, Tony, Nicolau, Alexandru

“… Hyperdimensional Computing (HDC) is a computation framework based on random vector spaces, particularly useful for machine learning in resource-constrained environments …”
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SFLU: Synchronization-Free Sparse LU Factorization for Fast Circuit Simulation on GPUs von Zhao, Jianqi, Wen, Yao, Luo, Yuchen, Jin, Zhou, Liu, Weifeng, Zhou, Zhenya

“… Sparse LU factorization is one of the key building blocks of sparse direct solvers and often dominates the computing time of circuit simulation programs …”
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ISLU: Indexing-Efficient Sparse LU Factorization for Circuit Simulation on GPUs (Invited Paper) von Niu, Dan, Tao, Yiyang, Jin, Zhou, Dong, Yichao, Wang, Chao, Sun, Changyin

“… Conventional LU factorization methods generally involve two approaches: either they utilize space-intensive dense matrices for direct index-to-data mapping, or they inefficiently scour through indices to locate the positions of updated data elements …”
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Federated Tensor Factorization for Computational Phenotyping von Kim, Yejin, Sun, Jimeng, Yu, Hwanjo, Jiang, Xiaoqian

“… Tensor factorization models offer an effective approach to convert massive electronic health records into meaningful clinical concepts (phenotypes) for data analysis …”
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Predicting accurate and actionable static analysis warnings: an experimental approach von Ruthruff, Joseph R, Penix, John, Morgenthaler, J David, Elbaum, Sebastian, Rothermel, Gregg

“… Static analysis tools report software defects that may or may not be detected by other verification methods …”
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A history-based test prioritization technique for regression testing in resource constrained environments von Kim, Jung-Min, Porter, Adam

“… Regression testing is an expensive and frequently executed maintenance process used to revalidate modified software. To improve it, regression test selection …”
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Identifying Traits of Leaders in Movement Initiation von Amornbunchornvej, Chainarong, Crofoot, Margaret C., Berger-Wolf, Tanya Y.

“… ? In this paper we present a computational method to characterize and classify the types of leaders in movement initiation …”
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Privacy-Preserving Tensor Factorization for Collaborative Health Data Analysis von Ma, Jing, Zhang, Qiuchen, Lou, Jian, Ho, Joyce C, Xiong, Li, Jiang, Xiaoqian

“… Tensor factorization has been demonstrated as an efficient approach for computational phenotyping, where massive electronic health records (EHRs …”
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LogPar: Logistic PARAFAC2 Factorization for Temporal Binary Data with Missing Values von Yin, Kejing, Afshar, Ardavan, Ho, Joyce C, Cheung, William K, Zhang, Chao, Sun, Jimeng

“… , either presence or absence of a feature). Learning accurate low-rank approximations from such binary irregular tensors is a challenging task …”
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A replicated assessment and comparison of common software cost modeling techniques von Briand, Lionel C., Langley, Tristen, Wieczorek, Isabella

“… Delivering a software product on time, within budget, and to an agreed level of quality is a critical concern for many software organizations. Underestimating …”
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Spatial correlation modeling for probe test cost reduction in RF devices von Kupp, Nathan, Huang, Ke, Carulli, John M., Makris, Yiorgos

“… In this work, we investigate a spatial correlation modeling approach using Gaussian process models to enable extrapolation of performances via sparse sampling of probe test data …”
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Inference for Ever-Changing Policy of Taint Analysis von Chiang, Wen-Hao, Li, Peixuan, Zhou, Qiang, Banerjee, Subarno, Schaef, Martin, Lyu, Yingjun, Nguyen, Hoan, Tripp, Omer

“… Identifying correct and complete taint specifications is critical for detecting vulnerabilities in the ever-changing landscape of software security, and an …”
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Analysis and RTL correlation of instruction set simulators for automotive microcontroller robustness verification von Espinosa, Jaime, Hernandez, Carles, Abella, Jaume, de Andres, David, Ruiz, Juan Carlos

“… Increasingly complex microcontroller designs for safety-relevant automotive systems require the adoption of new methods and tools to enable a cost-effective verification of their robustness …”
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Distributed regression: an efficient framework for modeling sensor network data von Guestrin, Carlos, Bodik, Peter, Thibaux, Romain, Paskin, Mark, Madden, Samuel

“… We present distributed regression, an efficient and general framework for in-network modeling of sensor data. In this framework, the nodes of the sensor …”
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SUSTain: Scalable Unsupervised Scoring for Tensors and its Application to Phenotyping von Perros, Ioakeim, Papalexakis, Evangelos E, Park, Haesun, Vuduc, Richard, Yan, Xiaowei, Defilippi, Christopher, Stewart, Walter F, Sun, Jimeng

“… This paper presents a new method, which we call SUSTain, that extends real-valued matrix and tensor factorizations to data where values are integers …”
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Target Gene Prediction of Transcription Factor Using a New Neighborhood-regularized Tri-factorization One-class Collaborative Filtering Algorithm von Lim, Hansaim, Xie, Lei

“… Thus, computational prediction methods are useful to predict the unobserved associations …”
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An empirical study of regression test application frequency von Kim, Jung-Min, Porter, Adam, Rothermel, Gregg

“… Regression testing is an expensive maintenance process used to revalidate modified software. Regression test selection (RTS) techniques try to lower the cost …”
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Fast Component Pursuit for Large-Scale Inverse Covariance Estimation von Han, Lei, Zhang, Yu, Zhang, Tong

“… The maximum likelihood estimation (MLE) for the Gaussian graphical model, which is also known as the inverse covariance estimation problem, has gained …”
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