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NECO
2007
150views more  NECO 2007»
15 years 1 days ago
Reinforcement Learning, Spike-Time-Dependent Plasticity, and the BCM Rule
Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Dorit Baras, Ron Meir
105
Voted
DAGM
2003
Springer
15 years 5 months ago
Learning Human-Like Opponent Behavior for Interactive Computer Games
Compared to their ancestors in the early 1970s, present day computer games are of incredible complexity and show magnificent graphical performance. However, in programming intelli...
Christian Bauckhage, Christian Thurau, Gerhard Sag...
101
Voted
CDC
2009
IEEE
124views Control Systems» more  CDC 2009»
15 years 5 months ago
The Kalman like particle filter: Optimal estimation with quantized innovations/measurements
— We study the problem of optimal estimation using quantized innovations, with application to distributed estimation over sensor networks. We show that the state probability dens...
Ravi Teja Sukhavasi, Babak Hassibi
90
Voted
WSC
1998
15 years 1 months ago
Informational Macrodynamics: System Modelling and Simulation Methodologies
Informational Macrodynamics (IMD) presents a unified informational systemic approach with common information language for modeling, analysis and optimization of a variety of inter...
Vladimir S. Lerner
MM
2009
ACM
203views Multimedia» more  MM 2009»
15 years 5 months ago
Distance metric learning from uncertain side information with application to automated photo tagging
Automated photo tagging is essential to make massive unlabeled photos searchable by text search engines. Conventional image annotation approaches, though working reasonably well o...
Lei Wu, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Ne...