This volume provides a systematic in-depth analysis of nonparametric learning. It covers the theoretical limits and the asymptotical optimal algorithms and esti

Bayesian nonparametrics works - theoretically, computationally. The theory provides highly flexible models whose complexity grows appropriately with the amount

The statistical and mathematical principles of smoothing with a focus on applicable techniques are presented in this book. It naturally splits into two parts: T

Focusing on quantative approaches to investigating problems, this title introduces the basics rules and principles of statistics, encouraging the reader to thin

Bayesian nonparametrics comes of age with this landmark text synthesizing theory, methodology and computation.