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» Information Geometry of Neural Networks
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NN
2007
Springer
105views Neural Networks» more  NN 2007»
15 years 3 months ago
Guiding exploration by pre-existing knowledge without modifying reward
Reinforcement learning is based on exploration of the environment and receiving reward that indicates which actions taken by the agent are good and which ones are bad. In many app...
Kary Främling
137
Voted
ICANN
2010
Springer
15 years 2 months ago
Dynamic Shape Learning and Forgetting
In this paper, we present a system capable of dynamically learning shapes in a way that also allows for the dynamic deletion of shapes already learned. It uses a self-balancing Bin...
Nikolaos Tsapanos, Anastasios Tefas, Ioannis Pitas
131
Voted
NN
2008
Springer
15 years 2 months ago
Sensory adaptation in human balance control: Lessons for biomimetic robotic bipeds
- This paper describes mechanisms used by humans to stand on moving platforms, such as a bus or ship, and to combine body orientation and motion information from multiple sensors i...
Arash Mahboobin, Patrick J. Loughlin, Mark S. Redf...
154
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JMLR
2002
133views more  JMLR 2002»
15 years 3 months ago
Learning Precise Timing with LSTM Recurrent Networks
The temporal distance between events conveys information essential for numerous sequential tasks such as motor control and rhythm detection. While Hidden Markov Models tend to ign...
Felix A. Gers, Nicol N. Schraudolph, Jürgen S...
MOBIHOC
2006
ACM
16 years 3 months ago
Distributed localization using noisy distance and angle information
Localization is an important and extensively studied problem in ad-hoc wireless sensor networks. Given the connectivity graph of the sensor nodes, along with additional local info...
Amitabh Basu, Jie Gao, Joseph S. B. Mitchell, Giri...