NettetJun enjoys processing the large scale data to uncover meaningful and interesting results. He has published 50+ papers (6 NIPS, 8 KDD, 4 ICML) with 3000+ citations. He has 11 US patents with a few ... Nettet10. apr. 2024 · The features were extracted using sparse principal component analysis (SPCA), and enhanced marine predators algorithm (EMPA) was used for feature selection. The BMS’s safety and dependability may be enhanced by the suggested incipient bat-optimized deep residual network (IB-DRN)-based false battery data …
Learning Feature Sparse Principal Subspace Request PDF
Nettet6. feb. 2024 · We propose a general ensemble classification framework, RaSE algorithm, for the sparse classification problem. In RaSE algorithm, for each weak learner, some random subspaces are generated and the optimal one is chosen to train the model on the basis of some criterion. To be adapted to the problem, a novel criterion, ratio … NettetI am a Principal Researcher at Microsoft. My expertise spans topics across computer vision and healthcare, with publications in CVPR, ICCV, ECCV, ICLR, MICCAI, Nature Medicine, Lancet Oncology ... tims math
Minimax sparse principal subspace estimation in high dimensions
NettetLearning Feature Sparse Principal Subspace NeurIPS 2024 ... (FSPCA), which performs feature selection and PCA simultaneously. Existing optimization methods for FSPCA require data distribution … Nettet28. des. 2024 · The sparse representation-based classification is a hot topic in computer vision and pattern recognition. It is one type of commonly used image classification algorithms for FER in recent years. To improve the accuracy of FER system, this study proposed a sparse representation classifier embedding subspace mapping and … Nettet31. okt. 2007 · Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, information retrieval, and pattern recognition. Some popular methods include principal component analysis (PCA), linear discriminant analysis (LDA) and locality … parts and labour lewisham way