Search Results - structural risk minimization algorithm

Learning Hidden Graphs From Samples by Abniki, Ahmad, Beigy, Hamid

“…Several real-world problems, like molecular biology and chemical reactions, have hidden graphs, and we need to learn the hidden graph using edge-detecting…”
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Improvements on least squares twin multi-class classification support vector machine by de Lima, Márcio Dias, Costa, Nattane Luiza, Barbosa, Rommel

“… Besides that, in our algorithm the structural risk minimization (SRM) principle…”
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In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines by Anguita, D., Ghio, A., Oneto, L., Ridella, S.

“… risk minimization framework and propose a proper reformulation of the SVM learning algorithm…”
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CLAss-Specific Subspace Kernel Representations and Adaptive Margin Slack Minimization for Large Scale Classification by Yu, Yinan, Diamantaras, Konstantinos I., McKelvey, Tomas, Kung, Sun-Yuan

“… In the second part, we propose a novel structural risk minimization algorithm called the adaptive margin slack minimization to iteratively improve the classification accuracy by an adaptive data selection…”
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Indefinite twin support vector machine with DC functions programming by An, Yuexuan, Xue, Hui

“… However, the lack of the structural risk minimization principle restrains the generalization of TWSVM and the guarantee of convex…”
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Rademacher penalties and structural risk minimization by Koltchinskii, V.

“…We suggest a penalty function to be used in various problems of structural risk minimization…”
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An Anomaly Detection Method Based on Normalized Mutual Information Feature Selection and Quantum Wavelet Neural Network by Huang, Wanwei, Zhang, Jianwei, Sun, Haiyan, Ma, Huan, Cai, Zengyu

“…This paper presents an anomaly detection model based on normalized mutual information feature selection (NMIFS) and quantum wavelet neural network (QWNN). The…”
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Capped Linex Metric Twin Support Vector Machine for Robust Classification by Wang, Yifan, Yu, Guolin, Ma, Jun

“… Moreover, the effect of outliers on the model can be greatly reduced by introducing two regularization terms to realize the structural risk minimization principle…”
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Genetic algorithm optimize neural network based on structural risk minimization by Fan Jinsong, Tao Qing, Fang Tingjian

“…The paper demonstrates a method for optimizing a neural network based on structural risk minimization (SRM…”
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Fast minimization of structural risk by nearest neighbor rule by Karacali, B., Krim, H.

“…In this paper, we present a novel nearest neighbor rule-based implementation of the structural risk minimization principle to address a generic classification problem…”
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Forecasting concentrations of air pollutants by logarithm support vector regression with immune algorithms by Lin, Kuo-Ping, Pai, Ping-Feng, Yang, Shun-Ling

“…) model which takes advantage of the structural risk minimization of SVR models, the data smoothing of preprocessing procedures, and the optimization…”
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Towards Accurate Post-Training Quantization for Diffusion Models by Wang, Changyuan, Wang, Ziwei, Xu, Xiuwei, Tang, Yansong, Zhou, Jie, Lu, Jiwen

“…In this paper, we propose an accurate post-training quantization framework of diffusion models (APQ-DM) for efficient image generation. Conventional…”
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Multi-objective structural risk minimization in multi-gene genetic programming for mathematical modeling of battery digital twin by Vandana, Garg, Akhil, Panigrahi, B.K., Gao, Liang

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Structural Risk Minimization-Driven Genetic Programming for Enhancing Generalization in Symbolic Regression by Chen, Qi, Zhang, Mengjie, Xue, Bing

“…) for symbolic regression. Structural risk minimization (SRM) is a framework providing a reliable estimation of the generalization performance of prediction models…”
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Application of smoothing techniques for linear programming twin support vector machines by Tanveer, M.

“… One significant advantage of our proposed algorithm over TWSVM is that the structural…”
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Structural risk minimization of rough set-based classifier by Liu, Jinfu, Bai, Mingliang, Jiang, Na, Yu, Daren

“… The structural risk minimization (SRM) inductive principle is one of the most effective theories to control the generalization ability, which suggests a trade-off between errors in seen objects and complexity…”
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An Interval Type-2 Fuzzy-Neural Network With Support-Vector Regression for Noisy Regression Problems by Juang, Chia-Feng, Huang, Ren-Bo, Cheng, Wei-Yuan

“… The parameters are optimized for structural-risk minimization using a two-phase linear SVR algorithm in order to endow the network with high generalization ability. IT2FNN-SVR performance is verified through comparisons with type-1 and type-2 fuzzy-logic systems and other regression models on noisy regression problems…”
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Support vector regression with chaos-based firefly algorithm for stock market price forecasting by Kazem, Ahmad, Sharifi, Ebrahim, Hussain, Farookh Khadeer, Saberi, Morteza, Hussain, Omar Khadeer

“…[Display omitted] ► Novel optimization method integrating chaotic mapping operator & firefly algorithm…”
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Regularized Least Squares Twin SVM for Multiclass Classification by Ali, Javed, Aldhaifallah, M., Nisar, Kottakkaran Sooppy, Aljabr, A.A., Tanveer, M.

“… Multiclass classification problems require high computational cost and thus need efficient algorithms to reduce the training time…”
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Hierarchical Semantic Risk Minimization for Large-Scale Classification by Wang, Yu, Wang, Zhou, Hu, Qinghua, Zhou, Yucan, Su, Honglei

“… However, most existing hierarchical classification models aim at maximizing the percentage of correct predictions, and do not take the risk of misclassifications into account…”
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