Výsledky vyhledávání - Computing methodologies Machine learning Machine learning approaches Factorization methods
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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
ISSN: 0033-4553, 1420-9136Vydáno: Cham Springer International Publishing 01.05.2021Vydáno v Pure and applied geophysics (01.05.2021)“…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
ISSN: 1016-8478, 0219-1032, 0219-1032Vydáno: Springer Korean Society for Molecular and Cellular Biology 01.08.2010Vydáno v Molecules and cells (01.08.2010)“… 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
Vydáno: IEEE 09.07.2023Vydáno v 2023 60th ACM/IEEE Design Automation Conference (DAC) (09.07.2023)“…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
Vydáno: IEEE 05.12.2021Vydáno v 2021 58th ACM/IEEE Design Automation Conference (DAC) (05.12.2021)“…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)
ISSN: 1558-2434Vydáno: ACM 27.10.2024Vydáno v Digest of technical papers - IEEE/ACM International Conference on Computer-Aided Design (27.10.2024)“… 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
ISSN: 2154-817XVydáno: United States 01.08.2017Vydáno v Proceedings / International Conference on Knowledge Discovery and Data Mining (01.08.2017)“…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
ISBN: 1605580791, 9781605580791ISSN: 0270-5257Vydáno: 01.01.2008Vydáno v International Conference on Software Engineering 2008 (01.01.2008)“…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
ISBN: 158113472X, 9781581134728ISSN: 0270-5257Vydáno: New York, NY, USA ACM 2002Vydáno v Proceedings - International Conference on Software Engineering (2002)“…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
ISBN: 1450349935, 9781450349932ISSN: 2473-991XVydáno: New York, NY, USA ACM 31.07.2017Vydáno v 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (31.07.2017)“…? 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
ISSN: 2155-0751Vydáno: United States 01.11.2019Vydáno v Proceedings of the ... ACM International Conference on Information & Knowledge Management (01.11.2019)“…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
ISSN: 2154-817XVydáno: 23.08.2020Vydáno v Proceedings / International Conference on Knowledge Discovery and Data Mining (23.08.2020)“…, 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
ISBN: 1581132069, 9781581132069ISSN: 0270-5257Vydáno: New York, NY, USA ACM 2000Vydáno v Proceedings / International Conference on Software Engineering (2000)“…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
ISBN: 9781450315739, 1450315739ISSN: 1092-3152Vydáno: New York, NY, USA ACM 05.11.2012Vydáno v 2012 IEEE/ACM International Conference on Computer-Aided Design (ICCAD) (05.11.2012)“… 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
ISSN: 2832-7659Vydáno: ACM 14.04.2024Vydáno v IEEE/ACM International Conference on Software Engineering: Software Engineering in Practice (Online) (14.04.2024)“…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
ISSN: 0738-100XVydáno: IEEE 01.06.2015Vydáno v Proceedings - ACM IEEE Design Automation Conference (01.06.2015)“…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
ISBN: 1581138466, 9781581138467Vydáno: New York, NY, USA ACM 26.04.2004Vydáno v IPSN 2004 : Third International Symposium on Information Processing in Sensor Networks, April 26-27, 2004, Berkeley, California, USA (26.04.2004)“…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
ISSN: 2154-817XVydáno: United States 01.07.2018Vydáno v Proceedings / International Conference on Knowledge Discovery and Data Mining (01.07.2018)“…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
Vydáno: United States 15.08.2018Vydáno v ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine (15.08.2018)“… Thus, computational prediction methods are useful to predict the unobserved associations…”
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An empirical study of regression test application frequency
ISBN: 1581132069, 9781581132069ISSN: 0270-5257Vydáno: New York, NY, USA ACM 2000Vydáno v Proceedings / International Conference on Software Engineering (2000)“…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
ISSN: 2154-817XVydáno: United States 01.08.2016Vydáno v Proceedings / International Conference on Knowledge Discovery and Data Mining (01.08.2016)“…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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