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NIPS
1998
15 years 7 months ago
Risk Sensitive Reinforcement Learning
In this paper, we consider Markov Decision Processes (MDPs) with error states. Error states are those states entering which is undesirable or dangerous. We define the risk with re...
Ralph Neuneier, Oliver Mihatsch
CN
2006
163views more  CN 2006»
15 years 6 months ago
A framework for mining evolving trends in Web data streams using dynamic learning and retrospective validation
The expanding and dynamic nature of the Web poses enormous challenges to most data mining techniques that try to extract patterns from Web data, such as Web usage and Web content....
Olfa Nasraoui, Carlos Rojas, Cesar Cardona
SIGIR
2008
ACM
15 years 6 months ago
Learning from labeled features using generalized expectation criteria
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
Gregory Druck, Gideon S. Mann, Andrew McCallum
BSN
2011
IEEE
233views Sensor Networks» more  BSN 2011»
14 years 6 months ago
Compressive Sensing of Neural Action Potentials Using a Learned Union of Supports
—Wireless neural recording systems are subject to stringent power consumption constraints to support long-term recordings and to allow for implantation inside the brain. In this ...
Zainul Charbiwala, Vaibhav Karkare, Sarah Gibson, ...
CVPR
2003
IEEE
16 years 8 months ago
Learning epipolar geometry from image sequences
We wish to determine the epipolar geometry of a stereo camera pair from image measurements alone. This paper describes a solution to this problem which does not require a parametr...
Yonatan Wexler, Andrew W. Fitzgibbon, Andrew Zisse...