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Ensemble Learning

Papers

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Showing 751–775 of 1207 papers

TitleStatusHype
Securing Fog-to-Things Environment Using Intrusion Detection System Based On Ensemble Learning—0
SEdroid: A Robust Android Malware Detector using Selective Ensemble Learning—0
SEERL: Sample Efficient Ensemble Reinforcement Learning—0
SEGEN: SAMPLE-ENSEMBLE GENETIC EVOLUTIONARY NETWORK MODEL—0
Self-paced ensemble learning for speech and audio classification—0
Semantic-Preserving Feature Partitioning for Multi-View Ensemble Learning—0
SemiContour: A Semi-supervised Learning Approach for Contour Detection—0
Semi-supervised Predictive Clustering Trees for (Hierarchical) Multi-label Classification—0
Sensor-Type Classification in Buildings—0
Sequential Ensemble Learning for Outlier Detection: A Bias-Variance Perspective—0
SFE-Net: EEG-based Emotion Recognition with Symmetrical Spatial Feature Extraction—0
SHINRA2020-ML: Categorizing 30-language Wikipedia into fine-grained NE based on "``Resource by Collaborative Contribution" scheme—0
SHINRA: Structuring Wikipedia by Collaborative Contribution—0
Short-term prediction of construction waste transport activities using AI-Truck—0
SINAI at SemEval-2019 Task 5: Ensemble learning to detect hate speech against inmigrants and women in English and Spanish tweets—0
SleepEGAN: A GAN-enhanced Ensemble Deep Learning Model for Imbalanced Classification of Sleep Stages—0
Sleep Quality Prediction from Wearables using Convolution Neural Networks and Ensemble Learning—0
Smaller, more accurate regression forests using tree alternating optimization—0
Smart obervation method with wide field small aperture telescopes for real time transient detection—0
Snapshot Spectral Clustering -- a costless approach to deep clustering ensembles generation—0
Softlog-Softmax Layers and Divergences Contribute to a Computationally Dependable Ensemble Learning—0
Solving Soft Clustering Ensemble via k-Sparse Discrete Wasserstein Barycenter—0
Solving the Problem of the K Parameter in the KNN Classifier Using an Ensemble Learning Approach—0
Sparse identification of nonlinear dynamics with high accuracy and reliability under noisy conditions for applications to industrial systems—0
Sparse Learning and Class Probability Estimation with Weighted Support Vector Machines—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DCFAccuracy0.98—Unverified