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HSR: L 1/2-regularized sparse representation for fast face recognition using hierarchical feature selection.

, , , , , , and . Neural Comput. Appl., 27 (2): 305-320 (2016)

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Combination of Evidence with Different Weighting Factors: A Novel Probabilistic-Based Dissimilarity Measure Approach., and . J. Sensors, (2015)LARSEN-ELM: Selective Ensemble of Extreme Learning Machines using LARS for Blended Data., , , , , , and . CoRR, (2014)Are Multimodal Transformers Robust to Missing Modality?, , , , and . CVPR, page 18156-18165. IEEE, (2022)HSR: L1/2 Regularized Sparse Representation for Fast Face Recognition using Hierarchical Feature Selection., , , , and . CoRR, (2014)Predefined-time parameter estimation via modified dynamic Regressor extension and mixing., , , , and . J. Frankl. Inst., 358 (13): 6897-6921 (2021)SMIL: Multimodal Learning with Severely Missing Modality., , , , , and . AAAI, page 2302-2310. AAAI Press, (2021)HSR: L 1/2-regularized sparse representation for fast face recognition using hierarchical feature selection., , , , , , and . Neural Comput. Appl., 27 (2): 305-320 (2016)Forecasting hourly electricity demand with nonparametric functional data analysis., , and . ITQM, volume 214 of Procedia Computer Science, page 428-436. Elsevier, (2022)A Calibration Method of Anamorphic Lens Camera Based on Virtual 3D Target*., , , , and . AIM, page 205-210. IEEE, (2019)LARSEN-ELM: Selective ensemble of extreme learning machines using LARS for blended data., , , , , , and . Neurocomputing, (2015)