MLSS 2005 - Canberra

Machine Learning Summer School (MLSS), Canberra 2005

Machine Learning is a foundational discipline of the Information Sciences. It combines deep theory from areas as diverse as Statistics, Mathematics, Engineering, and Information Technology with many practical and relevant real life applications. The aim of the summer school is to cover the entire spectrum from theory to practice. It is mainly targeted at research students, IT professionals, and academics from all over the world.

Categories

Top » Computer Science » Machine Learning


Lectures
[syn] 154208 views, 6:39:02 Probabilistic Graphical ModelsProbabilistic Graphical Models Sam Roweis Sam Roweis 24 comments	[syn] 7533 views, 3:03:31 How to predict with Bayes, MDL, and ExpertsHow to predict with Bayes, MDL, and Experts Marcus Hutter Marcus Hutter	[syn] 19351 views, 1:49:01 Generalized Principal Component Analysis (GPCA)Generalized Principal Component Analysis (GPCA) René Vidal René Vidal 8 comments	[syn] 5747 views, 1:53:54 Text CategorizationText Categorization Jon David Patrick Jon David Patrick	[syn] 73222 views, 5:44:22 Independent Component AnalysisIndependent Component Analysis Aapo Hyvärinen Aapo Hyvärinen 19 comments
[syn] 9942 views, 3:59:04 Gradient Methods for Machine LearningGradient Methods for Machine Learning Nicol Schraudolph Nicol Schraudolph 2 comments	[syn] 7652 views, 3:17:29 Exponential Families in Feature SpaceExponential Families in Feature Space Alex Smola Alex Smola 1 comment	[syn] 4045 views, 47:31 Exponential Families in Feature Space - Part 5Exponential Families in Feature Space - Part 5 S.V.N. Vishwanathan S.V.N. Vishwanathan	[syn] 4015 views, 59:27 Exponential Families in Feature Space - Part 6Exponential Families in Feature Space - Part 6 S.V.N. Vishwanathan S.V.N. Vishwanathan	[syn] 11208 views, 3:15:09 Kernel Methods for Higher Order Image StatisticsKernel Methods for Higher Order Image Statistics Matthias O. Franz Matthias O. Franz 6 comments
[syn] 6398 views, 3:10:51 MarkusSparse Grid MethodsMarkusSparse Grid Methods Markus Hegland Markus Hegland	[syn] 7199 views, 1:31:32 Reinforcement LearningReinforcement Learning Douglas Aberdeen Douglas Aberdeen	[syn] 20332 views, 2:32:26 Graph Matching AlgorithmsGraph Matching Algorithms Terry Caelli Terry Caelli 6 comments	[syn] 16189 views, 5:44:47 Machine Learning for GamesMachine Learning for Games Thore Graepel Thore Graepel	[syn] 7449 views, 3:22:36 Bioinformatics Challenge: Learning in Very High Dimensions with Very Few SamplesBioinformatics Challenge: Learning in Very High Dimensions with Very Few ... Adam Kowalczyk Adam Kowalczyk 4 comments