NSTL国家科技图书文献中心

1. Iterative target updation based boosting ensembles for outlier detection NSTL国家科技图书文献中心

Mukhriya, Akanksha | Kumar, Rajeev - 《Pattern Recognition》 - 2025,158 - 共13页

摘要： with a boosting-based selection. The proposed iBoost | detectors are restricted. Multiple rounds of a boosting | the previous round. Our modified boosting* ensemble* | , BoostSel+, implements an add-on boosting* step for the* | In unsupervised settings, the goodness of the

关键词： Outlier detection | Ensembles | Target formation | Boosting

2. Constructing a Memristive Chaotic Oscillator With 2-D Offset Boosting NSTL国家科技图书文献中心

Keyu Huang | Chunbiao Li ... - 《IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems》 - 2025,44(1) - 294～303 - 共10页

摘要： applies offset boosting* of a system variable while the* | By designing a proper electromagnetic | constraint within a memristor, and introducing it into a | dynamical system with the increase of dimension, a class | of memristive chaotic systems with 2-D offset

关键词： Boosting | Memristors | Chaotic communication | Design automation | Bifurcation | Control systems | Trajectory

3. SecureCut: Federated Gradient Boosting Decision Trees with Efficient Machine Unlearning NSTL国家科技图书文献中心

Bowen Li | Jian Zhang ... - 《Pattern Recognition,Part V》 - International Conference on Pattern Recognition - 2025, - 350～365 - 共16页

摘要： Gradient Boosting* Decision Tree (GBDT) framework that* | In response to legislation, companies are now | mandated to honor the right to be forgotten by erasing | user data. Consequently, it has become imperative to | enable data removal in Vertical Federated Learning (VFL

关键词： Machine unlearning | Vertical federated learning | Gradient boosting decision trees

4. Evaluation of the transient performance of a two-stage hybrid boosting system for spark ignition engines NSTL国家科技图书文献中心

Usai, Vittorio | Marelli, Silvia - 《Proceedings of the Institution of Mechanical Engineers,Part D.Journal of Automobile Engineering》 - 2025,239(2/3) - 822～833 - 共12页

摘要： boosting system aimed at minimizing the delay in torque | -compressor significantly reduces time-to-boost, thus | on the boost* pressure dynamic response during* | adopting an e-compressor in terms of time-to-boost | This paper investigates a two-stage hybrid

关键词： Experimental | time-to-boost | turbo-lag | turbocharging | turbocharger | compressor | spark ignition engine | electric boosting system | hybrid boosting system | boosting system...

5. Boosting Adversarial Transferability via Relative Feature Importance-Aware Attacks NSTL国家科技图书文献中心

Jian-Wei Li | Wen-Ze Shao ... - 《IEEE transactions on information forensics and security》 - 2025,20 - 3489～3504 - 共16页

摘要：, and introduces an innovative boosting* idea different* | Modern deep neural networks are known highly | vulnerable to adversarial examples. As a pioneering work | , the fast gradient sign method (FGSM) is proved more | transferable in black-box attacks than its multi-small-step

关键词： Boosting | Feature extraction | Closed box | Computational modeling | Backpropagation | Artificial intelligence | Neurons | Glass box | Training | Sun

6. Feature Selection Voting Strategies and Hyperparameter Tuning in a Boosting Classification NSTL国家科技图书文献中心

Nicole Dalia Cilia | Giovanni Fanara ... - 《Pattern Recognition,Part II》 - International Conference on Pattern Recognition - 2025, - 123～142 - 共20页

摘要： performance of boosting* classification. As a case study, the* | damage in concrete structures. By leveraging boosting | work improves the performance of the boosting | This paper presents a novel approach to | feature selection voting strategies and a combination of

关键词： Boosting techniques | Machine learning | Optimization strategies | Predictive modeling | Feature selection | Damage classification

