DOIAbstract
Sure to be influential, this book lays the foundations for the use of algebraic geometry in statistical learning theory
Sure to be influential, this book lays the foundations for the use of algebraic geometry in statistical learning theory
Statistical Learning Theory now plays a more active role after the general analysis of learning pro...
Statistical learning theory provides the theoretical basis for many of today's machine learning algo...
Statistical learning theory provides the theoretical basis for many of today's machine learning algo...
An up-to-date account of algebraic statistics and information geometry, which also explores the emer...
How does an algebraic geometer studying secant varieties further the understanding of hypothesis tes...
This up-to-date account of algebraic statistics and information geometry explores the emerging conne...
This up-to-date account of algebraic statistics and information geometry explores the emerging conne...
In algebraic statistics, computational techniques from algebraic geometry become tools to address st...
In algebraic statistics, computational techniques from algebraic geometry become tools to address st...
Algebraic statistics uses tools from algebraic geometry, commutative algebra, combinatorics, and the...
This book provides an introduction to various aspects of Algebraic Statistics with the principal aim...
This book provides an introduction to various aspects of Algebraic Statistics with the principal aim...
We develop the necessary theory in computational algebraic geometry to place Bayesian networks into ...
A general mathematical framework is developed for learning algorithms. A learning task belongs to ei...
Statistical learning theory provides the theoretical basis for many of today's machine learning algo...
Statistical Learning Theory now plays a more active role after the general analysis of learning pro...
Statistical learning theory provides the theoretical basis for many of today's machine learning algo...
Statistical learning theory provides the theoretical basis for many of today's machine learning algo...
An up-to-date account of algebraic statistics and information geometry, which also explores the emer...
How does an algebraic geometer studying secant varieties further the understanding of hypothesis tes...
This up-to-date account of algebraic statistics and information geometry explores the emerging conne...
This up-to-date account of algebraic statistics and information geometry explores the emerging conne...
In algebraic statistics, computational techniques from algebraic geometry become tools to address st...
In algebraic statistics, computational techniques from algebraic geometry become tools to address st...
Algebraic statistics uses tools from algebraic geometry, commutative algebra, combinatorics, and the...
This book provides an introduction to various aspects of Algebraic Statistics with the principal aim...
This book provides an introduction to various aspects of Algebraic Statistics with the principal aim...
We develop the necessary theory in computational algebraic geometry to place Bayesian networks into ...
A general mathematical framework is developed for learning algorithms. A learning task belongs to ei...
Statistical learning theory provides the theoretical basis for many of today's machine learning algo...
Statistical Learning Theory now plays a more active role after the general analysis of learning pro...
Statistical learning theory provides the theoretical basis for many of today's machine learning algo...
Statistical learning theory provides the theoretical basis for many of today's machine learning algo...
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