Pages that link to "Item:Q3546516"
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The following pages link to Individual Convergence Rates in Empirical Vector Quantizer Design (Q3546516):
Displaying 12 items.
- Fast rates for empirical vector quantization (Q351685) (← links)
- A statistical view of clustering performance through the theory of \(U\)-processes (Q392047) (← links)
- Empirical risk minimization for heavy-tailed losses (Q892246) (← links)
- Redesigning vector quantizers using implicitly estimated probability density functions (Q1010172) (← links)
- A notion of stability for \(k\)-means clustering (Q1711576) (← links)
- On Hölder fields clustering (Q1936547) (← links)
- On strong consistency of kernel \(k\)-means: a Rademacher complexity approach (Q2070586) (← links)
- Nonasymptotic bounds for vector quantization in Hilbert spaces (Q2343956) (← links)
- Bandwidth selection in kernel empirical risk minimization via the gradient (Q2515491) (← links)
- Statistical learning guarantees for compressive clustering and compressive mixture modeling (Q2664825) (← links)
- Convergence of Vector Quantizers with Applications to Optimal Quantization (Q3314662) (← links)
- Dimensionality-Dependent Generalization Bounds for <i>k</i>-Dimensional Coding Schemes (Q5380581) (← links)