7. Partner in Crime: Boosting Targeted Poisoning Attacks Against Federated Learning NSTL国家科技图书文献中心

Shihua Sun | Shridatt Sugrim ... - 《IEEE transactions on information forensics and security》 - 2025,20 - 4152～4166 - 共15页

摘要：-training stage approach to Boost* Targeted Poisoning* | FL training process, as a means to boost* attacks* | Federated Learning (FL) exposes | vulnerabilities to targeted poisoning attacks that aim to cause | misclassification specifically from the source class to the target

关键词： Data models | Training | Boosting | Computational modeling | Servers | Training data | Sun | Privacy | Image edge detection | Fires

8. GB5mCPred: Cross-species 5mc Site Predictor Based on Bootstrap-based Stochastic Gradient Boosting Method for Poaceae NSTL国家科技图书文献中心

Sinha, Dipro | Dasmandal, Tanwy ... - 《Current Bioinformatics》 - 2025,20(2) - 139～148 - 共10页

摘要：, including random forest, gradient boosting, na & iuml;ve | , i.e., 92.6%, 86.41% and 0.84. Gradient Boosting | models were Random Forest, Gradient Boosting, and | Boosting, and Support Vector Machine ended up being the | Background One of the most prevalent

关键词： Epigenetics | 5mC prediction | artificial intelligence | hybrid feature selection | gradient boosting | poaceae.

9. Modeling of Ejection Efficiency of Vortex Tube Extractor by Gradient Boosting Machine NSTL国家科技图书文献中心

Akhilesh Kumar Singh | Nand Kumar Tiwari - 《Advances in clean energy technologies,Volume 1》 - International Conference on Innovations in Clean Energy Technologies - 2025, - 13～23 - 共11页

摘要： Gradient Boosting* Machine(GBM)approaches to predict* | Sediment in the canal has been a significant | concern for civil engineers in recent years.Most | irrigation and power canal water come from Himalayan rivers | ,which also keep a lot of silt.The vortex tube ejector

关键词： Gradient boosting machine(GBM) | Ejection efficiency | Vortex tube ejector

10. Rapid stability assessment of barrier dams based on the extreme gradient boosting model NSTL国家科技图书文献中心

Yang, Haiqing | Li, Hao ... - 《Natural Hazards》 - 2025,121(3) - 3047～3072 - 共26页

摘要： to optimize the Gradient Boosting* Decision Tree* | , Random forest, and Extreme Gradient Boosting* (XGBoost* | Barrier dams are major natural disasters that | frequently occur in mountainous areas and have a high | probability of destabilizing and failing within a short

摘要： with a boosting-based selection. The proposed iBoost | detectors are restricted. Multiple rounds of a boosting | the previous round. Our modified boosting* ensemble* | , BoostSel+, implements an add-on boosting* step for the* | In unsupervised settings, the goodness of the

关键词： Outlier detection | Ensembles | Target formation | Boosting

摘要： applies offset boosting* of a system variable while the* | By designing a proper electromagnetic | constraint within a memristor, and introducing it into a | dynamical system with the increase of dimension, a class | of memristive chaotic systems with 2-D offset

关键词： Boosting | Memristors | Chaotic communication | Design automation | Bifurcation | Control systems | Trajectory

摘要： Gradient Boosting* Decision Tree (GBDT) framework that* | In response to legislation, companies are now | mandated to honor the right to be forgotten by erasing | user data. Consequently, it has become imperative to | enable data removal in Vertical Federated Learning (VFL

关键词： Machine unlearning | Vertical federated learning | Gradient boosting decision trees

摘要： boosting system aimed at minimizing the delay in torque | -compressor significantly reduces time-to-boost, thus | on the boost* pressure dynamic response during* | adopting an e-compressor in terms of time-to-boost | This paper investigates a two-stage hybrid

关键词： Experimental | time-to-boost | turbo-lag | turbocharging | turbocharger | compressor | spark ignition engine | electric boosting system | hybrid boosting system | boosting system...

