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» Using Machine Learning to Focus Iterative Optimization
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HICSS
2009
IEEE
118views Biometrics» more  HICSS 2009»
15 years 10 months ago
Decentralized Reactive Power Dispatch for a Time-Varying Multi-TSO System
This paper addresses the problem of reactive power dispatch in a power system partitioned into several areas controlled by different transmission system operators. Previous resear...
Yannick Phulpin, Miroslav Begovic, Marc Petit, Dam...
IMCSIT
2010
15 years 1 months ago
A Breast Cancer Classifier based on a Combination of Case-Based Reasoning and Ontology Approach
Breast cancer is the second most common form of cancer amongst females and also the fifth most cause of cancer deaths worldwide. In case of this particular type of malignancy, earl...
Essam AbdRabou, Abdel-Badeeh Salem
ICML
2006
IEEE
16 years 3 months ago
Qualitative reinforcement learning
When the transition probabilities and rewards of a Markov Decision Process are specified exactly, the problem can be solved without any interaction with the environment. When no s...
Arkady Epshteyn, Gerald DeJong
GECCO
2004
Springer
106views Optimization» more  GECCO 2004»
15 years 8 months ago
Learning to Acquire Autonomous Behavior: Cooperation by Humanoid Robots
In this paper, we describe a cooperative transportation to a target position with two humanoid robots and introduce a machine learning approach to solving the problem. The difficul...
Yutaka Inoue, Takahiro Tohge, Hitoshi Iba
ICML
2006
IEEE
16 years 3 months ago
Totally corrective boosting algorithms that maximize the margin
We consider boosting algorithms that maintain a distribution over a set of examples. At each iteration a weak hypothesis is received and the distribution is updated. We motivate t...
Gunnar Rätsch, Jun Liao, Manfred K. Warmuth