About
This school is suitable for all levels, both for people without previous knowledge in Machine Learning, and those wishing to broaden their expertise in this area. It will allow the participants to get in touch with international experts in this field. Exchange of students, joint publications and joint projects will result because of this collaboration. \ For a research student, the summer school provides a unique, high-quality, and intensive period of study. It is ideally suited for students currently pursuing, or intending to pursue, research in Machine Learning or related fields. Limited scholarships are available for students to cover accommodation and registration costs. If funds are available partial travel support might also be provided. \ IT professionals who use Machine Learning will find that the summer school provides relevant knowledge and exposure to contemporary techniques. In addition, they will benefit by direct interaction with top-notch researchers and knowledge workers. Previous experience indicates that personnel from both the industry as well as national laboratories like CSIRO, DSTO benefit immensely from the school. \ For academics, the summer school is an excellent opportunity to help getting started in research on novel topics in Machine Learning. It provides an ideal forum for networking and discussions. Academics will also benefit from interaction with IT professionals which will lead to a deeper understanding of real life problems.
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Uploaded videos:
Introduction
Introduction
Feb 25, 2007
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3112 Views
Lectures
Learning with Kernels
Feb 25, 2007
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13548 Views
Rapid Stochastic Gradient Descent: Accelerating Machine Learning
Feb 25, 2007
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10075 Views
Graphical Models for Structural Pattern Recognition
Feb 25, 2007
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12807 Views
Optimization for Kernel Methods
Feb 25, 2007
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6795 Views
Brain Computer Interfaces
Feb 25, 2007
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17254 Views
Reinforcement Learning
Feb 25, 2007
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29259 Views
Exponential Families in Feature Space
Feb 25, 2007
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4964 Views
Exponential Families
Feb 25, 2007
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20961 Views
Anti-Learning
Feb 25, 2007
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8437 Views
Learning techniques in Planning
Feb 25, 2007
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8936 Views
Measures of Statistical Dependence
Feb 25, 2007
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11040 Views
Policy-gradient Reinforcement Learning
Feb 25, 2007
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11073 Views
The Sparse Grid Method
Feb 25, 2007
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9354 Views
Introduction to Learning Theory
Feb 25, 2007
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30924 Views
Dirichlet Processes and Nonparametric Bayesian Modelling
Feb 25, 2007
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32258 Views
Information Retrieval and Text Mining
Feb 25, 2007
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15721 Views