摘要：, and introduces an innovative boosting* idea different* | Modern deep neural networks are known highly | vulnerable to adversarial examples. As a pioneering work | , the fast gradient sign method (FGSM) is proved more | transferable in black-box attacks than its multi-small-step

关键词： Boosting | Feature extraction | Closed box | Computational modeling | Backpropagation | Artificial intelligence | Neurons | Glass box | Training | Sun

摘要： performance of boosting* classification. As a case study, the* | damage in concrete structures. By leveraging boosting | work improves the performance of the boosting | This paper presents a novel approach to | feature selection voting strategies and a combination of

关键词： Boosting techniques | Machine learning | Optimization strategies | Predictive modeling | Feature selection | Damage classification

摘要：-training stage approach to Boost* Targeted Poisoning* | FL training process, as a means to boost* attacks* | Federated Learning (FL) exposes | vulnerabilities to targeted poisoning attacks that aim to cause | misclassification specifically from the source class to the target

关键词： Data models | Training | Boosting | Computational modeling | Servers | Training data | Sun | Privacy | Image edge detection | Fires

摘要：, including random forest, gradient boosting, na & iuml;ve | , i.e., 92.6%, 86.41% and 0.84. Gradient Boosting | models were Random Forest, Gradient Boosting, and | Boosting, and Support Vector Machine ended up being the | Background One of the most prevalent

关键词： Epigenetics | 5mC prediction | artificial intelligence | hybrid feature selection | gradient boosting | poaceae.

摘要： Gradient Boosting* Machine(GBM)approaches to predict* | Sediment in the canal has been a significant | concern for civil engineers in recent years.Most | irrigation and power canal water come from Himalayan rivers | ,which also keep a lot of silt.The vortex tube ejector

关键词： Gradient boosting machine(GBM) | Ejection efficiency | Vortex tube ejector

摘要： to optimize the Gradient Boosting* Decision Tree* | , Random forest, and Extreme Gradient Boosting* (XGBoost* | Barrier dams are major natural disasters that | frequently occur in mountainous areas and have a high | probability of destabilizing and failing within a short

关键词： Barrier dam stability | Rapid assessment method | Sparrow search algorithm | Extreme gradient boosting

4008-161-200 800-990-8900

国家科技图书文献中心

摘要： with a boosting-based selection. The proposed iBoost | detectors are restricted. Multiple rounds of a boosting | the previous round. Our modified boosting ensemble | , BoostSel+, implements an add-on boosting step for the | In unsupervised settings, the goodness of the

关键词： Outlier detection | Ensembles | Target formation | Boosting

摘要： applies offset boosting of a system variable while the | By designing a proper electromagnetic | constraint within a memristor, and introducing it into a | dynamical system with the increase of dimension, a class | of memristive chaotic systems with 2-D offset

关键词： Boosting | Memristors | Chaotic communication | Design automation | Bifurcation | Control systems | Trajectory

摘要： Gradient Boosting Decision Tree (GBDT) framework that | In response to legislation, companies are now | mandated to honor the right to be forgotten by erasing | user data. Consequently, it has become imperative to | enable data removal in Vertical Federated Learning (VFL

关键词： Machine unlearning | Vertical federated learning | Gradient boosting decision trees

摘要： boosting system aimed at minimizing the delay in torque | -compressor significantly reduces time-to-boost, thus | on the boost pressure dynamic response during | adopting an e-compressor in terms of time-to-boost | This paper investigates a two-stage hybrid

关键词： Experimental | time-to-boost | turbo-lag | turbocharging | turbocharger | compressor | spark ignition engine | electric boosting system | hybrid boosting system | boosting system...

