Learning from Multiple Sources

Recent Events more...

Twenty-Fifth Annual Conference on Neural Information Processing Systems (NIPS) 2011

You are invited to participate in the Twenty-Fifth Annual Conference on Neural Information Processing Systems, which is the premier scientific ...

NIPS 2011 Workshops

The Post-Conference Workshop Program covered a wide range of topics from Neuroscience to Machine Learning. Detailed information can be found ...

2nd Workshop on Applications of Pattern Analysis 2011

Pattern Analysis and Statistical Learning cover a wide range of technologies and theoretical frameworks, and significant activity in the past ...

Machine Learning Summer School 2011 - Bordeaux

The school provides tutorials and practical sessions on basic and advanced topics of machine learning by leading researchers in the ...

International Workshop on Social Web Mining

There is an increasing interest in social web mining, as we can see from the ACM workshop on Social Web ...

Project summary - PASCAL NoE

PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

The objective is to build a Europe-wide Distributed Institute which will pioneer principled methods of pattern analysis, statistical modelling and computational learning as core enabling technologies for multimodal interfaces that are capable of natural and seamless interaction with and among individual human users. more information >>>

Workshops

NIPS 2011 Workshops

The Post-Conference Workshop Program covered a wide range of topics from Neuroscience to Machine Learning. Detailed information can be found ...

2nd Workshop on Applications of Pattern Analysis 2011

Pattern Analysis and Statistical Learning cover a wide range of technologies and theoretical frameworks, and significant activity in the past ...

International Workshop on Social Web Mining

There is an increasing interest in social web mining, as we can see from the ACM workshop on Social Web ...

TUTORIALS: more...

[syn] 30927 views, 4:59:00 Machine Learning, Probability and Graphical ModelsMachine Learning, Probability and Graphical Models Sam Roweis Sam Roweis 31 comments	[syn] 22818 views, 3:54:22 Support Vector MachinesSupport Vector Machines Chih-Jen Lin Chih-Jen Lin 29 comments	[syn] 21534 views, 2:51:03 Introduction To Bayesian InferenceIntroduction To Bayesian Inference Christopher Bishop Christopher Bishop 5 comments
[syn] 18584 views, 5:22:53 Monte Carlo Simulation for Statistical Inference, Model Selection and Decision Making Monte Carlo Simulation for Statistical Inference, Model Selection and Decision ... Nando de Freitas Nando de Freitas 22 comments	[syn] 14752 views, 42:39 A Tutorial Introduction to Stochastic Differential Equations: Continuous-time Gaussian Markov ProcessesA Tutorial Introduction to Stochastic Differential Equations: Continuous-time Gaussian Markov ... Chris Williams Chris Williams 12 comments	[syn] 13399 views, 2:27:56 Markov Chain Monte CarloMarkov Chain Monte Carlo Iain Murray Iain Murray 5 comments

SCHOOLS:

Machine Learning Summer School 2011 - Bordeaux
The school provides tutorials and practical sessions on basic and advanced topics of machine learning by leading researchers in the ...

Machine Learning Summer School 2010 - Canberra
Machine Learning is a foundational discipline of the Information Sciences. It combines deep theory from areas as diverse as Statistics, ...

Cognitive Science and Machine Learning Summer School 2010 - Sardinia
Cognitive science aims to reverse engineer human intelligence; machine learning provides one of our most powerful sources of insight into ...

Machine Learning Summer School 2009 - Cambridge
The 13th Machine Learning Summer School was held in Cambridge, UK. This year's edition was organized by the University of ...

Machine Learning Summer School on Theory and Practice of Computational Learning
The theme of this year's summer school is Theory and Practice of Computational Learning, to be held in conjunction with ...

From:
To:

View order

Topic taxonomy

Type of content

Language

Year

Learning from Multiple Sources

Learning from Multiple Sources

NIPS ´08 Workshop: Kernel Learning - Automatic Selection of Optimal Kernels

27th International Conference on Machine Learning 2010 - Haifa

European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)

Optimization

Spring School in Complexity Science

ILP/MLG/SRL collocated International conferences/workshops on learning from relational, graph-based and probabilistic knowledge

Students Session

PASCAL Bootcamp in Machine Learning

Third International Workshop on Machine Learning in Systems Biology

NIPS ´08 Workshop: Causality: objectives and assessment

MLG - 2008: 6th International Workshop on Mining and Learning with Graphs

Workshop on Applications of Pattern Analysis 2010

Workshop

Sparsity and Inverse Problems in Statistical Theory and Econometrics

International Workshop on Social Web Mining

NIPS '07 Workshop on Approximate Bayesian Inference in Continuous/Hybrid Models

Learning and Inference in Computational Systems Biology

Sparsity in Machine Learning and Statistics

Machine Learning Summer School 2008 - Kioloa

Open House on Multi-Task and Complex Outputs Learning 2006 - London

Sessions

PASCAL First Challenges Workshop 2005 - Southampton

Machine Learning Summer School 2003 - Tübingen

Machine Learning Summer School 2006 - Taipei

Machine Learning

LEARNING Conference 2006 - Vilanova

Optimization for Machine Learning

Machine Learning and Cognitive Science of Language Acquisition

BBCI Workshop 2009 - Advances in Neurotechnologies

Clustering

6th IARP -TC-15 Workshop on Graphbased Representations in Pattern Recognition

NIPS 2011 Workshops

9th International Colloquium on Grammatical Inference

14th International Conference on Artificial Intelligence and Statistics 2011 - Ft. Lauderdale

International Conference on Multimodal Interfaces 2005 - Trento

Computational Biology

Talks

Machine Learning Summer School 2002 - Canberra

Special Session

Machine Learning Summer School 2010 - Canberra

NIPS ´08 Workshop: Optimization for Machine Learning

NIPS ´08 Workshop: Machine Learning Open Source Software

International Workshop - Machine Learning for Aerospace

The 5th International Workshop on Mining and Learning with Graphs

Machine Learning Summer School 2005 - Canberra

Workshop on New Directions on Decoding Mental States from fMRI Data 2006 - Whistler

Joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR 2010) and Statistical Techniques in Pattern Recognition (SPR 2010)

Modelling in Classification and Statistical Learning Workshop 2004 - Eindhoven

The 25th International Conference on Machine Learning (ICML 2008)

10th International Conference on User Modeling: Workshop on Machine Learning for User Modeling: Challenges 2005 - Edinburgh

Sessions

Workshop on On‐lineTrading of Exploration and Exploitation 2

Generative / Discriminative Interface

Type I and type II errors for Multiple Simultaneous Hypothesis Testing

Learning on Cores, Clusters, and Clouds

Sessions

Oral Sessions

Conference Sessions

Probabilistic Modeling and Machine Learning in Structural and Systems Biology 2006 - Tuusula

Machine Learning Summer School 2006 - Canberra

Award Paper Joint Session

Optimization and inference in machine learning and physics workshop 2005 - Lavin

JOINT AMI/PASCAL/IM2/M4 Workshop on Multimodal Interaction and Related Machine Learning Algorithms 2004 - Martigny

Kernels for Multiple Outputs and Multi-task Learning

NIPS ´08 Workshop: New Challenges in Theoretical Machine Learning: Learning with Data-dependent Concept Spaces

International Workshop on Intelligent Information Access 2006 - Helsinki

Sessions

Regression in Robotics - Approaches and Applications

PASCAL Bootcamp in Machine Learning

The 18th European Conference on Machine Learning (ECML) and the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD)

Machine Learning Summer School 2004 - Berder Island

Machine Learning Summer School 2005 - Chicago

NIPS '07 Workshop on Efficient Machine Learning