Št. zadetkov: 24
Video in druga učna gradiva
Oznake:
computer science;machine learning
Recent work on collaborative filtering has led to a large number of both scalable and theoretically well founded algorithms. In this paper, we show that collaborative filtering and multitask learning are innately closely connected. In particular, the 'learning the kernel' paradigm in multitask learn ...
Leto:
2010
Vir:
videolectures.net
Video in druga učna gradiva
Oznake:
computer science;machine learning;kernel methods;multiple kernel learning
Leto:
2008
Vir:
videolectures.net
Video in druga učna gradiva
Oznake:
computer science;machine learning;linear models
In this course I will discuss how exponential families, a standard tool in statistics, can be used with great success in machine learning to unify many existing algorithms and to invent novel ones quite effortlessly. In particular, I will show how they can be used in feature space to recover Gaussia ...
Leto:
2004
Vir:
videolectures.net
Video in druga učna gradiva
Oznake:
computer science;machine learning;linear models
In this introductory course we will discuss how log linear models can be extended to feature space. These log linear models have been studied by statisticians for a long time under the name of exponential family of probability distributions. We provide a unified framework which can be used to view m ...
Leto:
2005
Vir:
videolectures.net
Video in druga učna gradiva
Oznake:
computer science;machine learning;linear models
In this introductory course we will discuss how log linear models can be extended to feature space. These log linear models have been studied by statisticians for a long time under the name of exponential family of probability distributions. We provide a unified framework which can be used to view m ...
Leto:
2006
Vir:
videolectures.net
Video in druga učna gradiva
Oznake:
computer science;machine learning;kernel methods
This lecture given by Mr. Smola is combined with Mr. Bernhard Schoelkopf and will encopass Part 1, Part 5, Part 6 of the complete lecture. \\ Part 2, 3 and 4 of this lecture can be found here [[mlss07_scholkopf_intkmet|//at Bernhard Schoelkopf's// "%title"]]
Leto:
2007
Vir:
videolectures.net
Video in druga učna gradiva
Oznake:
computer science;machine learning;kernel methods
The tutorial will introduce the main ideas of statistical learning
theory, support vector machines, and kernel feature spaces.
This includes a derivation of the support vector optimization
problem for classification and regression, the v-trick,
various kernels and an overview over applications o ...
Leto:
2008
Vir:
videolectures.net
Video in druga učna gradiva
Oznake:
computer science;optimization methods
In this talk I will discuss a number of vignettes on scaling optimization and inference. Despite arising from very different contexts (graphical models inference, convex optimization, neural networks), they all share a common design pattern - a synchronization mechanism in the form of a parameter se ...
Leto:
2012
Vir:
videolectures.net
Video in druga učna gradiva
Oznake:
computer science;machine learning;statistical learning
Leto:
2006
Vir:
videolectures.net
Video in druga učna gradiva
Oznake:
mathematics;statistics
Reproducing Kernel Hilbert Spaces have been mainly used for estimation. Distributional tests in this area were mainly concerned with tests for independence of random variables. We give concentration of measure bounds for the latter using an easy to compute criterion between spaces of observations. I ...
Leto:
2005
Vir:
videolectures.net