Dimensionality Reduction
اختزال وتقليص الأبعاد الحسابية
تقنيات ضغط واختزال للفضاء الرياضي تهدف لتقليل عدد متغيرات البيانات مع الحفاظ على أهم خصائصها الدالة.
Dimensionality Reduction
Also translated asضغط المساحات المتجهية الكثيفة، تبسيط الفضاء الرياضي للمصفوفات، اختزال الأبعاد
First appears in this corpus in: On Lines and Planes of Closest Fit to Systems of Points in Space (1901)
Appears in these papers
- Reducing the Dimensionality of Data with Neural Networks2006in the sky ✦
- Reducing the Dimensionality of Data with Neural Networks2006in the sky ✦
- K-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation2006in the sky ✦
- Face Recognition Using Eigenfaces1991in the sky ✦
- Face Recognition Using Eigenfaces1991in the sky ✦
- GloVe: Global Vectors for Word Representation2014in the sky ✦
- Going Deeper with Convolutions2014in the sky ✦
- Amazon.com Recommendations: Item-to-Item Collaborative Filtering2003in the sky ✦
- Nearest Neighbor Pattern Classification1967in the sky ✦
- On Lines and Planes of Closest Fit to Systems of Points in Space1901in the sky ✦
- On Lines and Planes of Closest Fit to Systems of Points in Space1901in the sky ✦
- Random Features for Large-Scale Kernel Machines2007in the sky ✦
- Representation Learning: A Review and New Perspectives2013in the sky ✦
- Emergence of Simple-Cell Receptive Field Properties by Learning a Sparse Code for Natural Images1996in the sky ✦
- On Spectral Clustering: Analysis and an Algorithm2001in the sky ✦
- UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction2018in the sky ✦
- UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction2018in the sky ✦