摘要：, and introduces an innovative boosting idea different | Modern deep neural networks are known highly | vulnerable to adversarial examples. As a pioneering work | , the fast gradient sign method (FGSM) is proved more | transferable in black-box attacks than its multi-small-step

关键词： Boosting | Feature extraction | Closed box | Computational modeling | Backpropagation | Artificial intelligence | Neurons | Glass box | Training | Sun

摘要： performance of boosting classification. As a case study, the | damage in concrete structures. By leveraging boosting | work improves the performance of the boosting | This paper presents a novel approach to | feature selection voting strategies and a combination of

关键词： Boosting techniques | Machine learning | Optimization strategies | Predictive modeling | Feature selection | Damage classification

摘要：-training stage approach to Boost Targeted Poisoning | FL training process, as a means to boost attacks | Federated Learning (FL) exposes | vulnerabilities to targeted poisoning attacks that aim to cause | misclassification specifically from the source class to the target

关键词： Data models | Training | Boosting | Computational modeling | Servers | Training data | Sun | Privacy | Image edge detection | Fires

摘要：, including random forest, gradient boosting, na & iuml;ve | , i.e., 92.6%, 86.41% and 0.84. Gradient Boosting | models were Random Forest, Gradient Boosting, and | Boosting, and Support Vector Machine ended up being the | Background One of the most prevalent

关键词： Epigenetics | 5mC prediction | artificial intelligence | hybrid feature selection | gradient boosting | poaceae.

摘要： Gradient Boosting Machine(GBM)approaches to predict | Sediment in the canal has been a significant | concern for civil engineers in recent years.Most | irrigation and power canal water come from Himalayan rivers | ,which also keep a lot of silt.The vortex tube ejector

关键词： Gradient boosting machine(GBM) | Ejection efficiency | Vortex tube ejector

摘要： to optimize the Gradient Boosting Decision Tree | , Random forest, and Extreme Gradient Boosting (XGBoost | Barrier dams are major natural disasters that | frequently occur in mountainous areas and have a high | probability of destabilizing and failing within a short

关键词： Barrier dam stability | Rapid assessment method | Sparrow search algorithm | Extreme gradient boosting

4008-161-200 800-990-8900

国家科技图书文献中心

摘要： with a boosting-based selection. The proposed iBoost | detectors are restricted. Multiple rounds of a boosting | the previous round. Our modified boosting* ensemble* | , BoostSel+, implements an add-on boosting* step for the* | In unsupervised settings, the goodness of the

摘要： applies offset boosting* of a system variable while the* | By designing a proper electromagnetic | constraint within a memristor, and introducing it into a | dynamical system with the increase of dimension, a class | of memristive chaotic systems with 2-D offset

摘要： Gradient Boosting* Decision Tree (GBDT) framework that* | In response to legislation, companies are now | mandated to honor the right to be forgotten by erasing | user data. Consequently, it has become imperative to | enable data removal in Vertical Federated Learning (VFL

摘要： boosting system aimed at minimizing the delay in torque | -compressor significantly reduces time-to-boost, thus | on the boost* pressure dynamic response during* | adopting an e-compressor in terms of time-to-boost | This paper investigates a two-stage hybrid

摘要：, and introduces an innovative boosting* idea different* | Modern deep neural networks are known highly | vulnerable to adversarial examples. As a pioneering work | , the fast gradient sign method (FGSM) is proved more | transferable in black-box attacks than its multi-small-step

摘要： performance of boosting* classification. As a case study, the* | damage in concrete structures. By leveraging boosting | work improves the performance of the boosting | This paper presents a novel approach to | feature selection voting strategies and a combination of

摘要：-training stage approach to Boost* Targeted Poisoning* | FL training process, as a means to boost* attacks* | Federated Learning (FL) exposes | vulnerabilities to targeted poisoning attacks that aim to cause | misclassification specifically from the source class to the target

摘要： Gradient Boosting* Machine(GBM)approaches to predict* | Sediment in the canal has been a significant | concern for civil engineers in recent years.Most | irrigation and power canal water come from Himalayan rivers | ,which also keep a lot of silt.The vortex tube ejector

摘要： to optimize the Gradient Boosting* Decision Tree* | , Random forest, and Extreme Gradient Boosting* (XGBoost* | Barrier dams are major natural disasters that | frequently occur in mountainous areas and have a high | probability of destabilizing and failing within a short