Pages that link to "Item:Q3304733"

The following pages link to Turning Big Data Into Tiny Data: Constant-Size Coresets for $k$-Means, PCA, and Projective Clustering (Q3304733):

Displaying 12 items.

• Faster coreset construction for projective clustering via low-rank approximation (Q1671019) (← links)
• The spherical \(k\)-means++ algorithm via local search scheme (Q2084616) (← links)
• Improved local search algorithms for Bregman \(k\)-means and its variants (Q2084627) (← links)
• Lossy kernelization of same-size clustering (Q2097218) (← links)
• Minimum cost‐compression risk in principal component analysis (Q6075174) (← links)
• A novel method for optimizing spectral rotation embedding \(K\)-means with coordinate descent (Q6125254) (← links)
• On coresets for fair clustering in metric and Euclidean spaces and their applications (Q6152182) (← links)
• Turning Grain Maps into Diagrams (Q6173521) (← links)
• Lossy kernelization of same-size clustering (Q6174654) (← links)
• Coresets for kernel clustering (Q6613883) (← links)
• Core-elements for large-scale least squares estimation (Q6643225) (← links)
• A principal-weighted penalized regression model and its application in economic modeling (Q6662620) (← links)