Results 31 to 40 of about 263,437 (264)
Hyper-parameter Tuning for Quantum Support Vector Machine
Advances in Electrical and Computer Engineering, 2022 In recent years, the positive effect of quantum techniques on machine learning methods have been studied. Especially in training big data, quantum computing is beneficial in terms of speed.
DEMIRTAS, F., TANYILDIZI, E.
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Least Squares Support Vector Machine for Minimizing VC Dimensional Expectation Upper Bound [PDF]
Jisuanji kexue yu tansuo, 2023 Machine learning is an important aspect of modern computer technology, and the support vector machine method has been widely used in all walks of life because of its good performance in recent years.
LI Hao, WANG Shitong
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The support vector decomposition machine [PDF]
Proceedings of the 23rd international conference on Machine learning - ICML '06, 2006 In machine learning problems with tens of thousands of features and only dozens or hundreds of independent training examples, dimensionality reduction is essential for good learning performance. In previous work, many researchers have treated the learning problem in two separate phases: first use an algorithm such as singular value decomposition to ...
Francisco Pereira 0001 +1 more
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Transformers as Support Vector Machines
CoRR, 2023 Since its inception in "Attention Is All You Need", transformer architecture has led to revolutionary advancements in NLP. The attention layer within the transformer admits a sequence of input tokens $X$ and makes them interact through pairwise similarities computed as softmax$(XQK^\top X^\top)$, where $(K,Q)$ are the trainable key-query parameters. In
Davoud Ataee Tarzanagh +3 more
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Twin Support Vector Machine: A review from 2007 to 2014
Egyptian Informatics Journal, 2015 Twin Support Vector Machine (TWSVM) is an emerging machine learning method suitable for both classification and regression problems. It utilizes the concept of Generalized Eigen-values Proximal Support Vector Machine (GEPSVM) and finds two non-parallel ...
Divya Tomar, Sonali Agarwal
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Vector machine techniques for modeling of seismic liquefaction data
Ain Shams Engineering Journal, 2014 This article employs three soft computing techniques, Support Vector Machine (SVM); Least Square Support Vector Machine (LSSVM) and Relevance Vector Machine (RVM), for prediction of liquefaction susceptibility of soil.
Pijush Samui
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Gaussian Pyramid for Nonlinear Support Vector Machine
Applied Computational Intelligence and Soft Computing, 2022 Support vector machine (SVM) is one of the most efficient machine learning tools, and it is fast, simple to use, reliable, and provides accurate classification results.
Rawan Abo Zidan, George Karraz
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Reciprocal control of viral infection and phosphoinositide dynamics
FEBS Letters, EarlyView.Phosphoinositides, although scarce, regulate key cellular processes, including membrane dynamics and signaling. Viruses exploit these lipids to support their entry, replication, assembly, and egress. The central role of phosphoinositides in infection highlights phosphoinositide metabolism as a promising antiviral target.
Marie Déborah Bancilhon, Bruno Mesmin
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$$\nu $$ ν -Improved nonparallel support vector machine
Scientific Reports, 2022 In this paper, a $$\nu $$ ν -improved nonparallel support vector machine ( $$\nu $$ ν -IMNPSVM) is proposed to solve binary classification problems.
Fengmin Sun, Shujun Lian
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The human gut microbiome across the life course
FEBS Letters, EarlyView.Despite significant individual variation and continuous change throughout life, the human gut microbiome follows some life stage‐specific trends. This article provides a brief overview of how gut microbiome composition shifts across different phases of life. Created in BioRender. Özkurt, E. (2026) https://BioRender.com/8q4nrnc.
Alise J. Ponsero +4 more
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